Swen Koller

Building with LLMs. MS / MBA @HarvardHBS | Forbes U30

[Swen Koller @swekol]

🤔 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... 🧵👇

[Swen Koller @swekol]

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

[Swen Koller @swekol]

@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.

[Swen Koller @swekol]

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

[Swen Koller @swekol]

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

[Swen Koller @swekol]

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

[Swen Koller @swekol]

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

[Swen Koller @swekol]

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.

[Swen Koller @swekol]

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.

[Swen Koller @swekol]

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

[Swen Koller @swekol]

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)

[Swen Koller @swekol]

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.

[Swen Koller @swekol]

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: https://t.co/ZT1WcQxTga (desktop only)

[Swen Koller @swekol]

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.

[Swen Koller @swekol]

@garrytan The future is now

[Garry Tan @garrytan]

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.