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Let’s go!
New Devin dropped
Devin for everyone
Introducing Devin 2.0: a new agent-native IDE experience.
Generally available today starting at $20. 🧵👇
Arjun Mishra retweeted
We’re thrilled to welcome Chris Degnan as our Chief Revenue Officer to help us scale globally and build the future of software.
Chris joined Snowflake as its first sales hire. Over the next decade, he scaled alongside the company and grew into Snowflake’s CRO, driving over $3B in ARR and building one of the most iconic sales organizations in tech.
He’s a world-class leader that builds winning teams, executes with relentless rigor, and focuses on what’s right for customers.
We’re also excited to partner with Chad Peets and the RPT team to build Cognition’s GTM team. Chad was Chris’ co-pilot in building Snowflake’s world-class sales team.
Welcome to Cognition, Chris.
I’m super excited to join Cognition as its Chief Revenue Officer.
Going from the 1st sales rep at Snowflake to CRO at a $100b public company was the thrill of a lifetime. Never in my wildest imagination did I think I'd get the opportunity to jump on another rocket ship. Meeting Scott, Russell, and the entire team at Cognition got me so excited to do it again with world-class technology. Hearing how customers spoke about how Devin is transforming their business made me realize this is a once-in-a-lifetime opportunity.
While I am not jumping on as the first sales rep this time, I can’t wait to dive in and help drive amazing customer outcomes while building a world-class sales team. As many of you know, Chad Peets was my co-pilot in building the sales team at Snowflake and my business partner when I joined RPT. There is no world where I could be the best version of myself without Chad. So I am thrilled that Chad and the RPT team will be working closely with me in our pursuit of building a generational company. LFG!!
our customers help make us better every day
we love them
everyone else: dm me
Cognition has crossed $1B in annualized revenue run rate.
This milestone belongs to our customers. Here's how a few of them are building with Devin.
Arjun Mishra retweeted
Be more ambitious
At Cognition, one of our values is to go for it all: when faced with a tradeoff, pick the ambition-maximizing direction.
When we launched Devin in 2024, we envisioned a future where every team had an infinite army of junior engineers. We were early and Devin wasn't good enough.
Now it is! The only constraint left is how ambitious you're willing to be.
colhodm.github.io/FIFA/
Devin shipped FIFA 26 Premier League before i slept a couple of nights ago
if you're still micro-managing a local agent, open your eyes
if devin can make fifa, it can work on your CRUD
colhodm.github.io/AgeOfEmpir…
before I slept, last week I had devin build age of empires.
when i woke up it was done
thats what a cloud agent is for
Broadly this is correct for a few reasons:
1). AI requires much more behavior change than SaaS
2). Agentic Products need to be co-designed with enterprise problems that are extremely nascent i.e how should a cloud agent actually interact with customer dev environments
3). Agents broadly are accelerating product development timelines, which means that the gap between a problem, and the product solving needs to be faster than ever.
4). People buy from people, and if you hire really exceptional people — they also help differentiate the product.
5). Most people are not opinionated enough on the talent of FDEs they hire — if the product and your deployed engineers are the front door of your product, you need to have an exceptionally high bar.
Devin is just so smart
a large part of my early childhood was playing street racer games
Devin made this street racing game for me in 1 hour,
enjoy driving through the marina in a GT3 and having your driver rep ALD while listening to coco-chanel
lfg
play here — colhodm.github.io/gt-sf/
Arjun Mishra retweeted
Here’s a great post on driving down costs, while maintaining high performance, with frontier intelligence as a manager and lower cost models for the workhorse tasks. This will be the template for what model routing looks like in the future.
“We started this experiment expecting to measure how much Fable’s 2x premium would increase cost. We were surprised to find that Fable’s effective delegation actually decreased cost overall. It specified constraints and outcomes instead of spelling out the implementation, gave feedback instead of making fixes itself, and in most cases never touched the code at all. These are the habits of a good manager.”
The industry is increasingly figuring out what it looks like to mix models together to be able to get targeted performance levels and optimal cost structures.
Of course, the only way to get this is to have a deep understanding of the business problem you’re trying to solve and how to effectively route work to different models. If you’re in the applied layer - whether it’s customer support, legal, finance, or coding - this is how your harness will become a core area of differentiation.
I was determined after never having worked at a company for more than a year - to find a sick place to work.
@calvingiroud whose judgement is the best out of anyone I know, had joined a few months before, and told me to chat.
I entered the famed cog house at 12pm and left at 9.
Kept thinking about everyone I met after I got home and how fun it would be to work with them.
Turned out to be true!
Work that by all rights should take months is done in hours by our engineering and sales teams, because we’re like the Yankees - if everyone was Ty Cobb.
Everyone bats .350 here - join our squad
I asked people which companies have the highest density of talented people they know:
1st. Cognition - 9 votes
Equal 1st. Anthropic - 9 votes
2nd. Modal - 5 votes
3rd. OpenAI - 4 votes
4th. Standard Intelligence - 3 votes
4th. Cursor - 3 votes
Two votes each:
- Ramp
- Flapping Airplanes
- DeepMind
- Long Lake
- Applied Compute
One vote each:
- SpaceXAI
- SpaceX (treated separately, one vote was for the AI lab subsidiary and one was for the rocket team)
- American Terawatt
- Mechanize
- Olix
- Fluidstack
- Chai Discovery
- Sail Research
- Etched
- Core Automation
- Specter
- Clay
- Applied Intuition
- Sierra
- Hivemind
- Bitrig
- Retro
- Thinking Machines
- Decagon
- Precigenetics
- Pangram
- Reflect
- Thrive Holdings
- Adaption
Arjun Mishra retweeted
Introducing SWE-1.7, the most capable model we’ve trained yet.
It scores within a few points of the strongest frontier models at a fraction of the cost, and is now available at 1000 tok/s.
RL is not hitting its limit: after refining our recipe, we keep seeing gains as we scale

























