The Game Has Changed

I’ve spent much of my career at the intersection of technology and human endeavor, from gaming to organizational design in large companies. In titles like League of Legends, the “meta” is the most effective tactic available—an emergent pattern of strategies, builds, and compositions that shifts as the game’s mechanics change.

When a patch drops, the meta doesn’t adjust—it transforms. Optimality is dynamic—it's a response to change.

Today, the rapid advancement of artificial intelligence (AI) is reshaping the way we work, challenging traditional roles, and forcing us to rethink the structure of organizations. The current approach of bolting AI onto existing organizational structures and processes is reactive and fails to capture the systemic value that AI promises.

The core problem is not a lack of tools or use cases, but a lack of a strategic framework for redesigning the organization itself.

We don’t know how far AI will ultimately advance—whether we stop at powerful narrow AI, reach artificial general intelligence (AGI), or one day confront artificial superintelligence (ASI). However, in the current transition, those unable to adapt and adjust will be dramatically disadvantaged.

This is where I introduce a concept I call The Organizational Meta.

In League of Legends, a meta shift changes the competitive environment and the optimal ways to win. The same thing is happening inside companies, except the "patch" is the relentless advance of AI capabilities.

In this context, the Organizational Meta refers to the optimal organizational structure that emerges based on AI's current capabilities and limitations.

Working definition: Organizational Meta is the current best configuration of roles, teams, workflows, and artifacts that maximizes outcomes, especially given AI’s evolving capabilities and constraints—reviewed and “patched” on a fixed cadence.

To win, leaders must stop reacting to the patch notes and start proactively designing their meta.

A New Physics of Organizations

We stand at an inflection point. The traditional physics of organizations—built on assumptions of human cognitive limits, communication costs, and specialized expertise—is breaking down. AI has changed the fundamental constants.

Consider what's actually happening:

• Individuals with AI can perform tasks that once required entire departments

• Cognitive work that took weeks now takes hours

• Expertise that took years to develop can be synthesized in moments

• Coordination overhead that justified management layers has evaporated

Yet most organizations still operate as if these changes are incremental optimizations rather than a phase transition. They're adding AI to existing roles, much like adding faster horses to carriages, without recognizing that the entire vehicle needs redesigning.

This isn't about job replacement. It's about something far more profound: the emergence of entirely new organizational structures optimized for human-AI collaboration.

The Organizational Meta isn't just a framework—it's an evolutionary imperative.

Rethinking Organizational Structure

Given the dramatic impact of AI on work, a maximally efficient and effective company should think about organizational structure from first principles.

More specifically, designing an appropriate Organizational Meta should be considered with a reconsideration of the organizational design of a company’s people (roles and teams) and practices (artifacts and workflows).

ROLES -> Hybridization and Compression

Traditional organizations evolved around a simple constraint: human limitations. We created roles because individuals couldn't hold all necessary expertise. We built hierarchies because coordination required dedicated overhead. We separated functions because expertise was specialized and siloed.

AI obliterates these constraints, creating what I call the Compression Phenomenon. It manifests in two dimensions:

Intra-role compression: AI handles the routine, computational, and even some creative aspects within a role, leaving only the uniquely human elements.

Inter-role compression: Entire roles merge as AI eliminates the friction between domains. The boundaries between product, engineering, design, and marketing dissolve.

But here's what most miss: compression isn't just about efficiency. It's about emergence. When you compress carbon under extreme pressure, you don't get smaller carbon—you get diamond. Similarly, role compression creates entirely new capabilities.

A Product Engineer isn't just a product manager who codes or an engineer who thinks about users. They're something qualitatively different: someone who can hold the entire product in their head, from user insight to implementation detail, orchestrating AI to handle what would have required a team of specialists.

In the traditional organization, the atomic unit was the individual role. In the AI-native organization, it's the human-AI hybrid capability. Let me make this concrete:

Traditional Atomic Unit: Frontend Engineer

• Writes React components

• Implements designs

• Debugs browser issues

• Optimizes performance

New Atomic Unit: Design Technologist + AI Ensemble

• Envisions user experiences and prompts AI to generate multiple implementations

• Orchestrates AI agents to create, test, and refine design systems

• Focuses on taste, judgment, and creative vision while AI handles execution

• Can produce in a day what previously took a team weeks

The crucial insight: the new atomic unit isn't smaller—it can be much more powerful. It combines human judgment, creativity, and context with AI's computational power and consistency.

We'll likely see the emergence of an increase in hybrid positions:

• Product Engineers: Combining technical implementation with product thinking

• Design Technologists: Merging creative design with technical execution

• Data PMs: Fusing data analysis with product strategy

• Growth Marketer: Combining growth techniques with product design

Example Potential Role Evolution:

These are just examples, but the specific “role+1” (or more than one role) and adjusted scope of work per role to maximally drive efficiency will be product-specific.

Where interfaces become clean, hybrids dominate; where interfaces stay messy, roles decompose more slowly, and artifacts carry more load.

TEAMS -> Smaller, Faster, Cross-Functional

As roles shift and AI subsumes more and more work, the most efficient and effective team structure should be thoughtfully and holistically reconsidered.

• Do you need 10 engineers or 2?

• Do you need 300 people generating ad creatives or 3?

• Do you need 5 engineers, 3 product managers, and 2 marketers, or do you need 2 product marketing engineers?

The implications of optimized role and team changes should become clear:

• A 5-person team with AI might outperform a traditional 20-person team

• Reduced coordination overhead

• Faster decision-making cycles

• More ownership and fewer blockers per individual

These newly designed team structures will be based on what maximizes product velocity and outcomes.

Furthermore, we need to become comfortable with teams that dynamically form and reform based on specific challenges or problems, rather than relying on fixed departments.

ARTIFACTS -> Complete Redesign + Usability of Informal Knowledge

Work artifacts, such as documents, diagrams, and data analysis, are generated for a specific purpose and audience.

The modern enterprise needs to design artifacts for the consumers it actually has. If an agent must read it, it needs structure—intent, constraints, evals, and state—not prose alone.

In the new world of AI, artifacts should be redesigned to consider what is required given 1. role compression and 2. how work artifacts will be consumed not just by humans but also by AI and agents.

If a design and engineering role is compressed into a single design engineering role, does the person designing a product feature necessarily need a complete design spec or PRD? Is there another form of document that would better serve the needs of that new role, given their objective?

What if the engineer is an AI? An AI generating code may be better served by an extensive prompt optimized for an LLM rather than a traditional design spec or PRD.

The bigger point here is that revised roles and AI/agents create a need to thoroughly re-evaluate whether the workplace artifacts currently used are optimally serving their purpose.

An additional opportunity in the new world of AI is the potential to generate artifacts from informal or semi-formal corporate knowledge.

While formal artifacts are standardized and designed for usability and shareability within an enterprise, we find two issues when it comes to informal or semi-formal enterprise knowledge:

1. Information Defection: A lot of information that should be codified and shared in formal documents often leaks into informal systems. Lack of discipline and the practical realities of day-to-day work frequently lead to information leaking into verbal conversations, notes, and untracked Figjam boards.

2. Informal Information Loss: Valuable enterprise knowledge captured in informal or semi-formal systems is not tracked, not accessible or shareable, and lacks a mechanism for surfacing to other employees who may find the information valuable.

Hence, another significant area of productivity unlock will come from AI’s ability to capture, formalize, store, and share previously informal and semi-formal knowledge into usable artifacts.

As a specific example, imagine a team evaluating several vendors to help determine what analytics platform they would like to use. They may have whiteboard sessions, face-to-face discussions, and many Zoom calls with different vendors. Various team members maintain their informal notes. Meetings are then called, followed by discussions, and ultimately, a decision framework is established. At some point, a document may be created to codify how the decision was made.

However, a more usable artifact would be if every discussion were summarized and structured into a formal “Analytics Vendors Evaluation” document of some kind that automatically gets updated with new meeting notes. A framework for evaluation could have been pre-determined, automatically filled in, and presented for review by an AI. Every meeting that any team member takes could get recorded, transcribed, and relevant information automatically updated in the Analytics Vendors Evaluation document. An agent watching that doc could automatically alert teammates to new information or proactively identify a new data comparison point to research and fill in. AI could also be used to critically analyze the decision framework, suggesting improvements and updating any missing information via agents.

Hence, the key point here is that the impact of AI on enterprise artifacts remains at the very early stages of driving productivity gains. To drive higher productivity from artifacts, they should be reconsidered entirely and redesigned. Further, a potential massive unlock for additional productivity could be through the creation of new AI-native artifacts that contemplate the capabilities of AI and agents from first principles.

Key Principles:

• Critically re-evaluate existing enterprise artifacts to determine whether they are still necessary. What happens if some of these artifacts are deleted (maybe nothing)?

• Redesign artifacts to be maximally efficient and effective based on updated roles and to better work with AI.

• Make artifact surfaces agentable. Replace narrative-only documents with structured intents (goals, constraints, acceptance criteria), explicit state, and linked evals.

• Treat informal knowledge as a first-class input to agent-legible artifacts: capture, structure, and surface it in schemas that agents can consume.

WORKFLOWS -> Adapt for AI, Automation, and Agents

Workflows should consider newly designed roles, team structures, updated artifact designs, and most importantly, how AI fits into the picture—especially with the integration of agents to automate and coordinate different kinds of work.

If you believe that product velocity will be the primary basis of competition in the future, workflow optimization will be a critical component of designing an organization for super high velocity.

Current workflows designed with legacy departmental hand-offs, alignment/coordination, and human labor in mind should be reconsidered. Every major workflow should be broken down into component workflow steps, and every step should consider AI and agents.

Critical: Any non-agentable workflow step becomes the rate limiter of product velocity.

Most importantly, specific workflow steps that block AI or agentic use should be redesigned. For instance, if a current workflow involves updating an Excel spreadsheet with pricing data, which is then uploaded to a website, redesigning the pricing data to be stored as a file or within a database that can be more easily modified by AI/agents should be considered.

Durable advantage accrues to organizations that minimize non-agentable surfaces (private file silos, tacit approvals, ad hoc formats).

Human verification or review points should also be integrated into the workflow where there is a risk of AI error or hallucinations.

Understanding AI’s Limitations

Design begins with constraints. As AI continues to improve, the best way to optimally design for organizational meta may be through having a deep understanding of AI’s limitations.

More specifically, consider these potential areas for limitations by AI:

1. Creativity – Generating genuinely novel, resonant ideas that connect with culture, emotion, and human experience.

2. Multi-Step, Long-Horizon Work – Managing work that unfolds over many steps and months (or years) without losing the thread.

3. Complex Collaboration – Integrating new, unpredictable inputs from multiple people and disciplines into a coherent whole.

4. Judgment – Making nuanced and contextual decisions when data is incomplete or ambiguous. Ability to do proper eval and determine hallucinations.

5. Contextual Awareness – Understanding the specialized, nuanced, and domain-specific details that affect decisions and execution.

The areas where AI has constraints should help define where humans add the most value.

Assign agents where failure is cheap and evals are strong; assign humans where failure is costly, context is tacit, or goals are renegotiated in flight. Everything else—roles, teams, artifacts, workflows—flows from this constraint surface.

Looking back at our People and Process framework, we can see that the use of AI may dramatically increase Product Velocity through human + AI hybrid work. However, determining what to build and evaluating product outputs may (at least currently) still be best executed by humans.

The Organizational Orchestrator Role

In this new world, someone must architect the organization itself. Not manage it—architect it. This role, which I call the Organizational Orchestrator, becomes perhaps the most critical in any company.

The Orchestrator doesn't manage people or projects. They design the system within which work happens. Their responsibilities:

Capability Architecture: Maintain a living map of what is AI-led vs. human-led, continuously experiment with AI, and understand current limitations.

Meta Optimization: Recompose roles and teams and redesign artifacts and workflows to optimize efficiency and effectiveness.

Evaluation: Always monitor the effectiveness of roles/teams/artifacts/workflows. Create simple KPIs to demonstrate efficiency and effectiveness. Require reversible changes by default, with explicit rollback plans.

Returns to Intelligence: Re-allocate human time and agent capacity to the current bottleneck where a marginal unit of intelligence yields the largest cycle-time or outcome gain.

This isn't a Chief Technology Officer or a Chief Operating Officer. It's something new: someone who thinks about organizations the way a game designer thinks about game balance. They understand that in a world of rapidly evolving AI, organizational structure itself must be dynamic.

The orchestrator is a hybrid: technologist (reads/defines evals, understands agent limits), organizational designer (recomputes roles and teams), operator (optimizes for cycle time and outcomes), and ethicist (knows when to add friction). Treat it as a capability to build, not a project to assign.

In doing so, the following three questions should be deeply considered:

1. Deliverables – What are we producing, and what makes it good?

2. Objectives – What are we trying to achieve, and how can AI help?

3. Effectiveness – What’s now possible—or possible to improve—because of AI?

These questions anchor the search for alpha in organizational design.

Conclusion: Why the Organizational Meta Matters

Just like with every technological shift in the past, new winners and losers will be created by this new environment of AI.

In the grind of day-to-day life, we can underappreciate or forget that AI is the most transformative and impactful technology in human history and likely the history of Earth.

Regulation, culture, and infrastructure will modulate the pace. I may be wrong on timing, but I doubt I’m wrong on direction.

Organizations that cling to rigid, vertically siloed structures will find themselves uncompetitive. The winners will be the ones who can continuously adapt their Organizational Meta to align human strengths with AI capabilities.

During GDC, AWS and CleverTap sponsored a Product x LiveOps Symposium event, including a panel, "The Evolution of the Product Manager," dissecting the significant industry changes and their implications for the role of PM.

This post distills some of the most compelling observations and actionable takeaways from these discussions. It will explore the macro forces reshaping game development, the tangible impact of AI (both current and future), the shifting identity and skillset required of product managers, and crucial strategies for thriving in this dynamic new era.

Watch the full video below, including an after-panel discussion with me, AWS (Tim Hong) + CleverTap (Solomon Lichter) below! 👇👇👇

🎧 Listen on Spotify, Apple Podcasts, or Anchor

Speakers:

• Oren Debi. Generative AI Lead & VP Product at SciPlay.

• David Duong. Sr. Director of Product Management at Respawn Entertainment (Apex Legends).

• Tim Hong. Head of Live Service Games at AWS for Games.

• Lee Horn. Fmr. VP of Product & Game Director at Mountaintop Studios.

• Joseph Kim. CEO at Lila Games.

• Solomon Lichter. Sr. Director, Global Gaming at CleverTap.

Part 1: Decoding the Product x LiveOps Panel – The Product Manager in Flux

We are faced with an industry undergoing significant change, which is forcing the evolution of the product management role within it.

The New Battlefield: Macro Trends Redefining Game Development

Several powerful macro trends are fundamentally altering the terrain for game developers and product managers (PMs). These aren't isolated phenomena but rather interconnected forces that create a complex new competitive environment.

• The Attention Economy Squeeze: A primary challenge is the "attention economy." In the discussion, we highlighted that "getting attention, especially when launching a new game, has become increasingly difficult" due to the sheer volume of competing products vying for a user’s time, including video-on-demand, social media, TikTok, and the growing dominance of popular, live-operated games. This isn't merely about an increase in the number of games; it signifies a fundamental shift in how players allocate their finite leisure time. For executives and PMs, this translates into an arduous uphill battle for visibility and initial player traction for new titles. Consequently, more innovative and potent marketing and engagement strategies are demanded from the very conception of a game. The scarcity of attention directly influences return on investment calculations for new intellectual property. Studios may need to anticipate higher user acquisition costs or accept longer payback periods, which in turn can sway decisions about which projects get the green light, potentially favoring more established IP or less experimental concepts.

• The Colossus of Global Competition: The "rise of China" continues to impact our industry as a formidable competitive force, with "extremely big-budget, huge teams working 996," making it "very difficult to compete against them." David Duong from EA, working on Apex Legends, reinforced this by citing the example of Marvel Rivals, which is launching four new characters in a single season—a content velocity he described as "insane" and something that has "massively raised player expectations." This isn't just about more competitors; it establishes a new global benchmark for content volume and production cadence. Western studios now find themselves contending with development entities operating under vastly different economic and labor paradigms, and this directly reshapes player expectations worldwide. This intense competitive pressure, particularly concerning the speed of content delivery, may serve as a catalyst, accelerating the adoption of AI tools for content creation and workflow optimization not merely as an enhancement but as a fundamental competitive necessity. If competitors can produce vast amounts of content rapidly, maintaining player engagement without similar output becomes a significant challenge, pushing studios towards AI solutions to bridge the gap.

• LiveOps: The Resurgent King: A "resurgence in LiveOps" was one of the biggest trends of last year, when games like Brawl Stars reportedly increased their revenue sixfold: a significant revelation of what’s possible for even older live-operated games. This success underscores a fundamental question in today's market: "How do you succeed in new game development when it's so challenging?" The sustained triumph of long-tenured LiveOps games provides a validated model for achieving enduring revenue streams and player engagement. For PMs and studio executives, this observation reinforces the critical importance of long-term product strategy, continuous and meaningful content delivery, and robust community management, moving away from a "launch and leave" mentality. The pronounced difficulty in successfully launching new games, stemming from the crowded attention economy and fierce competition, makes investing in and nurturing existing successful LiveOps titles an increasingly attractive, and potentially less risky, proposition for studios. This can lead to a strategic reallocation of resources within organizations, prioritizing the known quantities of successful live games over the uncertainties of new ventures.

• Navigating Incumbents and Escalating Player Expectations: Lee Horn offered a stark warning: "Do not go up against an incumbent that has been around a long time," especially in competitive PvP genres that boast "years of credibility with high-quality matchmaking and great anti-cheat." He emphasized that in the current market, "a small innovation is not enough." David Duong added that established titles like Fortnite and Call of Duty present an "onslaught of content," compelling other games to "meet players where they need us to be so they don't go to other games." The barrier to entry and, more importantly, to sustained success in established genres, particularly player-versus-player experiences, is now extraordinarily high. Players have come to expect a baseline of polish, content depth, and technical stability that new entrants must not only meet but often exceed almost immediately upon launch. This market dynamic tends to favor either highly differentiated new IPs that carve out unique niches, games that can generate entirely new market segments, or titles that benefit from significant pre-existing IP leverage. Incremental improvements within already crowded spaces are proving increasingly insufficient to gain traction, demanding that PMs conduct brutally honest and rigorous market assessments before committing to new projects.

AI in the Trenches: Separating Hype from Reality

Artificial Intelligence was a central theme, with panelists keen to move beyond speculative discussions to its real-world impact on game development.

• AI: Transformative, Not Transitory: Tim Hong of AWS asserted that AI "is now a significant development, not a fad." Oren Debi from SciPlay concurred, noting that while truly transformative, game-changing uses of AI are not yet fully realized, its "adoption is mainly around efficiency" in current workflows. This consensus establishes AI as a fundamental technological shift that demands strategic attention from industry leaders, signaling that investment in AI capabilities is evolving from an optional experiment to a strategic imperative.

• Current Practical Wins with AI: The panel highlighted several areas where AI is already delivering tangible efficiency gains:

  • Art Creation: Oren Debi reported "about a 40% increase using AI tools to create collectibles and other features."

  • Code Assistance: "Code Assistant is also greatly used," according to Debi.

  • PM Productivity: Large Language Models (LLMs) are being employed by PMs for "competitive intelligence, PRDs, and wireframes—all the heavy stuff that takes a long time."

  • QA Testing: Although discussed more in the after-panel, its relevance to current utility was clear, with AI advancing QA "beyond simple automation to contextual automation."

    These concrete examples demonstrate that AI is not just a future promise but a present-day tool capable of delivering immediate ROI in specific departments. For PMs, this means an opportunity to explore these tools to automate or accelerate tasks, thereby freeing up valuable time for more strategic, high-impact work. The pattern emerging from these current applications is that AI is largely augmenting human capabilities and streamlining repetitive or time-intensive tasks, rather than outright replacing roles.

• The "Amplify, Not Replace" Consensus (for now): A key sentiment from the panel was that AI's current role is one of augmentation. David Duong stated, "I think AI is here to amplify, not replace." Oren Debi delivered a more pointed message: "The only people who will be replaced are those who don't adopt AI. PMs who adopt AI will eventually replace PMs who don't." This offers both reassurance and caution: AI tools are rapidly becoming essential, and proficiency in leveraging them will be a significant differentiator. The immediate concern isn't AI taking jobs but rather PMs who effectively integrate AI into their workflows, outperforming and potentially displacing those who do not. However, this "amplify, not replace" stage might be transitional. As AI capabilities continue to advance rapidly, particularly towards more sophisticated forms of narrow AI or even nascent Artificial General Intelligence, the distinction between amplification and replacement may become increasingly blurred. This is especially true for tasks currently considered core components of certain roles.

The Evolving Product Manager: Bridging Worlds and Skills

The discussion extensively covered how the product manager role itself is transforming in response to these industry and technological pressures.

• The Great Divide: Mobile Agility vs. PC/Console Tradition: Solomon Lichter, self-described as a "mobile guy," highlighted that mobile PMs are "very sought after due to their skill set, their ability to act on data, and their general working style." He traced mobile's DNA back to tech giants like Facebook and Zynga, fostering a culture of "move fast and break things." Conversely, Lee Horn pointed out that the PC and console space has a "long history of succeeding without product managers or data insights," which has cultivated a degree of "internal resistance" to their integration. This illuminates a significant cultural friction point within the broader games industry. As games across all platforms increasingly adopt LiveOps models and data-driven decision-making, the agile, iterative mindset characteristic of mobile PMs becomes more valuable. Yet, traditional AAA organizational structures often struggle to integrate these PMs and their methodologies effectively. This resistance within PC and console environments to data-informed PM practices can result in slower adaptation to market changes, missed optimization opportunities, and overall inefficiency, particularly as market pressures intensify the demand for greater agility. The "education process" Lee Horn mentioned is therefore not just a minor adjustment but a critical undertaking for the future competitiveness of many AAA studios.

• Hiring for the AAA Future: Fundamentals, Empathy, Communication: When discussing hiring PMs for the AAA space, David Duong emphasized the importance of "sound fundamentals," asserting that if a PM possesses a strong foundational skillset, "they can solve and do anything." Beyond core competencies, he stressed the critical need for "strong empathy, especially with designers," who, as he noted, "don't always respond well to data." This necessitates an ability to "read the room, understand what they care about, and think on your feet to reposition your message to connect with them and get things done." In the complex, multi-stakeholder environments typical of AAA development, raw technical or analytical skills are insufficient. PMs must possess robust foundational problem-solving capabilities, coupled with high emotional intelligence, to effectively navigate internal team dynamics and drive alignment. This is particularly crucial when introducing data-driven approaches into cultures traditionally led by design intuition. The emphasis on "empathy" and the skill of "repositioning messages" suggests that a core competency for PMs in the AAA sector is internal diplomacy and effective change management, especially when data-driven findings challenge established "tribal knowledge" or long-held artistic intuition, a point Solomon Lichter also touched upon when describing console organizations.

• AI's Shadow: Team Compression and the Rise of the "PM+1" As an "AI maximalist," (sort of), I offered a somewhat contrarian perspective on the impact of AI. I discussed how AI will "fundamentally subsume a lot of work from different roles," which will inevitably lead to a compression of traditional roles and the emergence of hybrid positions such as a "product engineer (PM + engineer) or a product marketer (PM + UA marketer)." To encapsulate the necessary evolution for product managers in this AI-suffused future, I sated how I believe the role of PM should be "PM+1": a product manager who not only masters the core PM skillset but also possesses "extreme depth in another area," be it engineering, marketing, design, or data science. This vision suggests that generalist PMs, whose value is tied to tasks that AI can increasingly automate, may find their distinctiveness diminishing. Specialization or profound expertise in a complementary field will likely become crucial for differentiation and sustained value. This outlook directly challenges conventional organizational structures built upon clearly demarcated, siloed roles. Companies that can successfully cultivate, hire, or retrain for these hybrid "PM+1" talents, and that can foster flexible "organizational metas" will be better positioned for adaptability and competitive advantage in the evolving landscape. If AI handles many current PM tasks, humans must bring skills that AI either cannot replicate or can uniquely leverage, leading to this more specialized, deeply skilled PM profile.

Key Panelist Takeaways: Your Evolution of PM Cheat Sheet

The panelists each offered a concise, potent piece of advice for navigating the changes ahead. These takeaways provide a clear roadmap for product managers and executives alike.

Part 2: The After-Panel Huddle – Deeper Reflections & Future-Proofing

Recently, Tim Hong, Solomon Lichter, and I reconvened for a debrief, delving deeper into some of the themes and sharing further reflections on the rapidly evolving landscape.

Beyond the Stage: Unpacking Surprises and Lingering Questions

The follow-up conversation revealed a palpable sense of both excitement and uncertainty pervading the industry.

• Industry's Thirst for Tactical AI Knowledge: Solomon Lichter observed a "huge hunger for more insights—tactical, real-world, and strategic" concerning AI, evidenced by "many follow-up requests to drill into specific areas or set up calls" after the panel. Tim Hong expressed that he was "positively surprised by how folks are thinking about AI and its possibilities," noting a clear progression in the industry "from idea to true POCs [Proofs of Concept], and possibly even into production this year." This indicates that the game development sector is moving beyond general discussions about AI's potential and is now actively seeking practical implementation strategies, best practices, and collaborative avenues to harness its power. The expressed interest in "collaboration" and clients wanting to build "councils" suggests a recognition among studios of the inherent complexity of AI implementation. Rather than attempting to develop all necessary AI capabilities in-house, many are looking towards partnerships and shared learning ecosystems, potentially opening significant opportunities for specialized AI service providers and consultants.

• Embracing Uncertainty in a Sea of Change: One observation I noted is about "the level of uncertainty and the embrace of change I'm seeing among leaders in the gaming industry." Many executives I talk to are "unsure what these environmental changes mean for them and how to prepare for a world with so many concurrent developments," especially with the significant looming impact of AI. From what I’m hearing, even seasoned industry leaders are grappling with the sheer pace and confluence of transformative forces—the lingering effects of the COVID boom, shifts in the attention economy, and the pervasive rise of AI. In such an environment, characterized by high uncertainty, the value of robust frameworks for decision-making, opportunities for shared learning (such as industry panels and discussions), and the adoption of agile, adaptive processes increases dramatically. Static, long-term strategic plans become inherently less reliable, necessitating a more flexible and responsive approach to leadership and planning.

AI: From Feature to Foundational Orchestration

The after-panel discussion further refined the understanding of AI's evolving role, positioning it not merely as a set of features but as a fundamental orchestration layer.

• The PM's Evolving Value Proposition with AI: Tim Hong posited that as basic knowledge acquisition becomes "somewhat commoditized by AI"—for instance, quickly getting context on an unfamiliar term—product managers will "need something else to hang your hat on, whether it's being design-focused or analytics-focused." The critical question becomes, "What will get you into the room to speak to issues and offer opinions?" If AI tools can efficiently handle foundational research and data queries, the onus falls on PMs to elevate their contributions toward more strategic thinking, specialized expertise, and the uniquely human elements of judgment, creativity, and experience informed by data. This directly implies that PMs whose primary value lies in tasks easily automated by AI must actively develop deeper, less automatable skills to maintain their relevance and impact.

• Offensive & Defensive AI: Automation Meets New Capabilities: PMs should consider how AI can automate existing work (a defensive posture, focused on efficiency) and, crucially, how it enables entirely new capabilities such as advanced personalization, dynamic offers, and sophisticated CRM (an offensive posture, focused on value creation). This offensive application of AI can empower "smaller teams... to compete with larger ones" by leveraging these new, powerful capabilities. This framing is vital because it positions AI not just as a means to cut costs or accelerate existing processes, but as a catalyst for unlocking entirely new avenues for player engagement and value generation, potentially re-leveling the competitive playing field.

• The PM as Orchestrator and Tastemaker: In the world we are moving towards with AI, a significant mindset shift is required towards leveraging AI less as a discrete feature layer and more as an "orchestration layer." In this paradigm, the PM is envisioned "at the controls of a command center orchestrating everything." Significant PM value may come as a "tastemaker for capabilities and tools," responsible for deciding "which specific actions to take to optimize the game" from the myriad possibilities AI enables. This perspective elevates the product manager's role from that of a feature owner or backlog manager to a strategic integrator and optimizer of complex, AI-driven systems. Such a role demands a broad understanding of AI's potential across various domains, coupled with the acuity to direct its application in the most effective and impactful manner. If PMs are to become orchestrators of diverse AI tools and agents, their core competencies must evolve to include strong systems thinking, the ability to strategically prioritize AI initiatives based on potential impact, and a keen understanding of the ethical considerations and player experience implications of AI-driven decisions. A high-level technical understanding of AI also becomes increasingly important in this context.

• Gartner's "3 Returns" Framework: Strategic AI Investment: Tim Hong introduced a valuable framework from Mary Maseglio, a VP at Gartner, designed to help leaders understand and categorize AI business outcomes. The "Three AI Business Outcomes Every Leader Must Understand" are: "return on employee" (focusing on enhancing employee efficiency and productivity), "return on investment" (aiming to directly improve the bottom line or key performance indicators), and "return on future" (involving the creation of entirely new capabilities and business models). This framework provides a structured approach for executives and product managers to categorize, justify, and measure their AI initiatives. It allows organizations to move beyond vague notions of "investing in AI" towards specific, outcome-oriented projects with clear objectives and metrics. For instance, Tim Hong described a project to leverage AI to create a comprehensive knowledge base capturing all past initiatives a studio has tried on a game. Such a project clearly falls under "return on employee," with its value measured in efficiency gains, reduced redundancy, and accelerated onboarding, rather than direct, immediate revenue impact.

• "Product Velocity" as a North Star Metric: A key metric that will become increasingly important is "product velocity." This may become "the most important metric for all PMs," particularly within the mobile and live ops spheres. In a market characterized by rapid evolution and intense competition, the speed at which teams can iterate, learn from those iterations, and deploy valuable changes to players becomes a critical competitive differentiator. Artificial Intelligence is seen as a major enabler of this necessary increase in velocity. Further, AI turns product velocity into a bigger point of differentiation between those who leverage AI for velocity and those who don’t. Further, the focus on product velocity directly addresses the competitive pressures previously discussed, such as the high content output from global competitors and the imperative to meet rapidly changing player expectations. If the market and competitors are moving fast, and AI can accelerate internal processes, then measuring and optimizing for product velocity becomes a crucial mechanism for effectively leveraging AI and maintaining a competitive edge.

Agentic AI: The Next Frontier in Live Ops and Beyond

The conversation then ventured into the more advanced concept of agentic AI, painting a picture of a future where AI plays an even more autonomous and proactive role in game operations.

• Understanding Agentic AI: AI That Learns and Evolves: Tim Hong provided a simple yet effective explanation of agentic AI: "If you let this 'person' keep playing the game, after a while, they're going to get better at it." This distinguishes agentic AI from more static AI models, implying systems that can autonomously learn from their environment and interactions, adapt their strategies, and optimize their performance over time. Solomon Lichter underscored the potential impact of this technology, viewing agents as an "existential shift" that will eventually "completely consume automation" as we currently understand it, particularly in marketing automation and, by extension, LiveOps. This represents a significant step beyond current AI applications, envisioning AI systems that operate with a greater degree of autonomy within defined parameters, which has profound implications for how games are managed, personalized, and monetized.

• Practical Applications: A Glimpse of Functional Agents: The discussion explored several potential applications of these functional, learning AI agents within game development and live operations:

  • Segmentation Agent: An agent "whose only job is to look at how to segment players," continuously refining segmentation based on evolving data. (Tim Hong)

  • Non-Spender Health Agent: A particularly insightful concept was an agent dedicated not to aggressive conversion, but to "observe the health of non-spenders... to figure out if we're engaging our player base in the most positive, healthy way." (Tim Hong) This highlights a shift towards using AI for holistic player experience management.

  • In-Game Economy Management: Agents could be tasked with "actively managing the in-game economy in real time," responding to shifts in currency availability, player pools, and spending habits to maintain balance and health. (Solomon Lichter)

  • Offer Tuning & Personalization: Agents could dynamically tune offers, enabling "true one-to-one personalization" at a scale unachievable through manual methods. (Solomon Lichter)

  • Dynamic Content/Asset Tagging: AI could dynamically tag in-game content and assets, a typically manual and laborious process, leading to significant efficiency gains. (Solomon Lichter)

  • These examples illustrate how specialized AI agents could potentially take over complex, dynamic LiveOps tasks that currently demand considerable human oversight and intervention. This could lead to more deeply personalized, responsive, and optimized player experiences delivered at an unprecedented scale. The emergence of such functional agents would necessitate a shift in the product manager's focus: from the direct execution of these LiveOps tasks to defining the goals, constraints, and ethical guidelines for these AI agents, and then diligently monitoring their performance and overall impact. The PM effectively becomes a "manager of AI agents."

• The Unshakeable Foundation: A Rock-Solid Data Strategy: A critical prerequisite for realizing the potential of advanced AI, especially agentic systems that learn and adapt based on data, is an impeccable data strategy. Tim Hong stated unequivocally, "If your data strategy is not solid, it's really hard to create a training model on that." This cannot be overstated. The efficacy of these sophisticated AI systems is entirely dependent on the quality, comprehensiveness, and accessibility of the data they are trained on and operate with. "Getting your data house in order," as Tim put it, is a non-negotiable foundational step before embarking on ambitious agentic AI initiatives. A deficient data strategy will inevitably lead to poorly trained AI models, resulting in ineffective or even detrimental AI agents, ultimately undermining the entire AI initiative.

The Culture Clash Revisited: Adaptability as the Ultimate Competitive Edge

The after-panel discussion returned to the persistent challenge of cultural integration and the overarching importance of organizational adaptability.

• The Persistent Struggle: Integrating Mobile DNA into Traditional Studios: Solomon Lichter reaffirmed the "cultural and organizational dichotomy" between the agile, data-centric world of mobile game development and the more traditional structures of many PC/console studios. He observed that while console companies actively want to hire mobile PM talent, recognizing the value of their skills, these organizations are often "not set up organizationally, culturally, or politically to do so." This frequently leads to a "retention issue," as mobile-native PMs become frustrated by slower paces and resistance to rapid, data-informed iteration. This is not merely a recruitment challenge; it points to a need for fundamental organizational change. Studios that cannot evolve their internal cultures to genuinely embrace and empower agile, data-driven, and velocity-focused methodologies will find it increasingly difficult to attract, retain, and effectively leverage top product talent, ultimately hindering their ability to keep pace with market demands.

• Failure to Adapt = Losing the Velocity War: "If you dig in, remain narrowly focused, and stick to 'this is how we did it before,' you'll struggle." Solomon Lichter connected this directly to the AI discussion, noting that if organizations are already finding it challenging to implement current LiveOps best practices, it will be "even harder for them to adapt to a new reality where human intervention... will be increasingly mitigated" by AI. The accelerating pace of change, significantly amplified by AI's disruptive potential, means that cultural inertia and resistance to new ways of working are greater liabilities than ever before. The ability to adapt quickly—encapsulated in the term "product velocity"—is rapidly becoming a primary determinant of competitive success. The "adapt or die" message is not mere hyperbole in this context. The potent combination of ongoing market shifts and AI's transformative capabilities will inevitably create clearer distinctions between winners and losers, largely based on their respective organizational adaptability and willingness to evolve. Traditional studios that fail to address these cultural and organizational impediments will find themselves increasingly outmaneuvered in an AI-driven future that prizes speed and data-driven agility.

Conclusion: Your Roadmap for the Future of Game Product Management

All of these discussions highlight the game development landscape is undergoing a seismic transformation. While the role of the product manager is arguably more critical than ever in navigating this complexity, its fundamental nature is changing. It's becoming less about the execution of specific, narrowly defined tasks and more about strategic orchestration, the cultivation of deep specialized knowledge, and the championing of organizational adaptability.

A final practical trinity of advice for thriving in this new era:

• Get Hands-On & Be Curious: Tim Hong urged PMs to actively engage with new technologies, emphasizing that "The barrier to entry... is extremely low... Go take a ride, take a spin, experiment." In a world where tools and platforms are rapidly evolving, particularly in the AI space, practical, hands-on experimentation is invaluable for building intuition, understanding capabilities and limitations, and identifying opportunities.

• Build in Public & Learn Out Loud: Solomon Lichter advocated for a shift away from secretive development cultures, advising PMs to "Share your experiments, failures, and thinking openly," because "The future likely belongs to PMs who learn out loud." In the face of complex, rapidly advancing technologies like AI, collaboration and shared learning will accelerate both individual growth and industry-wide progress. Openness can foster a collective intelligence that benefits all.

• Embrace Continuous, Urgent Learning: "The impact of AI will be the most significant not only in our lifetime but possibly in all of human history. Now is not the time to relax... learn as much as possible and push yourselves now." In these coming years, there may be a "power-law distribution of value" and wealth. Hence, in this new landscape, being slightly ahead of the curve could yield disproportionately large rewards.

The future of game product management is undoubtedly challenging, demanding new skills, new mindsets, and a new level of adaptability. However, it is also a future brimming with opportunity for those who are willing to embrace change, commit to continuous learning, and lead with strategic foresight. Hopefully, our discussions offer a valuable compass for navigating the exciting and transformative journey ahead.

Good luck!

Most game studios repeatedly make the same critical mistake—endless iteration on trivial design details while crucial systems remain broken. This cycle doesn't just waste resources—it kills games.

The Problem: Constant Churn in Game Design

"I'm fucking quitting. This is bullshit."

It was around 2015, and I had recently taken charge of a distressed game project.

"He changed it again. This is the fifth time PVE was redesigned, and he never even looked at the build."

Our lead client engineer was ready to leave, and morale was collapsing. It took weeks of careful reassurance to keep him onboard, at least until the project's completion. Fortunately, that game—King of Avalon—went on to achieve tremendous success.

Fast forward to a few years ago at my current game studio:

"They've changed heals and shields seven times already."

"What about the core loop? Why aren't they addressing that?" I asked.

More recently, it happened again:

• "Engineers want to change how squads work immediately."

• "We need to adjust how free loadouts function."

• "Here's the new Realm and House idea; it has to be implemented now."

I carry emotional scars from a lack of design discipline. Constant churn wastes valuable time, causes delays, and endangers critical features, trapping teams in a cycle of non-essential revisions.

Understanding the Root Cause

The disease that is killing game projects is a predictable yet preventable one: teams iterating endlessly on non-critical features, ignoring fundamental issues. The root of this disease is not a lack of talent or effort—it’s a lack of discipline.

Design discipline isn't rigid or uncreative; it's professional maturity. It means focusing relentlessly on critical tasks, even when they're difficult or intimidating.

Common symptoms include:

• Repeated feature redesign without clear objectives

• Ignoring broken core systems to polish minor details

• Chasing exciting ideas rather than solving fundamental problems

• Wasting time and resources without meaningful progress

• Always trying to copy some new feature from a new game by a reputable developer

This cycle is essentially a premature ejaculation of creative energy.

The Three Pillars of Effective Design Discipline

After observing numerous project successes and failures, I’ve identified three critical pillars:

1. Priority-Driven Development

Effective design starts with ruthless prioritization:

• High-Risk First: Always prioritize addressing the biggest risks first. If your core gameplay loop is broken, everything else is irrelevant.

• Resource Realities: Teams have finite time and budgets. Ignoring this truth dooms projects.

• Pain Avoidance: People naturally avoid difficult tasks. High-risk design problems must be tackled immediately, not postponed.

Designers who repeatedly sidestep challenging problems aren’t designing—they’re procrastinating.

Example: Your team proposes an exciting new weapon progression system, but your core combat loop remains uninteresting. Prioritize anything in the core loop, no matter how enticing shiny new features appear.

2. Critical Thinking Over Gut Feelings

Replace emotional decisions with structured thinking:

• Clear Objectives: Understand precisely why each feature exists and the specific problems it solves.

• Structured Analysis: Use formal decision-making frameworks rather than gut feelings.

• Evidence-Based Changes: If proposing yet another redesign, demonstrate its necessity with data or thorough analysis.

Without critical thinking, design becomes a never-ending loop of "Wouldn't it be cool if…" instead of "What do we need to ship?"

3. Professional vs. Amateur Mindset

Recognize the difference between amateur and professional game development:

• The Indie Trap: Indies often have endless freedom—no deadlines, budgets, or obligations—and thus can iterate forever. Amateurs fall into this mindset, risking never shipping.

• The Professional Reality: Even legendary games like God of War shipped with compromised features because professionals understand that shipping a good game is far better than endlessly chasing perfection.

Good designers prioritize effectively and accept imperfections to ship faster. They understand perfection as the enemy of completion.

Additionally, I've found that initial designs followed by a deliberate pause, allowing other aspects of the game to be resolved, often lead to more effective and insightful redesigns. This approach contrasts sharply with continuously redesigning the same feature repeatedly without meaningful reflection.

Hence, an initial design with a redesign towards the end is preferable to 5-10 constant redesigns..

Practical Steps for Implementing Discipline

Stop the Churn:

• Objective Clarity: Define measurable objectives for each proposed change.

• Data-Driven Decisions: Provide clear evidence why the current version is insufficient.

• Cost-Benefit Analysis: Clearly estimate time and resources against anticipated benefits.

• Priority Alignment: Compare proposed changes strictly against your established priorities.

Document Key Decisions:

• Maintain a list of deferred improvements.

• Clearly document rationale behind major decisions.

• Track system changes and iterations.

Hold the Line: You’ll frequently face:

• Enthusiastic teammates pushing "game-changing" ideas.

• Designers perpetually "almost there" on revisions.

• PMs adding "just one more feature."

Be the adult in the room—say no firmly yet calmly, redirecting enthusiasm toward genuine priorities.

Consequences of a Lack of Discipline

When discipline fails, consequences are severe:

• Morale Burnout: Developers quickly burn out from constant, meaningless changes.

• Resource Waste: Every needless iteration steals critical resources from essential features.

• Quality Degradation: Poor foundations inevitably require costly rewrites.

• Project Failure: Without discipline, many games simply never ship.

Key Takeaways

• Always prioritize the biggest risks first.

• Demand evidence, not emotions, for repeated design iterations.

• Embrace imperfection; professional developers ship, they don't endlessly perfect.

The Path Forward

Design discipline channels creative energy effectively. Mature teams recognize constraints as creativity enhancers, deadlines as decision-makers, and shipping a good game as infinitely superior to dreaming about a perfect one.

The next time your team wants to reprioritize or revisit a feature unnecessarily, ask yourself:

• Is this addressing our highest-priority risk?

• Do we have data or a structured analysis to justify this change?

• Are we avoiding something more important but harder?

If any answer is "no," note the idea, put it aside, and refocus your team’s energy where it matters.

Players can't play your perfect ideas—they can only play the games you actually ship.

The psychology behind our worst strategic decisions—and how to escape it

Would you rather have a 10% chance of success or a 99% chance of failure?

I've probably asked employees, cofounders, and investors this question at least 30 times in the past few years.

The answer seems obvious. But here's what's fascinating: when faced with this choice in real situations, almost everyone chooses the 99% path to failure.

Here's why: Most people focus on the immediate pain of change rather than the ultimate cost of not changing. They would rather accept a 99% chance of failure than face what it would take to pursue a 10% chance of success.

This is the failure trap, and it's everywhere.

Fear Locks Us Into Certain Failure

Almost everyone gets locked up by fear, held hostage by the terror of deviating from a path almost certainly headed toward failure.

The examples are everywhere: not giving direct feedback to an underperforming "key contributor," allowing toxic culture fits to poison the team, keeping friendly employees who try hard but can't deliver, delaying a difficult design or engineering decision, or continuing a project with no chance of success. There's agreement that a significant problem exists, but zero action because of fear of change.

"Let's cross our fingers and hope for the best" is not a strategy. It's surrender.

Many leaders apply stable company thinking to unstable business situations, which leads to catastrophically bad decision-making. When you're building something new, the rules are different. Safe choices become deadly choices.

The Ghost of Christmas Future

I broke free from this failure trap years ago when I learned to force myself to see the real consequences of staying on my current path.

Think about Scrooge in A Christmas Carol. The Ghost of Christmas Future shows him exactly where his current behavior leads—dying alone and unmourned. That glimpse of his actual future creates such emotional intensity that he immediately changes everything.

Most of us never look at our Ghost of Christmas Future. We focus on the immediate discomfort of change while ignoring the devastating long-term cost of not changing.

The exercise is simple but brutal: Where does your current path actually lead? What do you lose if you keep doing exactly what you're doing? What opportunities disappear forever?

When you force yourself to see the real endpoint of the 99% failure path, the 10% success path suddenly becomes less scary.

When Champions Play Not to Lose

This psychology isn't unique to business. You see it everywhere, including in professional football.

Take the prevent defense—used when teams are ahead late in games. The philosophy is "don't give up the big play" rather than "keep dominating." It often backfires.

Why? Because a prevent defense concedes easy yards to avoid low-probability explosive plays. But those easy yards add up. Teams pile up first downs, score methodically, and can flip momentum.

The data on fourth-down decisions tells the same story. UC Berkeley economist David Romer proved back in 2002 that teams should go for it on fourth down far more often than they do. The math is clear: going for it increases your chance of winning.

Yet most coaches still punt. They choose the "safe" option that actually makes them more likely to lose.

The rare coaches who embrace the data—like Kevin Kelley, who never punted in high school—dominate their competition. But most would rather lose conventionally than win unconventionally.

Sound familiar?

In business, we make the same trade-offs. We choose strategies that feel safe but mathematically decrease our odds of success. We punt when we should go for it. We play prevent defense when we should stay aggressive.

The Real Enemy: Comfortable Misery

The deepest truth about the failure trap is this: we often prefer comfortable misery to uncertain change.

A struggling startup founder knows their current strategy isn't working, but at least they know what to expect each day. A game studio keeps an underperforming team member because finding and training a replacement feels overwhelming. A company continues pouring money into a doomed project because the sunk cost feels too large to abandon.

We choose familiar problems over unfamiliar solutions.

This is why the 10% vs 99% question cuts so deep. It reveals that our brains are wired to avoid change and perceived risk, even when change dramatically improves our odds of success.

Breaking Free: Questions That Cut Through Fear

When you suspect you're on the 99% failure path, ask yourself:

1. What would I tell my best friend to do in this exact situation? (Removes your personal fear and status quo bias from the equation)

2. What would I do if this were a game and I was playing to win, not playing not to lose? (Connects to your competitive instincts rather than your protective ones)

3. What will I regret more in 5 years: trying this risky thing and failing or never trying at all? (Forces you to see your actual Ghost of Christmas Future)

The pattern I see in successful teams: they recognize the failure trap early and have systems to escape it. They build cultures where difficult truths can be spoken. They regularly audit their strategic assumptions. They're willing to course-correct before it becomes life-or-death.

The Bottom Line

Every day you stay on the path to 99% failure, that path becomes harder to leave. The sunk costs grow. The narrative solidifies. The fear compounds.

But here's what I've learned from getting punched in the face repeatedly: the regret of not trying is always worse than the regret of trying and failing.

The next time you face a choice between comfortable failure and uncomfortable possibility, remember your Ghost of Christmas Future. That's where your current path actually leads.

Choose the 10%.

Sometimes, we don't even know what game we're playing.

We work, turn the crank, and hope for the best.

In today's ultra-competitive and challenging marketplace, effort isn't enough. Even teams with exceptional talent and endless determination can find themselves heading towards failure.

Even if we give maximum effort, how do we know we're moving in the right direction?

Whether you realize it or not, you are playing a game. The work you do and the strategy you knowingly or unknowingly follow will dictate your odds of success. The question isn't whether you're in a game—it's whether you understand the game you're playing.

The All-In Mindset

My philosophy is that if you play, you play to win. You don’t play by half measure.

-Elon Musk

Whatever your personal opinions about Elon Musk, his track record as an entrepreneur speaks for itself. His approach to problem-solving offers valuable insights for game development teams seeking to maximize their potential for success.

Playing to win means doing two critical things:

1. Understanding what it takes to win

2. Committing fully to that understanding

Consider how Musk approached the 2024 U.S. Presidential election. After analyzing the electoral landscape, he identified Pennsylvania as the "linchpin" state that would likely determine the outcome. Once this single point of greatest leverage was identified, he didn't hesitate—he relocated to Pennsylvania, established a campaign war room, invested over $100 million, and remained until he helped secure the state.

This laser focus on the highest-leverage opportunity demonstrates a key principle: when you identify what matters most, go all in.

X + X.ai

More recently, Elon started X.ai, an AI company very late to the AI chat game, trying to compete against OpenAI, Google, Meta, and other major competitors.

How do you compete against massively resourced and capable competitors in one of the most challenging arenas to win?

First, Elon identified the game he was playing with LLMs: the AI scale game. Essentially, the way to drive LLMs is quite simple just based on 3 primary drivers:

• Compute

• Parameters

• Data

Elon proceeded to raise over $12B to compete for scale to build the biggest AI supercomputer (compute). Further, they went all in on execution because he knew time was critical.

Even more recently, x.AI announced another $20B raise and acquired the X/Twitter platform.

Why?

In an interview with Stratechery, Sam Altman (OpenAI’s CEO) suggested the future bases of competition would shift to distribution:

Elon is playing to win again, forcefully acquiring and driving the inputs for the LLM-scale game and securing distribution and exclusive access to X data from the X acquisition.

Playing to Win

If you were to ask your company’s leadership or team members, “How do we win?” would they know the answer? Would they all answer in the same way?

1. Identify The Game

If you want to win, you’ll need to know how. Hence, you have got to understand the rules of the game.

• Market reality: What competitive landscape are we entering?

• Player needs: What desires or problems are we addressing? Why are players playing your game vs. competitive alternatives?

• Success metrics: How will we measure whether we've won?

Many studios never explicitly define these parameters. They create games based on team capabilities, personal passions, or market trends without truly understanding the strategic context. This is equivalent to stepping onto a field without knowing which sport you're playing.

2. Understand Points of Operational Leverage

Every game has specific bases of competition that critically determine success.

Further, all actions are not created equal. In every project, certain decisions and activities will have a disproportionate impact on your success potential:

• Is your game's unique core gameplay loop the make-or-break factor?

• What specific player experience will players play your game for and not others?

• Will your marketing and user acquisition strategy determine success?

• Does technical innovation set you apart?

Identifying the bases of competition and critical leverage points allows you to concentrate resources where they matter most.

3. Go All In

Half-measures rarely produce extraordinary results. Once you've identified your game and your leverage points, successful teams commit with unwavering focus:

• Full alignment: Ensure everyone is fully aligned with how to win and that the strategy is fully communicated (a single email or Slack message isn’t enough!)

• Resource allocation: Direct the majority of your budget and talent toward your highest-leverage activities

• Decision velocity: Eliminate competing priorities that dilute focus

• Strategic persistence: Maintain commitment through inevitable setbacks

• Do it!: Fully commit and execute the required actions for your strategy - there is a huge difference between talking and doing

Today’s gaming landscape is littered with many dead bodies.

Are you ok with being the next dead body?

The only way to not look back with regret is if you give it your all and go All In.

Maximizing Chances for Success

What game are you playing?

How are you playing the game?

In today’s market, those who play to win don't just work harder—they work smarter by understanding exactly which game they're playing and what it takes to win.

Speed has long been considered one of the most important characteristics of successful startups and new game development projects.

Every investor and executive will tell you that speed is everything. However, I believe the general view of the importance of “speed” lacks specific nuance in two critical ways.

1. Product Velocity

Velocity is a vector with both magnitude (speed) and direction. This distinction is crucial in product development. Speed, while critical, isn’t enough. Teams must move fast and in the right direction.

In a gaming context, product velocity can be thought of as needing to get both the micro (speed/execution) and macro (direction) right.

Micro associates with the quality of the team leads (CEO, tech lead, creative director, etc.) and the team itself, the specific work processes and practices, the workflows, and the attitude and culture of the team.

Macro can be simplified to mean a team’s product strategy. This includes aligning against key environmental factors and trends, differentiation in the market, and how well a product delivers against critical bases of competition.

To make the macro a bit more specific for game development, it would include things like the kind of game to make, the development approach or philosophy, the operational and team model (hybrid, remote, in-office), geographic strategy, recruiting and hiring strategy, and other such things.

2. Characterizing Your Product Iteration Cycle

How do you improve speed?

Too often, we may adopt the simplistic view that speed improves only through hard work and effort. While the impact of hard work on speed may be true, the nuance here is that effort isn’t enough.

Speed critically depends on the design of a workflow. Hence, teams should also consider improving and optimizing their workflows to improve speed.

Two important steps to improve workflow:

1. Characterize and evaluate your product iteration cycle

2. Carefully analyze and deeply think about how to improve

1. Characterize & Evaluate

Map your iteration cycle. Characterize and break down each step. Find the bottlenecks. Fix them.

Think of it as a machine whose inputs, outputs, and process steps can be analyzed and improved.

A simple view of a typical product iteration cycle may look like the following:

2. Analyze & Deep Think

Too many teams keep “turning the crank” without carefully evaluating and analyzing how they work.

Teams need to consider more carefully:

• Where are we getting stuck?

• What can we do better?

• *Who* are we getting blocked on? Can someone else do better?

• Think from first principles: How would we design our work if we were to zero base the workflow?

• What is the root cause of process steps that take a long time?

Who vs. What

When analyzing and deep thinking about the workflow, teams should also remember to consider not only the what but also the who. Often, the problem may not be the process or practice but the specific person doing the work. Many times, calling out a person is politically problematic. However, to fix a problem, you will need to actually fix the problem.

This means you may need to replace someone to improve speed, regardless of how emotionally or politically difficult it may be.

Reducing Iteration

Product development generally requires many rounds of iteration to achieve product-market fit.

Hence, reducing the number of product iteration cycles is also a major contributor to speeding up. Teams should, therefore, carefully consider how product design changes are being made and how the quality of iteration decisions can improve.

Pivots May Be Necessary

One final note on iteration: During analysis and deep thinking, a team may conclude that the product direction is wrong. There should be some time to carefully consider the direction on a regular basis.

In short, re-evaluating direction should be part of the iteration cycle. Through iteration, a team may discover a new, much better global maxima of opportunity relative to a local maxima they are currently pursuing.

Improving Product Velocity Cheat Sheet

1. Characterize and Identify Your Bottlenecks

• Which process step causes the most delay?

• Where does work pile up? Which handoffs cause delays? Where, VERY specifically?

• What decisions are being made incorrectly, with too many stakeholders, or a bad process?

2. Measure Your Cycle Time

• Track time from iteration start to live deployment

• Break down time spent in each phase

• Identify which types of changes move fastest

3. Optimize Systematically

• Remove blockers or unnecessary steps or approvals

• Parallelize where possible

• Remove or change the people that cause delays

4. Analyze Carefully and Think Deeply

• Deploy root cause analysis and decision analysis to help determine problems & solutions

• Be brutally honest on required changes

• Thought experiment: If your mom’s life depended on you getting this right, what would you do?

Real World Context

Recently, many game studios have unsuccessfully tried making extraction shooter games. Some of the world’s most skilled game studios, like the Tencent Timi and Netease teams, have tried many times and failed here.

There are many, many dead bodies in extraction.

Our studio started before them, but we’ve been stuck in development hell for over four years. Our execution was so bad that we were too slow to fail fast. We’re still here, while most others have already started, launched, failed, and given up.

In short, we have sucked at speed. We’ve been slowly improving, but not quite there yet. To be clear, I believe speed is critically important for success, and we’re working on it.

My insights on this topic are drawn from getting punched in the face over and over again.

However, if we succeed, it will be due to our direction, which differentiates more strongly than previous attempts. We're still working on our speed, but at least now we know where to look. Our story is still being written.

These words from one of our investors last year highlighted what was obvious: we were in trouble. Our game studio struggled with delays and direction changes from the start, and we were way off track.

Many problems plagued us, but the biggest problem was our lack of teamwork and operational efficiency against our product objectives.

And while we've made strides since then, we're still not entirely out of the woods.

Sound familiar?

You know how common this story is if you've worked in game development. The industry is notorious for its high failure rate, with some estimates suggesting that over 90% of new game projects fail.

But what if there was a framework that could help teams avoid these pitfalls and dramatically improve their chances of success?

Enter AACT: Alignment, Accountability, Communication, and Tracking Performance.

The AACT Framework

After much soul-searching, internal team discussions, and consultation with experienced industry veterans, I've identified the four foundational areas above that are key to reducing iteration, accelerating progress, and improving outcomes.

Addressing these areas will help our team work better together and with greater operational efficiency.

1. Alignment

Alignment is crucial but often fuzzy and difficult to characterize, like "company culture."

Alignment means that everyone on the team is moving in the same direction. Energy and resources are aligned towards a common goal instead of varied goals or even goals that are at odds with different team members.

Misalignment manifests in delayed milestones, lack of follow-through on decisions, and perpetual disconnects between intent and action.

Specific examples of these symptoms can look like:

• The agreement to focus on building towards a playable core loop keeps getting delayed; deep into production, you still don’t have anything you can actually play.

• The move to get a team to track and cost sprint tasks and visualize sprint performance keeps getting removed, then put back in and removed repeatedly.

• The art bible you asked for three months ago keeps getting delayed, then for another month, then another month, and 6+ months in, you wonder if it’s ever going to get done.

• You agree with a manager that they must have a difficult discussion with an underperforming employee. However, weeks later, you discover that even though the manager told you they had the discussion, it never happened.

• As a principle, you agree as a team to push towards a system of iteration rather than final polish. However, the team continues to operate similarly, and excuses are made every time questions are raised about the approach.

A commonality amongst many of the examples above is a general “agreement” by people but then delays or lack of follow-through. That generally means that the alignment you thought you had is, in reality, false.

To fix alignment, you must clarify WHAT to align on and VERIFY that alignment is truly happening.

1. What: Understanding and prioritizing what is critical to align on.

2. Verify: Auditing that teammates are actually aligned (not just saying they are).

What: Crystallizing Priorities

Even deep into development, many teams remain fuzzy on fundamental questions they should be aligned on:

• What is the vision of the game (or the vision of the product for non-game companies)? What is the “essence” (as per Rick Rubin)?

• How and by what metrics will a key role to hire for be evaluated?

• What are the expectations and focus for every milestone?

• Are deadlines commitments or best effort?

• How do we make decisions? Who owns AORs?

As a team lead or PM, your job is to crystallize and communicate the most critical areas requiring alignment for your project and team. This is situational and can’t be everything you can think of. You can't afford to diffuse focus by trying to align on everything. Ruthless prioritization is critical.

Once you've identified your top alignment priorities, it's crucial to communicate them clearly and repeatedly to key stakeholders and the broader team. In the upcoming section on communication, we'll explore the importance of clearly communicating through direct communication further.

Verify: “Trust, but Verify”

“Yeah, yeah, yeah, I understand. We’ll do that.”

Bullshit!

The number of times I have heard those words or some version of it, and there was zero follow-through, makes me sick.

Verification of alignment is essential. As I've learned the hard way, simply taking agreement at face value is staggeringly naive.

In my experience, there are three main reasons why professed alignment often proves false:

1. Lack of Belief.

A teammate doesn’t believe in whatever you agree on but doesn’t want to argue openly. Hence, they will do the bare minimum but not actually try to do what you have agreed upon. The team member may be capable but lacks conviction.

Note that lack of belief can also be a problem in leadership. As a lead, PM, or manager, it’s also your responsibility to communicate the importance of initiatives or decisions.

Lack of belief is a two-way street. Leaders must do a better job of instilling belief and team motivation. On the other hand, non-believers must be honest about their lack of belief.

2. Undermining Behavior.

This is much more dangerous. You have someone who disagrees with a decision and, instead of openly disagreeing, intends to do things their way sneakily. The moment they can, they will ignore decisions agreed upon with full intentionality to undermine decisions made.

If you ask them later why they acted to undermine a decision, they will make excuses or attribute their behavior to a “misunderstanding.” They may say, “Oh, I didn’t understand.” Or, “There was a miscommunication.”

Of course, these excuses are often lies. The kinds of people who undermine decisions are dangerous.

In almost all situations with underminers, you should move to eliminate these people from the organization. There are no questions or ambiguities here. If these kinds of people are allowed to stay on your team, they will lead to huge problems and be cancer to the company.

3. Laziness.

Some people on your team may agree and don’t intend to undermine your decision but will not put in full effort. These are people who lack the discipline or determination to see things through.

In my experience, many of these people are “naive dreamers.” They imagine themselves as senior leaders with many accomplishments but don’t get much done and don’t work very hard.

Trying to convince a lazy person to put in more effort is a losing proposition. This effort is like trying to push on a noodle.

If you have a string of wet spaghetti which you want to move forward, you can’t do it by pushing from the tail end. You have to pull it from the front.

-General George S. Patton, US Army General

“Trust, but verify.”

Given that there may be a lack of alignment despite “agreement” based on some of the reasons above, verification of alignment becomes critical.

There may be some proven or more experienced people you can trust. However, not verifying alignment is very naive, especially for new people, those with less experience, or those you haven’t worked with before. I know from experience, having learned the hard way. Years of failure have taught me that the “just trust your people” approach is very naive.

Don’t verify, and you’ll regret it.

2. Accountability

When setting expectations, no matter what has been said or written, if substandard performance is accepted and no one is held accountable—if there are no consequences—that poor performance becomes the new standard.

-Jocko Willink, Extreme Ownership: How U.S. Navy SEALs Lead and Win

In most startup situations, carrying dead weight and inefficiency can kill your project. While there is always some inefficiency and poor performance in all teams, accountability is critical to startup success and new game development to eliminate inefficiency.

In large, established companies, accountability is rare. Areas of responsibility (AORs) are often muddled to hide leaders who make mistakes and to enable them to take credit for others’ work.

This behavior significantly hampers the potential success of projects for startups and new game development initiatives. As a leader or product manager, you must fight against the temptation to keep accountability nebulous. Many will fight you on this, but accountability is absolutely critical. I’m repeating this mantra of how critical accountability is because of how important it is.

Let’s be honest. As an individual contributor, the political climate at your company may punish you for pointing out teams or people who are not being held accountable for poor performance. If that’s the case, you should seriously consider your future at the company. Your life is short; find another job. Find a better culture. Find a place where your efforts will be applied in an environment more serious about winning.

As a leader or someone capable of creating or influencing accountability, you must do what you can to push for it.

Super-talented people don’t want to be on a team with underperforming people who aren’t pulling their weight. Over time, a lack of accountability will lead to a team comprised of poor performers or mercenaries who are merely there for the money.

Accountability is crucial if you want to be part of a team that achieves great things.

Before closing the loop on accountability, I would like to add one note of caution. Situationally, be mindful that accountability often does not occur immediately. Especially with younger organizations, accountability can take time because 1. investment is being made into poor performers the organization is working on to improve, or 2. You have a role player or hired hand who is the best alternative until someone better can be hired.

3. Communication

Poor communication compounds misalignment and muddles accountability. You can't achieve alignment if vision and priorities aren't openly and constantly communicated. It's also harder to hold people accountable when expectations are unclear and ambiguous.

There’s a lot I could discuss about communication. However, for the objective of this post, I’d like to focus on the #1 priority that is the most challenging aspect of communication: being direct.

I submit that 99% of people struggle to be direct in challenging situations, and I further submit that 90% struggle to be direct even in standard situations.

Without unambiguous communication, alignment and accountability are not possible.

I’ve also noticed a tendency for many people to make excuses for themselves when they are not communicating directly. They will often delay or convey a message in a way that is so weak that it becomes a different message altogether.

Many people have an image of themselves that gives them a positive self-image and can be core to their self-worth. Based on this self-image, they may not view themselves as afraid of someone or too nervous to deliver a direct message. Hence, when they cannot communicate directly due to fear or other reasons, that image of themselves is attacked, causing cognitive dissonance. This then often leads to excuses or incorrect communication.

It’s challenging for someone unaccustomed to direct communication to do so suddenly. It feels hugely uncomfortable, and most people are terrified of it. The only way to overcome this barrier is through practice and repetition.

I have one final point on this issue. Sometimes, especially in startups, extreme emotion is needed to convey a critical situation or problem appropriately.

Someone cursing and yelling at another employee at a large company could result in that person being canceled and fired. At a startup, however, sometimes you need to be super clear and go over the top with some heat to ensure your message gets through. I hate it, and it’s very stressful, but I believe you must be as straightforward as possible in critical situations.

Unfortunately, being chill with “nice talk” usually won’t get the job done.

People often can only change under extreme situations and through direct clarity in expectations. Asking someone nicely to make significant changes and seeing massive change after a nice talk only happens in the movies. Even further, not giving super direct feedback about someone’s poor performance and firing them after all of your ambiguous “nice talk” is you being a jerk.

Believing otherwise is pretty naive.

4. Tracking Performance

Without appropriate tracking, accountability is challenging to implement.

Many people will also fight performance tracking, especially those with something to hide.

Tracking performance serves three vital purposes:

1. Planning & Progress: Tracking progress and maintaining a history of work velocity helps one gauge the team's progress and makes it easier to plan dependencies and development schedules.

2. Accountability: It clarifies where accountability is necessary.

3. Identifies Problems & Performers: Tracking will help identify problems and bring focus to why progress is not being made. Conversely, tracking can also help highlight high-performing teams or individuals to ensure they are appropriately compensated.

It’s very challenging to improve what you don't track. Without rigorous performance tracking, misalignment and unaccountability can fester unnoticed. Failing to address these issues could jeopardize your project. Act quickly before it’s too late.

Finally, it’s crucial to agree with a team on what constitutes good performance and the basis upon which performance will be tracked. Performance tracking reviews should not be antagonistic. You are still one team with the same goals. Try to use this practice to help each other improve and grow rather than to blame and attack.

In Conclusion

Getting a game studio on track is an immensely challenging task. While we are still in the process of full implementation, I believe the AACT framework, which focuses intensely on Alignment, Accountability, Communication, and Tracking Performance, can help us achieve long-term success.

This framework has already delivered benefits in terms of teamwork and operational efficiency, which I believe we will continue to improve upon.

We still have a long road ahead to deliver on our vision, but we're urgently moving to embed these principles deeply in our operations.

There’s no more time for us to lose. It’s time to AACT!

Does having an easy job, a nice family, and a big house define a life well lived? Is that success?

There was a time when two roads diverged in my career, and I considered: “Should I choose the path of difficulty or comfort.”

Many of you may be making a similar decision in your own life. Should you work just hard enough, train just hard enough, or be just good enough so you can spend time doing the other things you actually enjoy?

Or do you choose the more difficult path?

Do you want to work with passion, intensity, and with extreme dedication so that you can become the absolute best at your craft? As James Clear writes in Atomic Habits, is your work “have to” or “get to”?

This choice is the path to mastery.

You must train constantly. You must train repetitively. Learn this. Train well.

- Miyamoto Musashi, The Book of Five Rings

Miyamoto Musashi was possibly the greatest Japanese swordsman, with an undefeated record in 61 duels. He was not only a master swordsman but also a master philosopher who shared his philosophies in writing The Book of Five Rings.

Many consider Musashi the epitome of a Kensei, or “sword saint.” Kensei is a Japanese honorary title given to warriors with masterful swordsmanship skills.

Modern-day Kensei

Today, we have several modern-day examples of those who, like Musashi, became masters of their craft.

From my observation of many of these modern-day Kensei, through reading their works and listening to many interviews with them, I’ve noticed very similar traits amongst them:

• Work Ethic: Incredibly hard work ethic

• Passion: Passion and high emotion for their craft

• Details: Attention to detail

• Practicality: Focus on practicality over formal customs

• Discipline: Highly disciplined

• Determined Optimism: Masters believe, despite low odds, they will prevail

Let’s explore each of these traits in turn.

Work Ethic:

Bill Walsh is arguably the greatest football coach of all time. He was known as a perfectionist and workaholic. He would continuously think about football and ways to improve the teams he coached.

Exhibit a ferocious and intelligently applied work ethic directed at continual improvement

- Bill Walsh, The Score Takes Care of Itself.

All Kensei understand the criticality of an incredible work ethic.

Kobe Bryant, another master, was famous for having an insane work ethic which he discusses in this video below:

Most professional athletes have an incredible work ethic, but the great ones go even further than their peers:

Elon Musk, who has created the most significant companies of our time and potentially ever in history, states an obvious but often overlooked point:

There are easier places to work, but nobody ever changed the world on 40 hours per week.

Famed football coach Chip Kelly puts it this way:

Last time I checked, there is no ‘Hall of Average.’

There will always be people who question the path of difficulty. The drumbeat toward working less, focusing on enjoyment rather than meaning, and forcing their own "work-life balance" choices has never been louder.

Today, it has even reached the point where many people try to impose their own choices on others. The head of HR at another game company told me recently, “You must adopt work-life balance at your company.”

Never let people who choose the path of least resistance steer you away from your chosen path of most resistance.

- David Goggins

Passion:

Kensei are passionate; they care deeply about their work and craft. These deep emotions drive them to become the best.

See the musician Keshi’s reaction to his fans’ appreciation of his work:

Elon Musk is a man on a mission to save humanity. You better believe he holds powerful emotions about his mission, his work, and his craft:

In the book The Score Takes Care of Itself, San Francisco 49ers assistant coach Mike White described Bill Walsh’s passion and “obsession” with improvement:

Bill forced us to think at a higher level, which was the starting point for getting players to play at a higher level and the organization to operate at a higher level. That was his total focus, like an obsession. All he talked about was improvement.

Details:

Kensei focuses on details.

Pay attention even to trifles.

- Miyamoto Musashi, The Book of Five Rings

Note both the attention to detail and the emotion Matt Damon exhibits in trying to create a commercial with another actor:

The OG of details is Steve Jobs. Jobs was famous for perfection and making sure everything in his products delivered an incredible user experience.

Practicality:

Kensei are practical and focus on effectiveness over formality, and avoid just the perception of doing things in the right way. Musashi wrote: “Do nothing which is of no use.”

In his battle with Ganryu Sasaki Kojiro, known to be one of the best swordsmen of the time, Musashi chose to battle with a boat oar. Scholars have debated this point over the years; however, the swordmaster Hirayama Shiryu-gyozo wrote in his book Discourse on Swordsmanship:

Ganryu Sasaki Kojiro used a sword whose blade measured ninety centimeters in length. It was nicknamed "the clothes-drying pole." Judging that it would be to his disadvantage to use two swords, both of which were shorter than that of his opponent, Musashi asked the boatman to give him an oar, from which he made a large wooden sword. With that he could kill his adversary by smashing his skull. Musashi's talent was this ability to change his means as appropriate for a given adversary.

Kensei focuses on practicality, not common wisdom or traditional customs.

Elon Musk suggests likewise using common sense as a guide:

In general, always pick common sense as your guide. If following a ‘company rule’ is obviously ridiculous in a particular situation, such that it would make for a great Dilbert cartoon, then the rule should change.

Finally, Jeff Bezos shares a similar message he wrote in an Amazon shareholder letter. Despite their differences, both Musk and Bezos agree on this philosophy of practicality:

Good process serves you so you can serve customers. But if you’re not watchful, the process can become the thing. This can happen very easily in large organizations. The process becomes the proxy for the result you want. You stop looking at outcomes and just make sure you‘re doing the process right. Gulp.

It’s not that rare to hear a junior leader defend a bad outcome with something like, “Well, we followed the process.” A more experienced leader will use it as an opportunity to investigate and improve the process. The process is not the thing.

It’s always worth asking, do we own the process or does the process own us?

Discipline:

Mastery is created over a career, not overnight.

As Muhammad Ali once stated:

The fight is won or lost far away from witnesses - behind the lines, in the gym, and out there on the road, long before I dance under those lights.

As game developers, too many people don't realize that the battle isn't won or lost during the global game launch. Instead, it's won in the years of development leading up to the launch: Every day, every long night, every weekend, every sacrifice made, putting blood, sweat, and tears into the product during development.

As Vince Lombardi suggests:

Winning is not a sometime thing, it is an all the time thing. You don’t do things right once in a while…you do them right all the time.

Further, as the master of being badass, David Goggins, once posted on Instagram:

davidgoggins

A post shared by David Goggins (@davidgoggins)

True self-discipline is not for the weak-minded! In life we make too many excuses- I don’t live near a gym, don’t have the money for a trainer, my hours at work are crazy, I’m traveling too much, the kids schedules are too hectic, etc. The list is endless! Rather than giving yourself a way out, find a way to make “it” happen. There are 24 hours in the day. I can guarantee you that if you were to go through your schedule, you will find time where you can be more efficient and productive. For example, if you are watching tv, during every commercial break, do something! No one cares if you succeed or fail, it’s truly up to you. There are no tricks or shortcuts to any of this, it all comes down to self-discipline. It’s you against your mind. Your mind will always tell you that you don’t have the time. The one thing that we forget is that we are in charge of what we tell our minds, not the other way around!

Determined Optimism:

Kensei believe they will prevail. They believe in a way I call “determined optimism.” This differs from “blind optimism,” in which people hope for the best without actually taking any action to increase the odds of a successful outcome.

Elon Musk rationally understood that both Tesla and SpaceX likely only had a less than 10% chance of success, yet he bet everything on those companies anyway. Ultimately, he believed in his ability to achieve the results he needed to win.

In his 2008 Wired magazine interview, Musk put it this way, just after 3 failed launches for SpaceX and only having enough money for one more launch:

Wired.com: How do you maintain your optimism?

Musk: Do I sound optimistic?

Wired.com: Yeah, you always do.

Musk: Optimism, pessimism, fuck that; we're going to make it happen. As God as my bloody witness, I'm hell-bent on making it work.

The Modern-day Fantasy

How many today believe they are on a path to mastery, yet don’t have the traits I have described?

Today, we live in a world with dreamers who believe that ordinary effort can produce extraordinary mastery and outcomes.

Our society has been teaching a completely twisted fantasy:

• “You can be anything you want to be.”

• “You will be somebody great; you just need to believe.”

In addition, many push a narrative of somehow achieving greatness without effort:

• “People work better and more effectively with work-life balance.”

• “You just need to work smart, not hard.”

Is there anyone out there who believes Steph Curry or anyone could do the following practicing 9-to-5?

I’m sure Steph practiced smart, but you can be sure he also practiced extremely hard.

Becoming a Kensei

In our world today, the voices advocating for mediocrity scream louder than ever. People live a fantasy of praising masters like Elon Musk while in the next breath proselytizing the “4-hour work week.” This makes no sense.

What is your choice?

Not your delusional fantasy of becoming the best in the world with zero effort and sacrifice, but your actual choice for what you want from your life.

I respect anyone who chooses a life of comfort and “work-life balance,” but in a similar vein, I hope people appreciate the choice others make on their path, seeking meaning and mastery.

I chose the path to seek the mastery of a Kensei for my life.

Two roads diverged in my career-

I took the one less traveled by, the path of difficulty, and the path towards mastery.

And, for my choice in life, that has made all the difference.

In conclusion, just my opinion, don’t hate. Let’s be cool with having different views.

Key Trends:

• Rise of Emerging Countries: Former game development geographies better known for low-cost production and content pipelines, such as China, Turkey, and Poland, have now become centers of excellence and clusters for world-class talent

• Cost Structure: Lower costs create a “structural advantage” for teams in emerging countries relative to highly paid but not necessarily more capable teams in the West

• Technology Leveling: The emergence of third-party development, back-end, and operating frameworks has leveled the playing field for smaller development teams. Examples include Unity or Unreal for client development, Photon for netcode, and Gameye for server orchestration, not to mention cloud-based storage, data warehouse, and database services from Amazon/Google/Snowflake, etc. These services have enabled smaller teams to focus on game-oriented differentiation without having to acquire specific expertise and specialization across a gamut of other development disciplines.

• Dissemination of Information: More and more information around technical and product-related best practices is more widely available. Information creators such as GameMakers and world-class experts such as Glenn Fiedler with Network Next continue to publish formerly highly secretive information. Further, when one company in a specific geography “figures out” how to make a hit game, the talent from that company can then disperse to other companies nearby, creating a center of excellence in specific game areas.

• Access to Capital: There’s an increasing understanding that opportunities for F2P game development abound globally. Therefore, capital from successful founders in emerging geographies or venture capital that specifically seeks to invest in high potential geographies has become increasingly available.

Here’s a slide from a presentation that’s a few years old now but represents fairly crisply the cost structure advantage that’s possible:

These trends are leading to insurgent game studios suddenly with the capability of being globally competitive from geographic regions formerly less competitive. FunPlus and Lilith emerged on the scene from China dominating 4X, and MiHoYo has single-handedly turned China into a significant innovator for cross-platform games and a world-class, global competitor in console games. Even further, companies like Dream Games in Turkey show how new companies from emerging countries can become world-class leaders in their markets almost overnight.

Speaking of MiHoYo: How can any Western game studio compete with a leading company from China anymore?

• Dramatically lower cost structure

• Super hard work ethic

• Locally available best-in-class talent

• No ideological hang-ups about F2P monetization

• Can now spend $100M in budget for new game development and $200M a year in live ops

Meanwhile in Canada… 🧐

Incumbents always seem to forget about Clayton Christensen's concept of The Innovator's Dilemma in which disruptive technologies from insurgents overtake older, established incumbents.

What are large Western AAA game studios today if not old incumbents? How can we not consider companies like Mihoyo a disruptive insurgent force in the gaming industry?

Game over.

The Tides of War are Shifting.

The Case for India & The IndiaF2P Games Conference

Against this backdrop, a small group of adventurers has bet their lives and careers that the next emerging country will be India!

That’s me in the center above.

In August, we hosted the first IndiaF2P virtual games conference to help foster community and share best practices in this specific community. While much of the market today is still early and developing capability, we believe longer-term that India can and will become a global leader in F2P games.

Below you will find links to the talks from that conference, including speakers who are some of the biggest movers & shakers in the Indian F2P games community.

1. How India Becomes A World Leader in Games

I enjoyed moderating this panel. All around fantastic speakers, but I do have to give a special shoutout to Manish Agarwal, the CEO of Nazara (recently went public), who left me with a specific insight that I quoted and shared with my company during the pre-conference meetup:

For us, my simple learning was that investors trust companies that deliver on what they’ve been promising. From Nazara’s perspective, we have been engaging with those investors for the last 2 years… What narrative we said, what we would deliver, when they saw the delivery happening consistently, so that made my life much easier. Because you are known… there is a comfort and trust you have built. There is a consistent delivery and cadence you have set up. You are not an unknown entity.

Moderator:

• Joseph Kim, CEO, LILA Games

Speaker:

• Manish Agarwal, CEO, Nazara

• Amit Hardi, CEO, Nukebox

• Salone Sehgal, General Partner, Lumikai Fund

• Anuj Tandon, Head of Corp Dev, Krafton

2. Doing the Work To Make A Top Grossing Game

This video somehow got shared quite a bit in various LinkedIn posts and other newsletters. Thanks to everyone who shared, and yes, we also think Paul is hardcore! Lol.

Speaker:

• Paul Leydon, CCO LILA Games

3. Key Technical Challenges in Scaling F2P Games

We think Arvind is the man! Always great to talk to our friend who was a tech evangelist both at Unity and now at Epic. Given his background, he knows a thing or two about tech! In this talk, LILA Games’ CTO Avinash interviews Arvind and also gives a few lessons from his own experience:

Speakers:

• Avinash Pandey, CTO, LILA Games

• Arvind Neelakantan, Technology Evangelist, Epic Games

4. How to Build A Successful Career in F2P Games

Anyone interested in joining the games industry should listen to the perspectives of these great folks who generously share their experience and wisdom! Believe it or not, this is Vik’s first panel as a moderator. Great job, Vik!

Moderator:

• Vik Agarwal, Lead PM, Zynga

Speakers:

• Poornima Seetharaman, Director of Design, Zynga

• Karan Gaikwad, Lead PM, Nukebox

• Shilpa Gaur, Lead Marketing & Strategy, Cympl

5. What Global Strategics Are Looking for From Indian Game Companies

Lumikai is one of the funds that is betting big on India. You should listen to the insights from Salone in the first talk, but we also anchored the conference with Justin Keeling as moderator for this last panel.

Justin Keeling is almost as charismatic and good-looking as I am, so I highly recommend you check out his moderation of this great panel. 😜

While we have great speakers all around, special thanks to Alexis, who has always been very generous with his time participating in content with us! Also, many thanks to Justin Scarpone for staying long and answering questions late! And, as a former SEGA alumnus, I have to give a shoutout to Saito Go. Go SEGA!

Moderator:

• Justin Shriram Keeling, General Partner, Lumikai Fund

Speakers:

• Alexis Bonte, Group COO, Stillfront Group

• Saito Go, Executive Officer & Head of Japan Asia Publishing, SEGA Corporation

• Justin Scarpone, SVP & GM Asia, Scopely

Why India?

At LILA Games, we believe in the emergence of India as an insurgent and upcoming world-class global power in the F2P gaming industry. It will come, if for no other reason than the fact that we are going to help create it, just like Bugsy Siegel helped start Las Vegas.

Here’s a video from when Paul Leydon and I first traveled to India to explore development partnerships there:

I’ve been asked this same question quite a lot: “Why India?”

I give a lot of answers to this question but in reality, the truth is something deeper.

Rise of The White Tiger

The White Tiger is a movie both tragic and beautiful, evil and hopeful. It speaks to wealth inequality and more importantly opportunity inequality. It is, to some degree, India’s version of The Squid Game and asks a fundamental question:

• How does one rise beyond the rooster cages of their circumstances?

Some of the quotes from this movie I’ll take with me for the rest of my life:

• “Rich men are born with opportunities they can waste.”

• “You were looking for the key for years, but the door was always open.”

• “This is the century of the brown man and the yellow man.”

• “I am just one who has woken up while the rest of you are still sleeping.”

• “The moment you realize what is beautiful in this world, you stop being a slave.”

• “It was all worthwhile to know, just for a day, just for an hour, just for a minute what it means, not to be a servant.”

I’m an old bastard who, aside from my family, hasn’t done anything truly meaningful in my life yet. The answer my friends to the former question: do something actually meaningful.

As the late great Clayton Christensen wrote: “How will you measure your life?”

We are building an opportunity platform. We chose India to build The White Tiger of the games industry.

If you believe in this mission, check out our opportunities below and help us blow the fucking doors off these god damn rooster coops.

And while I don’t recommend that leadership teams focus on competition in the micro, I do recommend that leadership teams consider competition in the macro. In other words, don’t focus too much on what specific competitors are doing or overly focus on vainly trying to protect market share in a zero-sum game.

Instead, think of specific competitors as other players in an Infinite game. However, on a broad strategic level, you need to understand and design specific advantages that your company has that others do not.

So, what is structural advantage?

Structural advantage refers to the fundamental and systemic ways in which a company operates that are significantly better than those of other companies in the same ecosystem.

One of the most archetypal examples of a company with structural advantage is Amazon. Amazon competed against physical bookstores with a vastly larger selection, the ability to shop 24/7, the ability to continuously CRM customers, analytics and web-based optimization, and a powerful recommendation engine. Relative to other online retailers, they invested massively in infrastructure, customer service, and advanced recommendation technology.

In fact, Jeff Bezos disliked competition on a “level playing field”:

The other thing about competition is that you do not want to play on a level playing field… When it comes to competition, being one of the best is not good enough. Do you really want to plan for a future in which you might have to fight with somebody who is just as good as you are? I wouldn’t.

There are numerous examples of companies that leverage structural advantage to win in their respective markets. However, surprisingly, this is an area in which game company leadership teams think very little about. They focus instead more on tactics, execution, and operating “by analogy.” In other words, just doing things the way that other companies do things or how they did it before.

This is the opposite of innovation, and one of the reasons, in my opinion, why we should have much more innovation in gaming than we currently do.

In my view, I believe new game companies will emerge that find dramatic structural advantage in unforeseen ways that will destroy lazy incumbents. These insurgent companies will create a new world order of game company leadership, leading to better innovation and more products that gamers will love to play.

Examples of Structural Advantage

Surprisingly, we continue to see structural advantage deployed by companies that dramatically shift the power dynamics in lots of otherwise super competitive markets.

Here are some good examples:

There are two key takeaways I suggest you think more deeply about.

First, note that there seem to be fairly common sources of structural advantage from the following types of sources:

• Data: Use of data/data science for insights or recommendations

• Cost: Cost structure advantage

• Process: Process advantage in enabling additional time and cost efficiencies

• Vertical Integration: Owning a greater portion of a value chain or product to increase efficiency or provide higher profit margins

• Can’t Follow: Building strategies predicated on the inability of competitors to follow into specific markets

• Culture: Superior culture and communication leading to decision making, efficiency, and effectiveness improvements

Secondly, it appears that all of the examples above seemed to take a unique approach to how they operate their companies. In the words of Elon Musk, they seemed to have designed their businesses through “first principles thinking” rather than by operating “by analogy.”

IMHO Tesla, in particular, will be looked at in the future as one of the greatest companies ever created in the history of humankind built upon massive structural advantage.

How Chip Kelly Revolutionized Football

I first formalized my thinking about structural advantage as a college football fan. In 2007, Chip Kelly’s offense instantly turned the Oregon Ducks football team into the #1 scoring offense in the Pac-10 conference. For me, the history and context of Kelly’s approach were instructive on how a company should also think about its business.

Chip Kelly revolutionized college football through his unique approach. Many of the concepts he developed have been copied by many other teams including NFL teams today and were used to great success. During Kelly’s tenure as head coach of the Oregon Ducks, he took the team to multiple top 5 rankings including an undefeated regular season and the College Football Playoffs in 2010.

So how did he do it?

Although Chip Kelly is known for being an offensive coach. He started off as a defensive coach.

As a defensive coach, Kelly noticed specific situations that gave him a lot of problems as a defensive coach. And he basically took those things and used them as an offensive coach.

So let’s take a couple of examples of systems he installed. First, the hurry-up offense. As a defensive coach, Chip Kelly noticed that when opposing teams ran a lot of plays quickly his defense got tired very quickly. On the offensive side of the ball, Chip made his players become super conditioned. would make his players learn a few basic offensive plays but know them super well. Hence, when he ran a hurry-up offense and would run plays over and over very quickly, opposing offenses not only couldn’t substitute, but they would get fatigued and would often even have problems just getting lined up properly.

Using this concept, Chip Kelly was able to neutralize opposing teams’ super talented 5-star players by having his 2-star and 3-star rated players become super conditioned. Through the hurry-up and the “spread”, he forced defenses to have to run all over the field and without rest, quickly fatiguing those players. Therefore, he beat teams with much better players than his team, by finding a way to gain structural advantage.

Kelly also pioneered the concept of the zone-read option. Without going into too much detail here, by using a more athletic, running quarterback, this system gives the quarterback the option to keep or handoff the football based on how a play develops. It gives the offense a numerical advantage by turning the quarterback into a potential runner. This optionality put a lot more pressure on defenses and enabled the offense to have an extra player on run plays involved in moving the ball forward.

These are a few examples. Kelly also came up with a numerical system for defensive linemen to determine their blocking assignments and many other concepts. The bigger point I’m making, however, is that whether it’s the hurry-up, the zone read, or other systems, all of these systems create mismatches and structural advantage which led to massive success.

Structural Advantage In The Games Industry

In the history of the world, companies with structural advantage ultimately win out. Now, let’s discuss structural advantage in the gaming industry.

I’ve already heard from key leaders at companies like Blizzard and others, who won’t be named, that they are “scared to death” of Mihoyo and the Tencent studios, such as Quantum and Timi. A dedicated and more motivated work culture, deep and expanding expertise in game development, the ability to leverage frameworks like Unity or Unreal to level the playing field, and massively lower cost structure.

At Lila Games, we believe we have several ideas and innovations that offer a structural advantage. To be clear, I’m not here to convince anyone that we will be successful or to replicate our approach.

However, I do believe that not enough game company leadership teams have taken the time to think about structural advantage. This has led to the same lazy corporate initiatives around buybacks, focus on M&A, and making the same shit over and over again.

I can say, whether we at LILA succeed or fail, at least we tried.

On that note, let me leave you with a really interesting discussion thinking about structural advantage and long-term defensibility in games by:

• Kristian Segerstrale: CEO Super Evil Megacorp, Founder of Glu & Playfish, Seed investor in Supercell

• Mark Sottosanti: CFO, Riot Games

• Lloyd Melnick: GM Chumba Casino, Former exec at a bunch of places, including Zynga