CI/CD for coding agents: when validation becomes the bottleneck

About this episode

Coding agents write code faster than ever, and the bottleneck in shipping software has moved to validating it. A 15-minute build gives an agent 4 feedback cycles an hour. A 5-minute build gives it 12. Romain sits down with Dan Manges, co-founder and CEO of RWX and former CTO of Braintree and Root, to talk about what CI/CD looks like when agents are the main users, and how the rest of the software development lifecycle has to change with it. Key topics covered: - Why traditional CI/CD pipelines slow down coding agents - Graph-based execution and content-based caching, compared to Docker's lineage-based caching - A CLI-first workflow: run CI against local changes without committing or pushing, and get a green PR check right away if the agent already ran it - Sandboxes for the agent's inner loop, MCP, semantic outputs, and retrying only the failed tests - Building RWX on AWS: a distributed container runtime with no image build and push, a hot pool of EC2 M8a instances, single-tenant VMs, and self-hosted runners in customer VPCs - Rethinking the SDLC from first principles: give agents the context to get it right, throw code away and fix AGENTS.md instead of iterating - Software factories for internal tools versus human review for mission-critical code - Turning large changes into reviewable work by building the whole change first, then extracting shippable pieces - Guardrails for agent-driven changes: CloudWatch, gradual rollouts and feature flags - Results: pipelines about 2x faster on average, and about 35% lower cost - Is infrastructure as code still necessary? Chapters: 00:00 Rethinking engineering for AI agents 00:52 Meet Dan Manges and his engineering journey 02:59 Why traditional CI/CD becomes a bottleneck 05:34 Faster feedback loops for coding agents 08:02 Graph execution and content-based caching 13:19 A CLI-first, agent-native CI workflow 15:33 Unifying agent development and CI environments 17:45 Building RWX on AWS 21:33 Rethinking the SDLC for agents 24:33 When humans should review agent code 27:07 Giving agents the context to get it right 29:29 Sharing agent skills and team practices 35:50 Building software factories with agents 40:32 Turning large changes into reviewable work 46:20 Guardrails for safe agent-driven changes 48:06 Measuring CI speed, cost, and agent benefits 51:10 Signals your CI pipeline needs rethinking 54:02 Is infrastructure as code still necessary? 56:38 Closing thoughts and recommendations

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