Jon Turow

Builder. Partner at Madrona Venture Group. Former Amazon AWS.

[Jon Turow @jturow]

@CarinaLHong and @byroncook had so much wisdom to share here. Most of the industry agrees there’s a ceiling “somewhere” in how sophisticated reasoning models can become with our current technical approach. Byron and Carina are pushing hard on one of the best vectors around to crash through that ceiling.

[Madrona @MadronaVentures]

As models move beyond copilots into systems that operate independently, a new question starts to matter more than ever: How do we know an answer is actually correct?

In this live episode of Founded & Funded, @axiommathai's @CarinaLHong and @awscloud's @byroncook sit down with @jturow to explore what happens when AI moves into domains governed by objective truth: systems like infrastructure, security, finance, and science, where correctness is foundational, not optional.

The discussion looks at a powerful shift underway:
🔹How learning systems and formal verification are 🔹beginning to converge
🔹Why reasoning, not just generation, becomes the bottleneck at scale
🔹What changes when AI can prove its work, not just produce it
🔹How agentic workflows become more capable 🔹when verification is built in
🔹Why this unlocks entirely new categories of applications

This isn’t a critique of today’s models. It’s a view into what comes next as AI takes on more responsibility and higher-stakes work.

For founders building toward that future, this is a conversation worth spending time with. Watch/Listen wherever you get your podcasts: https://t.co/xXIVMJnx2N

[Jon Turow @jturow]

What a great evening of technical conversations about the future of AI reasoning with @axiommathai @BCapitalGroup and @MadronaVentures.

To anyone who thinks formal verification is a far away sci fi tale, it’s happening right now.

[Carina Hong @CarinaLHong]

People mountain people sea!!!

Our Verified Reasoning event at Neurips is a huge success - thank you for everyone for coming! We are here till 7pm!

And especially thank you for the 300-400th people on the waitlist! Come at 6pm to Shorebird anyways 😆

[email protected]

It is very clear that this is the future, and Axiom is honored to pave the way forward.

[Carina Hong @CarinaLHong]

AxiomProver keeps getting stronger.

And @axiommathai keeps growing.

I'm excited to share that Prof. Ken Ono @KenOno691 has joined Axiom as Founding Mathematician and FTE #15.

He left his tenured position as STEM Advisor to Provost at UVA to build an AI mathematician with us.

Here's Ken's story. (1)

[Jon Turow @jturow]

@CarinaLHong and Axiom have a bold, fresh and exciting approach to AI reasoning. Plus one of the most talent dense early teams I have seen. And now we’re thrilled to welcome @KenOno691, UVA’s Marvin Rosenblum Professor of Mathematics and one of the most cited number theorists globally, to Axiom.

https://t.co/VAGiyTOvNr

[Carina Hong @CarinaLHong]

I had the pleasure of chatting with @TheTuringPost about all things Axiom and AI4Math!

Tune in:

- How I define AGI vs domain specific ASI, the plate metaphor, can a chatty or poetic model prove the Riemann Hypothesis, and math’s incredible transfer learning power to coding and engineering

- Why an AI mathematician needs both proofs and constructions capability, mapping to the two branches of Axiom: formal proving, and specialized discoveries

- Data scarcity compared to code, the chicken-and-egg problem of autoformalization, Axiom’s bold synthetic data bets, and how we think about new knowledge generation

- Problem-Solving vs Theory-Building, why "Theory Building" is harder to benchmark than the International Math Olympiad (IMO), and why literature search / retrieval, so emphasized by LLMs today, is unsatisfying

https://t.co/HxRoCSOa2S

[Brian Zhan @brianzhan1]

There are roughly 1,100 problems in the Erdos canon, compiled from decades of papers. They've guided serious research in combinatorics and number theory for generations. Of those 1,100, only 266 have ever been proved. And only 10 have proofs fully formalized in Lean.

Axiom just added two more to that list of 10.

Problem #124 is an additive number theory question about representing integers as sums of powers across multiple bases. It stayed open for ~30 years.

Problem #481 is even older, from 1980. It asks whether a certain iterated arithmetic process must eventually produce a repeated element. Deceptively simple to state, but Erdos and Graham themselves wrote that it was "surprising" how difficult it turned out to be. Open for 45 years.

A few weeks ago, OpenAI claimed GPT-5 solved Erdos problems, only for the community to point out it had just retrieved existing literature.

Axiom actually solved it, with Lean that checks proofs down to foundational axioms. Every step must type-check. There's no hand-waving.

Axiom is late to the game, with a fraction of the resources, and they're producing proofs that major labs aren't able to solve.

[Jon Turow @jturow]

If you care about the next frontier of reasoning — not just faster LLMs, but systems that formalize, prove, and conjecture — Axiom is building it.

An invitation to work on the hard, beautiful problems.

A key piece is construction-driven discovery: the examples that seed conjectures, guide proof strategies, and surface structure we don’t yet understand. Axiom’s new post describes their tools for this — PatternBoost, Int2Int, and early mathematical world models.

[Carina Hong @CarinaLHong]

Introducing Axiom’s discovery team, led by @f_charton:

We build models that will create novel constructions, map problems into solutions and intuitions, and learn the structure of entire mathematical worlds.

Built to attack hard open problems, one at a time.

[Jon Turow @jturow]

@art_of_philo @CarinaLHong @axiommathai Cool story bro.

[Jon Turow @jturow]

@art_of_philo @CarinaLHong @axiommathai Will leave this here for posterity, for when you claim you didn’t say it. Cheers.

[Jon Turow @jturow]

@art_of_philo @CarinaLHong @axiommathai Your second post in a row with no claims. Same info density as the rest of your feed. Cool story bro. Take care.

[Jon Turow @jturow]

@art_of_philo @CarinaLHong @axiommathai Math proofs are not remotely just algorithms! They contain rigorous logical thinking.

[Jon Turow @jturow]

Let's go!

[Jon Turow @jturow]

98% error reduction. Built-in production backends. Frontier AI agents, zero CLI.

Dental offices building patient portals. Sales teams spinning up custom CRMs. Domain experts creating tools that would've needed dev teams last year.

Software creation, democratized. Congrats @stackblitz team

[bolt.new @boltdotnew]

Today vibe coding goes pro.

Introducing Bolt v2:

→ World's best agents (Claude Code, Codex)
→ Built in backend (hosting, DB, storage, ...)
→ No error loops, no setup nightmares

Now anyone can build without boundaries.

[Carina Hong @CarinaLHong]

Today, I am launching @axiommathai

At Axiom, we are building a self-improving superintelligent reasoner, starting with an AI mathematician.

[Jon Turow @jturow]

@oanaolt @oanaolt so great to have you there. Let’s go!!

[Jon Turow @jturow]

Huge congrats to @CoolestAK87, Idan, Barak.
Thrilled to support you on this journey along with our friends at @AmexVentures, @VisaVentures, @pk_iv, @shyamalanadkat, and @theaievangelist

More here → https://t.co/yOcn5pU3Aq

[Jon Turow @jturow]

AI agents are already driving real economic activity — Visa reports a 1,200% YoY spike in retail traffic from agents.

But agents aren’t like bots — they are bots.
And payments infra isn’t ready.

That’s why we backed @nekuda_ai: the trust layer for agentic commerce.

🧵👇

[Jon Turow @jturow]

We believe agents must become trustworthy before they can become trusted.

And when they are, they’ll stop being demos — and start contributing to GDP.

Nekuda makes that future happen faster.