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Practical guides on the tools developers use every day — JSON, regex, JWT, cron, and more.
23 posts matching · page 1 of 2
Learn to build a cost-effective AI agent with a minimal loop, tool schema, and guardrails, using open-source models and practical code examples.
Learn why AI agents lose context between tasks and how to fix it with memory, state, and observability patterns.
Learn why LLM context windows are not memory and how to build real persistent memory for AI agents with code examples.
A hands-on guide to choosing and integrating the top 5 AI models for developer agents, with code and config examples.
Learn to choose cost-effective LLMs for AI agents, with a practical routing setup, cost benchmarks, and a working example.
A practical guide to using AI coding agents for production maintenance: setup, guardrails, and a reproducible experiment with real commands.
Learn to stop AI agents from breaking features with sandboxing, guardrails, and regression testing. Includes configs and commands.
Learn practical strategies to stop AI agents from wrecking your git history, with concrete commands and configs you can apply today.
Learn to build a coding agent that runs tests, analyzes failures, and proposes fixes using the ReAct loop with real code examples.
Learn to grant AI agents terminal access safely with sandboxing, permission systems, and audit trails in this practical guide.
Learn where AI coding agents still fail in real workflows, and how to work around their blind spots with concrete commands and configs.
Learn to build an AI agent that writes failing tests before implementation, using a test-first loop with real code examples.