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.
Within AI Coding Agents
AI Coding Agents
Security
Session cookie tests for coding agent changes
Session cookie testing for coding agent changes verifies scope, transport protections, expiration, rotation, and logout behavior across application routes.
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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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Infrastructure
Safer infrastructure as code changes with agents
Infrastructure as code changes need plan evidence, policy checks, and controlled application. Learn how coding agents can prepare reviewable cloud changes.
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Enterprise AI
Fast inference changes the coding-agent workflow
Evaluate fast inference for coding agents across providers and gateways. Compare response latency, model compatibility, cost, and time to a validated result.
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Software Delivery
Cross-repository coding agent coordination
Cross-repository coding agents need explicit dependency order, isolated workspaces, compatible changes, and release evidence. Use this plan for coordinated updates.
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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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Security
Keeping test data private with coding agents
Test data privacy for coding agents requires approved fixtures, restricted access, and checks that prevent sensitive records from entering prompts, logs, or commits.
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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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Enterprise AI
Droid vs Devin for enterprise engineering workflows
Compare Droid vs Devin for interactive coding, delegated multi-step work, and review handoffs. Separate saved instructions, persistent compute, and model configuration.
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Guides
Token efficiency starts with smaller tool results
Improve token efficiency by controlling tool output, search scope, and repeated context. Use Factory’s existing measurement and harness resources to test the result.
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Developer Experience
Coding agents in monorepos, with clear boundaries
AI coding agents in monorepos need explicit package boundaries, local instructions, dependency graphs, and affected tests. Make large repositories easier to change safely.
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Maintenance
Removing stale feature flags with coding agents
Feature flag cleanup requires proof that a flag is stale. Coding agents can remove the obsolete branch and evaluation call while testing the permanent behavior.
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