Your AI agent just fixed your CI without leaving the terminal
Claude Code + CircleCI MCP = no more hunting through build logs.
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Cut CI Environment Setup Time in Half with Chunk sidecar Snapshots
Waiting minutes for CI feedback while you're building with AI agents kills your momentum. Chunk sidecars snapshots let you freeze your environment after setup, so every boot skips the install and starts from a cached state instead of scratch. In this tutorial, we demo how to set up Chunk sidecars, snapshot it, and boot from that snapshot. We also benchmark the difference: a cold sidecar start took 45 seconds. Booting from the snapshot took 12 seconds. That's 30+ seconds saved on every run, multiplied across every developer, branch, agent, and session.
Intent Debt: The Hidden Cost of AI-Generated Code
When AI writes the code and something breaks, nobody knows what it was supposed to do.
How to Set Up Claude Code with CircleCI MCP Server (Full Demo)
AI agents write code fast, but without a validation layer, fast just means faster bugs. In this video, we connect Claude Code to the CircleCI MCP server so Claude can trigger pipelines, pull build failures into context, and iterate until everything is green. No context switching. No copy-pasting logs.
Most Engineers Explain Ideas Backwards
Technical proposals can be like campfire stories. You start at the beginning, walk through every discovery & technical detail, and eventually arrive at the point. The problem? By then, you've lost the audience.
ACP vs MCP: What's the difference for agentic coding?
An AI coding agent holds many conversations at once. Not only is the user prompting it, the agent also talks to the IDE, showing diffs and asking before it touches a file. At the same time it talks to tools, pulling a failing build or querying a database. Two open protocols standardize those conversations. This guide compares ACP vs MCP in practical terms: what each protocol does and when each applies. ACP (Agent Client Protocol) connects a code editor to an AI coding agent.
Waiting Is Expensive for AI Agents
Same repo. Same tasks. Same validation gates. The only difference? Where validation happened. Here's how Chunk sidecars returned feedback in 22 seconds versus about 69 seconds through a traditional CI pipeline, giving the agent enough time to catch the failure, fix it, and revalidate before pushing.
Your AI App Passed the Vibe Check. Now What?
Run a few prompts. Looks good. Ship it. According to Laurie Voss, that's still how a surprising amount of AI software gets tested.
What Every ERG Leader Learns
People want to support your community. Sometimes you just have to invite them in.
What is mutation testing?
A test suite can be all green and hit 100% line coverage and still miss bugs. Coverage measures which lines ran during the tests, not whether the assertions actually caught a defect. A test that calls a function but never checks the return value still counts toward the coverage number. The bug it would have prevented still ships.