The most technically interesting part of this was building a self-improving AI loop Traditionally we think of coding agents as tools to do work faster, but we are quickly moving into a world where async agentic work is fully decoupled from human work This means you can build an AI system that is fully self-improving & can perform experiments and react to results. Based on OpenClaw-style heartbeats, we built a similar system using a bunch of Devin automations: - Calling: Agent dialed restaurants in a morning and an afternoon window on weekdays. - Review: Agent read every transcript afterward and edited the phone agent's prompt. - Idea: Agent once a day, picked one new thing to try. - Webhook: When money or a call came in, an event woke a fifth kind of Devin to handle it. Every ~20 minutes a heartbeat ran in the form of a Devin automation. Each heartbeat is its own Devin session + its own sandbox VM. They all begin by bulling down the "brain" from s3 Read more about the architecture in the quoted article

I didn't respond on Slack for a few days so Devin figured out how to email me ....... Been working with @sandylikesfrogs on a really cool fully-autonomous agent project (that you will find out about soon) but we both got really busy this week. Well Devin kept running every day and kept working but never got any further feedback from us. After sending 6 unanswered Slack messages, Devin apparently found our emails from git commit logs and connected to AgentMail to contact us & get unblocked True holy-shit moment from me

Proud to say that Devin has cracked three more unsolved problems today 1) REFUTED: Graffiti Conjecture 154 (open for ~40 years) 2) PROVED: Graffiti Conjectures 39 & 40 (~40 years) 3) REFUTED: Brandt's Regular Supergraph Problem from West's open problems list (~20 years) My methodology is explained below, but basically I showed Devin the original tweet and told it to find similar problems and crack them. The flood gates are open.

Frankly I think this is the reason Devin is having such a comeback Nobody is really doubting the productivity gains of AI, and I would guess that companies would still be willing to pay the exponential if they must... But token spend is scaled and open source is now really good. It makes sense we are now spending energy to curb the runaway train Extreme high-growth startups are only now thinking about token spend, but this has been an enterprise (read: Publicly Traded Company) concern since day 1 Want to understand how Cognition so quickly grabbed all the big banks and giant Fortune 100 enterprises as customers? Aligned incentives is the answer. 1. Being an independent company Because we are not a model lab with $100B+ raised and $1T+ of data center commitments, we don't need to "catch up" by selling increasingly more expensive tokens Nor do we need to push a specific model family to make margins. Our only calculus is - "Is this the best model for the job?" - "Can we make the user more productive?" - "Can we save the user money?" (increasingly) This comes in the form of post-training research (building cheap + specifically tuned coding models) + new coding evals (FrontierCode benchmarks) + model routing (a lot behind-the-scenes of Devin's cloud harness). You should be skeptical of an Italian restaurant pushing the expensive market price specials. Just like you should be skeptical of a model lab pushing the newest most expensive model 2. Enterprise cost controls As a pre-requisite to selling enterprise contracts to the biggest companies in the world, you need really good spend controls. These banks and big conglomerates have been token-sensitive since day 1. They saw the writing on the exponential. For this reason, Devin has the most complete & robust spend controls of any coding agent on the market. The boring stuff of orgs, users, scopes, limits. But it matters. 3. AI Productivity alignment Cognition has an "AI Productivity Guarantee" That means if Devin delivers less engineering value than you’re paying for, Cognition will fund your usage until it does, up to $10 million. This is the tip of the iceberg and the one thing about Cognition that has been most novel to me since joining. Everything (and I mean everything) in our GTM motion is oriented around ROI. Every conversation is rooted in the actual engineering tickets we are taking off the backlog. I can only imagine what it would be like if instead conversations were rooted in "how can we entice users to burn through tokens"

Huge update.. I joined @Cognition I’m so incredibly proud of what we built at @PromptLayer. Although it feels a little surreal, I know the team is left in amazing hands. I’ll be staying on as an advisor and can’t wait to see where they take it. We started PromptLayer four years ago, and we practically coined the term “prompt engineering”. ChatGPT had come out weeks prior. Nobody knew exactly how LLMs would evolve, but we did know it will completely change the way we build. We were the first developer platform for this new type of builder. Cognition feels like an extension of this vision. Devin is how this new builder will imagine, invent, and create. We're entering the age of software abundance, to steal a term from @scottwu46 Everything is Coding Agents. It’s the single biggest problem in AI. Cognition is one of the fastest growing companies ever. But I think the team is what really sold it for me- it's packed with so many former founders Excited to share more soon...