We're excited to announce a $90M Series C led by @KKR_Co with participation from QRT, @uncorkcap and other existing investors! Learn more: https://t.co/tTb2tqZ5MS
LDX3 London this week. Booth 209. Come talk to us about running AI coding agents on infrastructure you actually control.
Live demo on June 3 at 14:15.
https://t.co/5lvpeIxfX8
Live demo at LDX3 London: running AI agents securely in self-hosted infrastructure. Controlled execution, access management, infrastructure boundaries.
June 2, 13:10.
https://t.co/TYhcmRWreQ
On the ground at Open Source Summit NA. Nicky Pike on stage today: what happens when your AI agent has keys to production. Come find us. https://t.co/zOoxWF0ySY
At Open Source Summit NA next week. Nicky Pike is presenting on governance patterns for AI agents in production. Come find us in Minneapolis, May 18-20. https://t.co/zOoxWF0ySY
A lot of people ask us "how does it actually work?"
So we built something to answer that properly.
The Coder Architecture Explorer shows exactly where Coder fits into your infrastructure.
This is how teams like Anthropic set up cloud dev environments.
https://t.co/58Zzr6lqz2
Getting AI coding agents into a secure cloud environment shouldn't take longer than training the model did. May 27, 2 PM ET: hands-on workshop with Carahsoft + AWS. Deploy Coder on EKS, build agentic workflows with Bedrock, leave with a working setup.
https://t.co/mpygCYo1BI
Every enterprise hitting scale with AI agents runs into the same three bottlenecks. CI/CD. Team structure. Role definition. All predictable. All solvable. May 20 with David Fraley. https://t.co/F9ue3y8dAj
Updated: deploying governed AI coding agents on Red Hat OpenShift with workspace isolation and full audit trails. Come find us at Red Hat Summit this week. https://t.co/d8o8T7vCs0
AI adoption worked. Now your CI/CD is buckling, team structures are misaligned, and senior engineers are directing agents instead of writing code. David Fraley maps the predictable failure modes, May 20. https://t.co/F9ue3y8dAj
The agent loop runs in the coderd control plane.
It reads, writes, edits, and executes inside workspaces the same way a developer would.
The workspace itself doesn't know AI is involved.
Coder Agents separates how agents run from which models they use.
Platform teams centrally control models, prompts, MCPs, and skills.
Developers get a chat interface and an API.
Most agent tools are tightly coupled to a single provider. Pick one and you're locked into its models, its ecosystem, its workflow patterns. That gets expensive to undo at scale.
Coder Agents is self-hosted, model agnostic, and open source, giving you flexibility without lock-in
Coder Agents is now in beta!
A native agent that runs in the control plane, not inside the workspace. Workspaces only spin up when compute is actually needed.
Try it on your infrastructure - zero usage limits through September:
https://t.co/r8yrdTSvNz
Token usage. Model switching. Task completion velocity. Cost-to-value ratios. These are the metrics enterprises are tracking as AI agents enter the SDLC. Simon Gregory, UST AI Innovation Forum.
"I violated every principle I was given." That was the AI agent's response after deleting a production database in 9 seconds. The model wasn't the problem. The environment was. https://t.co/x9mLjC8vEG
"Because of the speed at which AI performs its tasks, you've got to be as close to the point of problem as you can. It can't be two hours, a day, two weeks later." AI observability is moving down the stack.
"For the unregulated teams, it's a free for all. At some point they're going to get to becoming regulated, there is no doubt." Simon Gregory on why governance infrastructure is a when, not an if.
AI coding agents on hardened Kubernetes without elevated permissions or custom SCCs. Coder on Red Hat OpenShift: process-level agent firewalls, centralized model governance, full audit trails.
https://t.co/W77X8N0B2f