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Making Our Monorepo Ergonomic for Agents
Basis successfully refactored its monorepo in three months to be "ergonomic" for code agents, using principles like verifiability and canonical context, unlocking substantial payoffs.
What: The company Basis spent three months making its monorepo ergonomic for code agents, discovering that the process is more complex and less intuitive than expected, but yields significant benefits by addressing agents' unique failure modes and context requirements. They achieved this by applying principles such as verifiability, interoperability, and canonical context.
Why it matters: As AI code agents become more prevalent in development workflows, this experience from Basis highlights a nascent but critical area of "agent-native" software engineering, suggesting that traditional repository structures and practices will need re-evaluation to maximize AI productivity.
Takeaway: Software engineering teams exploring code agents should anticipate significant effort in adapting their monorepo structures, focusing on making code bases verifiability, interoperability, and providing canonical context for agents.
Decoder
- Monorepo: A single repository containing multiple distinct projects, often with shared code and dependencies, managed by a single team or organization.
- Code agents: AI systems designed to understand, write, debug, and refactor code, often operating within a developer's workflow or directly on a codebase.
- Ergonomic (for agents): Designed to optimize the efficiency and minimize the errors of AI code agents when interacting with a codebase, considering their unique needs for context, structure, and verifiability.
Original article
Code agents have their own failure modes, appetite for context, and demands on what counts as a well-organized repository. Companies need to take this seriously as the work to make a repository ergonomic for agents is bigger than expected, and the principles are non-obvious. However, the payoff is substantial. This article looks at how Basis made its codebase ergonomic for agents in three months using principles rooted in verifiability, interoperability, and canonical context.
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