Moritz Stephan

Scheduled agents from @DevinAI allow you to automate repetitive tasks like daily reports, periodic code maintenance, routine data analysis, and more. Choose your agent: an AI engineer, a data analyst, or a session auditor. The agent has access to repo context, knowledge bases, playbooks, databases, Sentry, Datadog, Slack, Notion, Figma, +++ - no infrastructure or scripting required. Some jobs we see users running: - Automating daily Sentry error fixes overnight - Posting weekly PR changelogs to Slack and docs - Posting Daily Datadog error scans to Slack - Runing Nightly E2E Tests on Staging - Automating weekly dependency updates with PRs - Posting weekly PR summaries to Notion docs.devin.ai/product-guides…

I’ve joined @Cognition to lead Design and build out their Design team. The Windsurf and Devin you know of today is about to get exponentially better. Look forward to 2026 because we’re reshaping everything.

Introducing Codemaps in @windsurf! powered by SWE-1.5 and Sonnet 4.5 “Your code is your understanding of the problem you’re exploring. So it’s only when you have your code in your head that you really understand the problem.” — @paulg

Today we’re releasing SWE-1.5, our fast agent model. It achieves near-SOTA coding performance while setting a new standard for speed. Now available in @windsurf.

Generalists are useful, but it’s not enough to be smart. Advances come from specialists, whether human or machine. To have an edge, agents need specific expertise, within specific companies, built on models trained on specific data. We call this Specific Intelligence. It's what we're building at Applied Compute. We unlock the latent knowledge inside a company, use it to train custom models, and deploy an in-house agent workforce that reports to your team. We work with sophisticated companies that have already captured early gains from general models, like @cognition, @DoorDash, and @mercor_ai. They’re pulling even further ahead with proprietary in-house agents that don’t need to wait for the next public model release. Together, we are building and validating models and agents in days instead of months, achieving state-of-the-art performance on customer evals. Our team has high density and low latency. Our founders all worked on different parts of this problem while they were researchers at OpenAI — @ypatil125 as a key member on the agentic software engineer effort (Codex), @rhythmrg as a core contributor to the first RL-trained reasoning model (o1), and @lindensli as a core contributor on ML systems and infrastructure for RL training. Two-thirds of the team are former founders, and everyone brings a deep technical background, from top AI researchers to Math Olympiad winners. We are backed by $80M in funding from Benchmark, Sequoia, Lux, Elad Gil, Victor Lazarte, Omri Casspi, and others. With their support, we are growing the team, scaling deployments, and bringing to market the first generation of agent workforces built on specific models. In short: 1. We are building Specific Intelligence for specific work at specific companies. 2. That will power in-house agent workforces to support their human bosses. 3. That in turn will unlock AI’s full potential through humanity’s greatest engine of progress: thriving corporations in a free market.