Prefer an API or purpose-built connector when it exposes the required operation with clear identity, scoped access, and a result …
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Latest in AI & Agents
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An agent run needs independently enforced limits on how much work it may start, how long it may continue, and …
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Put human checkpoints where a decision changes the consequences of the work: sending information, changing permissions, spending money, publishing, or …
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An MCP server gives an AI application a standardized interface to specific data and operations. It can expose a document, …
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Use one agent when the task requires a continuous understanding of shared state or frequent decisions across the same files. …
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A tool should make three things clear after a failure: what it understood, what effects are known to have happened, …
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Evaluate a coding agent on representative tasks from your repository, starting each attempt from a recorded state and grading the …
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Use a script when you can specify the operations and the rules for choosing between them. Use a coding agent …
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A coding-agent workflow should carry a defined problem through reproduction, a bounded change, verification, and review. At every transition, preserve …
AI tools and agents for the work of building software. Explore coding assistants, agent workflows, tool integrations, and ways to evaluate their output. Our focus is on choosing useful capabilities, understanding their limits, and deciding where human judgment belongs—from a single development task to automation across a repository.