Swen Koller

🤔 Where are the moats for "GPT wrappers"? After building multiple LLM-based apps used by thousands of users, here's what I've learned about creating defensible Vertical AI solutions... 🧵👇

When are we getting the "@grok is this true" in Zoom calls?

@ErnestRyu It'll be like software engineering. The 10% of math research work AI can't do well yet will be 100x more valuable, the other 90% will be automated.

10. My career as a mathematician certainly isn't threatened by AI; in fact, I hope to leverage AI to accelerate my work. However, I'm unsure whether "mathematician" will remain a career path for my son’s generation. (10/10)

Two cents on AI getting International Math Olympiad (IMO) Gold, from a mathematician. Background: Last year, Google DeepMind (GDM) got Silver in IMO 2024. This year, OpenAI solved problems P1-P5 for IMO 2025 (but not P6), and this performance corresponds to Gold. (1/10)

Main bottleneck isn’t compute, it’s data and exploration. The challenge now is how to turn compute into useful, generalizable knowledge.

Next paradigm: pretraining + high-compute RL + environment interaction. Needed for general agents, science, and eventual AGI.

@shuchaobi shared perspectives from his OpenAI research at Harvard today. Key insights on what’s next:

Software engineers are evolving from being 10% logic designer and 90% translator to being 95% logic designer and 5% translation verifier.

For AI apps, context is the moat. OpenAI‘s memory feature increases the usefulness and switching cost of ChatGPT. We will see the same with other AI apps.

With the likes of OpenAI‘s o3 and its ability to produce truly novel work it feels like the intelligence take off is starting. Models will improve models.

@Sprintax_USA Your chatbot suggests exactly the right question. Let me know if I can help you build a chat bot that actually works.

Today @JoshuaKushner came to talk at @Harvard. My top three takeaways: 1) Thrive only invested in seven AI companies over the last 3 years. Josh explained, he doesn’t know if any of the vertical AI companies will still exist in a world with extremely capable AI models 2) OpenAI now is like Apple before they had decided which apps they build vs. let developers build. They need to look after their ecosystem but also want to build some themselves 3) A big opportunity Josh sees is vertical models such as for life science, physical intelligence or industry specific (e.g. legal)

The limiting factor of AI models today for most knowledge work is lack of context, not model capability. We’ll increasingly see tools to capture context to easily add it into prompts.

For a course at Harvard, I developed a game using AI. My assignment was overdue, so I made that the theme of the game. In Overdue, you’re a student dodging an endless wave of homework by firing excuses at professors. You can play it here: overdue.swenkoller.com (desktop only)

Projection: In 15 years, we will be talking to AI for 4-6h per day. Analogy: The iPhone was released 18 years ago. I now use it 4-6h per day. We should expect AI to have a similar impact on our day-to-day interaction with the world.

@garrytan The future is now

For 25% of the Winter 2025 batch, 95% of lines of code are LLM generated. That’s not a typo. The age of vibe coding is here.