Introducing Devin Security Swarm
A more cost effective and accurate way to find security vulnerabilities in complex codebases, based on a new architecture: Agentic MapReduce.
Conventional model routing sucks. It passes benchmarks but fails to write code you'd actually merge.
Introducing Devin Fusion, a new hybrid-model harness for agentic coding.
In testing, it reduces the cost of Fable-level intelligence by 35% and still feels good to use.
Measuring someone's productivity by their token usage is a horrible idea. Giving everyone the same fixed token budget isn't much better. So what's the right way to roll out AI across your org?
We built a system to measure how many productive engineering hours every Devin task is worth, validated against a dataset of real engineers’ times estimates. The goal is to answer the fundamental question that companies are grappling with: how much real value are you getting from each of your agent sessions?
On top of that, we're giving an AI productivity guarantee! Now if Devin delivers less engineering value than you're paying for, we fund your usage until it does.
The whole industry needs to move from measuring activity to measuring output. We hope to see more AI companies taking this approach.
Standalone IDEs have about 6 months left to live. An interface for manually editing and refactoring doesn’t need to exist if you're not manually editing and refactoring anymore.
So what's the right interface for a dev to be working in for 8h / day? Some parts are obvious: you want to be able to spin up agents (either local or cloud agents) and to have a clean interface to keep up with all of your parallel running agents. Then you want to be able to get into the weeds whenever needed for last-mile fixes and review.
But as software engineering continues to evolve we will see more and more of the lifecycle get reinvented. How do you build a single surface that allows you to plan, spec, prototype, debug, review, QA?
Bringing Devin and Windsurf together has been our vision ever since the acquisition. Devin Desktop is our first shot at what this looks like. Excited to make this a reality today!
Reinforcement learning has exploded on Modal, and we've been cooking.
Here's a review of lessons learned helping teams train at scale, the patterns we kept seeing, and an open-source library to get started with RL on Modal quickly.
1/ We’ve raised over $1B at a $26B valuation, led by @Lux_Capital, @generalcatalyst, and @8vc.
Our enterprise usage has grown >10x since the start of this year, and our run-rate revenue grew to $492 M.
We launched Devin two years ago as the first AI software engineer. Since then, cloud agents have gone from niche to mainstream, and today they are the fastest growing way to create software.
We're honored to deepen our partnership with @modal and co-lead their $355M Series C!
When @bernhardsson and @akshat_b started Modal in 2021, they had conviction that building a truly great cloud for AI meant rebuilding the entire stack from the ground up. Five years later, that bet has paid off.
Erik built the recommendation system behind Discover Weekly at Spotify. Akshat was an early engineer at Scale AI before joining Erik as co-founder and CTO. Together, they've assembled what one engineer affectionately calls "a monastery for super nerds" and it shows in the product.
Modal has become the high-performance cloud that serious AI teams reach for when they need to ship. We couldn't be more excited to continue backing them.
Huge congratulations to Erik, Akshat, and the entire Modal team!