Annual Review 2025

Sharing what went well and what didn't go well in 2025, and what I look forward to in 2026.

It’s the time of the year to reflect and review, and to take a look into what next year will hopefully bring to me. For the past five years, I’ve been in the habit of reflecting on the past 12 months, what have gone well, what hasn’t gone well and what things I look to improve. Previous reviews from 2020, 2021, 2022, 2023 and 2024.

Some handy templates for annual reviews that I’ve utilized over the years:

• Steve Schlafman’s Annual Reflection Guide

• James Clear’s annual reviews

• Chris Guillebeau’s annual reviews

So let’s get started.

What went well in 2025?

A lot of things went well this year. First, we completed several investments with F4 Fund, and I’m genuinely happy about how that chapter progressed.

But more importantly, during the summer I was fully bitten by the “AI bug.” That moment helped me see something very clearly: I am an entrepreneur first. I love building things, going deep into products, and watching ideas turn into something real. AI pulled me back into that mindset in a way I hadn’t fully felt in years.

I’ve experienced this kind of timing advantage before. When we started Next Games, mobile free-to-play gaming on smartphones was just taking off. The App Store was still early, distribution was changing fast, and new behaviors were forming. That timing mattered. We ended up building a company that eventually exited to Netflix, and in hindsight, the biggest leverage wasn’t just execution, but being early in a real platform shift.

I increasingly believe that the highest leverage an entrepreneur can have is to ride a genuine new wave, not a trend, but a fundamental change in how people behave and how products are experienced. For me in 2013, that wave was mobile free-to-play gaming. In 2025, it is clearly AI.

You could argue that moments like this resemble gold rushes, and in some sense they do. But AI feels different. This isn’t just another speculative cycle. It is a structural shift in how work gets done, how products are built, and how people interact with technology. In many ways, it feels comparable to the smartphone revolution, and arguably even larger. Smartphones changed what we carry in our pockets and how often we engage with a screen. AI changes how we think, create, and solve problems on a daily basis.

When I compare this to other “timing moments,” like the crypto and Web3 wave a few years ago, the difference is stark. That movement never felt like a true platform shift to me. It didn’t fundamentally reinvent everyday behavior, beyond a narrow set of financial use cases, and the incentives for mass adoption were never strong enough. With AI, the incentives are immediate and obvious. Anyone using generative AI, whether for writing code, creating art, answering complex questions, or building presentations, feels the value instantly. There is no friction in understanding why this matters.

What did I change my mind about in 2025?

That I could actually be a founder again. I had thought that my life of building and launching product was behind me, but it’s been the best mind change I’ve done in years. And that decision has felt better and better as more time goes on. I’m learning so much about myself in the midst, which is probably the most gratifying thing about being an entrepreneur again.

What didn’t go well in 2025?

There are quite a few things I could list, but one of the biggest was my expectation around AI and how much heavy lifting it would do for me when building products. When I started producing apps and experimenting seriously with AI-assisted coding, I genuinely believed the tools would take care of most of the work. When I picked up Claude Code during the summer, it felt like something entirely new. For a moment, it even felt like I didn’t need to do everything myself anymore.

At the same time, that illusion quickly broke. It felt like the tools could do everything, but in reality, they couldn’t. Especially when working on larger applications with multiple interconnected systems, client-server architectures, and real-time user interactions, the limitations became obvious. AI coding agents struggle to truly understand complex products as a whole. They have limited context windows, and unless you explicitly design your workflows to compensate for that, they simply cannot keep all the critical pieces of a project in mind at once.

I learned that AI does not anticipate product needs in the way a human architect does. To make it effective, you need very deliberate structures, rules, and methods that force the agent to repeatedly re-anchor itself to the core principles of the project. Without that, things slowly drift, and complexity becomes a liability rather than a strength.

Another thing that didn’t work out was my plan to create a coding course around AI-powered game development. I had hundreds of people on a waiting list, but the course never materialized. The core reason was simple: everything was changing too fast, including my own understanding. I spent most of the summer actively coding and learning, and by late August it felt like I should finally share what I knew.

But the problem was that I was still running into new issues every single week. AI coding constantly introduced new frustrations and unexpected limitations. I didn’t want to teach something that would immediately become outdated, nor did I want my students to hit the same walls I was hitting without having better tooling and solutions already figured out for them. Teaching felt premature when I hadn’t yet stabilized my own workflows.

Finally, after deciding to leave F4 Fund, I completely underestimated how consuming starting a new company would be. I didn’t expect it to affect my ability to write and reflect as much as it did. Building a startup is an all-consuming effort, and I felt that deeply this fall. After kicking off my new company project in September, my focus narrowed almost entirely to execution.

Right now, that company is centered on building mobile consumer apps with AI, drawing heavily on everything I’ve learned from two decades in the games industry and from being both an entrepreneur and a VC. But the trade-off was real. Writing, teaching, and stepping back to reflect became much harder than I expected.

What habits or interests held me back?

I went through my notes and reflections from the year and here are the things that stood out and things that could have held me back.

1. Too many parallel tracks. I consistently carried more projects, ideas, and experiments than my attention could truly support. Even good initiatives became diluted when run side by side.

2. Perfectionism disguised as preparation. I often stayed in optimization mode, refining systems, workflows, and setups instead of committing and compounding with something good enough.

3. Tool curiosity replacing execution. Exploring AI tools, models, and workflows sometimes felt like progress but delayed shipping and real-world validation.

4. Underinvesting in recovery. Stress, sleep issues, and insufficient recovery quietly reduced my cognitive capacity, creativity, and patience over long stretches.

5. Turning learning into pressure. I treated learning as a race, creating unnecessary urgency and self-imposed expectations that reduced enjoyment and clarity.

6. Execution crowding out reflection. Once I entered full building mode, I failed to protect space for writing, thinking, and synthesis, assuming it would happen automatically.

7. Opening loops faster than closing them. I started more initiatives than I finished, slowing momentum and limiting the compounding effect of completed work.

Top lessons learned in 2025?

Besides the fact that entrepreneurship is my way and not investing? Let me think.

No, actually this year delivered more learning than I expected, mostly through friction rather than smooth execution. These aren’t theoretical insights. They’re lessons earned by building, hitting limits, and adjusting in real time.

The biggest realization was that AI is leverage, not autonomy. It doesn’t replace thinking, judgment, or architectural responsibility. When I assumed it could “just handle things,” especially in complex products, it failed. The real power came from pairing AI with clear constraints, explicit rules, and strong product intent. Experience didn’t matter less this year. It mattered more.

I also learned that focus compounds more than intensity. Pushing hard across too many parallel efforts created motion without depth. Progress only accelerated when I narrowed the scope and stayed with a problem long enough for effort to compound. Intensity without focus produced noise. Focus produced momentum, and I’m still trying to learn it intensely.

What is my purpose for 2026?

I really want to ship a consumer app and run marketing for it, all by myself. I’m now in a spot, with all the AI tooling available, to make this a reality and to scale a business like that. The goal isn’t to ship and grow; rather it’s to actually show that you don’t need to raise funding to make it. Too many founders obsess over raising VC before they get going, and I want to prove that this is not necessary.

In 2026, my purpose is simple and very concrete: I want to ship a consumer app and take it all the way to meaningful traction entirely on my own. I want to build it, ship it, and run the marketing myself, end to end.

The point isn’t just to launch something, or even to grow it aggressively. The deeper goal is to demonstrate that, with today’s AI tooling, it’s now genuinely possible to build and do some early scaling for a real consumer business without raising venture capital. I want to prove this by doing it, not by arguing about it.

Too many founders fixate on fundraising before they’ve built anything of substance. Capital becomes the plan instead of a tool. I want to show a different path: start with users, distribution, and revenue, and let everything else be optional. If funding ever becomes relevant later, it should be a choice, not a prerequisite.

Do not get me wrong, this isn’t an anti-VC statement. VC has its place in growing companies past a certain point, when you’ve shown that things work and that there is a massive outcome to be pursued.

This is an efficiency statement. AI has lowered the cost of experimentation, development, and iteration so dramatically that individual founders can now operate at a scale that previously required teams and capital. My purpose for 2026 is to fully lean into that reality and make it visible through a real product in the world.

What 2-3 goals do I want to accomplish in 2026?

1. Ship and grow one consumer app to real usage and revenue, solo

I want to take a single consumer product from idea to real users and recurring revenue without raising funding or building a team. What matters isn’t just shipping, but owning the full loop: product, iteration, and distribution. This goal forces focus and removes excuses. If I can make this work alone with modern AI tooling, it proves that building a sustainable business no longer requires capital as a starting point.

2. Build repeatable solo-founder systems for product and marketing

Beyond one app, I want to develop reliable systems for how I build, ship, and market products as a solo founder. This includes AI-assisted development workflows, fast iteration loops, and distribution tactics that don’t depend on paid growth. What’s important here is compounding. If the systems work once, they should work again, and that turns one success into a durable operating model.

3. Make independence visible through execution, not commentary

I want to demonstrate, through a real product in the market, that founders don’t need permission or capital to get started. This isn’t about being anti-VC. It’s about shifting the default mindset from fundraising to building. What matters is credibility earned by execution. The product itself should be the argument.

Finally, what do I need in 2026?

More than anything, I need fewer moving parts and clearer constraints. I don’t need more ideas, tools, or opportunities. I need a tighter operating environment where focus is protected and decisions are simpler. One primary product, a small set of metrics that matter, and a clear definition of what “good progress” looks like.

I also need to deliberately protect energy. Sleep, recovery, and mental space can’t be treated as background variables anymore. They need to be designed into the year, not hoped for between sprints. High-quality output depends on sustainable input, and this year made that non-negotiable.

Happy new year everybody!