The agent-native software factory
Guides on building, governing, and scaling an agent-native software factory, plus write-ups of the podcasts and talks behind the ideas.
Software Factory
Inside the software factory, and what it takes to build one
A software factory is a managed model for producing software with repeatable inputs, standardized tooling, and measurable output. The model is increasingly agent-native, with development agents handling execution across the SDLC. Chainguard, Groq, Empower, and Nav run theirs on Factory.
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Testing
Accessibility testing with coding agents
Accessibility testing with coding agents combines deterministic scans, keyboard flows, semantic inspection, and human review. Build useful evidence into every UI change.
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Guides
Agent readiness: fix the repos slowing your rollout
Use agent readiness to find the repositories blocking an AI rollout, prioritize fixes, and measure progress with Factory’s reports and dashboard.
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AI Coding Agents
Agent readiness can cut repeated token work
Agent readiness exposes avoidable setup, search, and validation work. Connect repository improvements to token efficiency without inventing a savings benchmark.
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How to write an AGENTS.md file
Write an AGENTS.md file with verified commands, clear scope boundaries, and useful completion checks. Test the instructions on a small task before expanding them.
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Agent Governance
AI agent controls for private development networks
AI agent controls for private networks need enforceable permissions, sandboxing, managed model policy, and review gates. Build a testable policy for Droid.
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API Development
Protecting API compatibility with coding agents
API compatibility checks help coding agents change services without surprising consumers. Compare contracts, trace callers, and validate old and new behavior.
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Enterprise AI
Model routing has to account for the warm cache
Model routing can lose its price advantage when a switch discards cached context. Factory’s research explains why task state belongs in the decision.
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Governance
Audit trails for coding agent changes
A coding agent audit trail connects identity, intent, tool activity, validation, review, and deployment. Learn what evidence to retain without collecting unnecessary data.
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Enterprise AI
Context compaction must preserve the next step
Context compaction should preserve decisions and file state, not just shrink a transcript. Factory’s published study shows what to test after a long coding session.
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Platform Engineering
Safer database migrations with coding agents
Database migrations with coding agents need staged schema changes, compatibility tests, rollback evidence, and human approval without hiding operational risk.
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Software Supply Chain
Safer dependency updates with coding agents
AI dependency updates need more than a version bump. Scope compatibility work, inspect transitive changes, run focused tests, and keep every update reviewable.
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