10 tips to improve your coding agent game

Effective coding-agent workflows rely on keeping durable, verifiable guidance in repositories rather than chat context, with short, concrete, regularly maintained instruction files supplemented by task-specific files, tests, and hooks. Research cited in the piece suggests that long or stale configuration files can reduce adherence, instructions can be lost during session compaction, and mandatory behaviors such as test execution, secret scanning, or deployment-policy enforcement are more reliable when implemented as deterministic hooks or external gates. It recommends starting fresh sessions rather than transferring flawed transcripts to stronger models, using concise human-written handoff notes, and treating parallel subagents cautiously because they can greatly increase token costs and coordination failures without improving results. The piece also argues for assigning clear interfaces and ownership when delegating work instead of relying on coordinator agents, planning verification before coding, separating code generation from review, and using fresh contexts for reviewers. Finally, it advises committing once current tests pass, avoiding unnecessary revisions that can undo correct work, limiting retries, and applying infrastructure previews and mandatory policies before deployment.

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