We're building the world's most capable AI for software development & the applications to unlock the potential of developers.


The future of software is AI, the future of AI is software.

We believe in a positive technological future, one of abundance for humanity, one where AI progress will help us drive improvements in science, health, housing, food, and education by making it better, more affordable and more accessible.

To get there, we need to develop sufficiently advanced Artificial Intelligence, and today we’re still far from it. We believe that all of humanity's greatest technological breakthroughs can be traced back to continuous iteration, with ideas building on top of each other and compounding. We believe that in our life-time neural networks will be capable of learning anything and everything at human skill level and beyond.

While others are focused on building general purpose AI, we've decided to focus on a single capability, software development. To build software you need to have an understanding and model of the world, and be capable of reasoning and planning. Software development in our opinion represents a lot of what makes up human intelligence. It is also a capability that as we continue to improve it, has a massive immediate positive impact on progress in our world.

We want to work towards a future where artificial intelligence will integrate in our lives in such a way that most economically valuable work can be done by machines, giving people the freedom to choose how they spend their time.


The journey towards this future is a long one and ambitious goals to nudge humanity towards more abundance can only be achieved if poolside is around for the long-term. This is why we feel very strongly about the importance of sequencing towards this future.

Step One
Assist developers in building software by building the most capable AI for software development
Step Two
Allow anyone to build software by making AI-led ↔ human-assisted interactions the next abstraction for building software
Step Three
Generalize these capabilities beyond software to all other fields

We believe that over time interactions with machines will go from human-led ↔ AI-assisted to AI-led ↔ human-assisted.

Our first major milestone in step 1 is to significantly surpass the state of the art that is currently held by general purpose models. To do this we're focused on training a large language model that is entirely oriented towards software development and allowing it to improve by completing millions of tasks in tens of thousands of real world software projects.

We call this approach Reinforcement Learning from Code Execution Feedback and we’ll be sharing a lot more about it.

Some of our strong beliefs, weakly held (empirical results will show us) are:

  • To push beyond current capabilities you need to train your own foundation model
  • You can’t fine tune your way to success - major capabilities ‘emerge’ from training a base model and are made accurate and useful during fine tuning
  • Scale matters, more compute and data solve for a large subset of problems
  • Not all tokens are equal - there is a lot of value in truly obsessing over the quality of our data
  • Building our own training stack allows us to iterate faster
  • Synthetic data generation, while seemingly counterintuitive, works and works particularly well for code. Over time we suspect that all data that models are trained on will become synthetic
  • Yes, larger models are more likely to show the strongest capabilities, but once you have them you can distill them into smaller models that are useful in production
  • For LLMs to improve at software development, they need to have a real world environment in which they can improve through self-play


We believe big missions are achieved by small groups of people who are deeply passionate and committed to the problem they’re tackling. They are resilient, low-ego, kind-hearted and bring lots of raw brain power to the table.

The team that is formed at the beginning of a company is the biggest determinant of its success. Which is why we’re very proud of the team we’ve assembled and hope if you are reading this you’ll consider joining the mission.

poolside was founded in April 2023 by Jason Warner and Eiso Kant.

Prior to poolside, Jason was a VC at Redpoint, CTO at GitHub and led engineering at Heroku & Canonical.

Eiso, a serial entrepreneur, previously founded Athenian (2019) and source{d} (2016), one of the world's first companies dedicated to applying AI to code.

We're always keen to meet people who are interested in what we're building. If you'd like to get in touch, please email us at hello@poolside.ai.