Build a Claude Agent: A Step-by-Step Walkthrough (Building Effective AI Agents)
A linear, copy-paste walkthrough to build a working Claude agent — the loop, tool schemas, robust dispatch, budgets, and tracing, with code and a diagram.
Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
A linear, copy-paste walkthrough to build a working Claude agent — the loop, tool schemas, robust dispatch, budgets, and tracing, with code and a diagram.
How a Claude agent is wired internally — model loop, context store, tool router, MCP layer, and control plane — with a diagram, code, and pitfalls.
A practical guide to fine-tuning large language models for specialized domains including data preparation, training strategies, evaluation, and when fine-tuning beats prompting.
Compare CallSphere and PlayAI for AI voice agents. See features, pricing, compliance, and which platform is better for your business.
A practical guide to implementing observability in LLM applications, covering distributed tracing for multi-step agents, structured logging, cost tracking, quality monitoring, and debugging production issues with tools like LangSmith, Langfuse, and custom solutions.
Bosch deploys agentic AI at the edge to cut HVAC energy costs by 35% while improving occupant comfort. Technical breakdown of edge AI architecture.
Practical cost optimization strategies for production AI agents — from prompt caching and model routing to token budgets and semantic caching that can cut LLM API costs by 50-80%.
Deep dive into Claude Code hooks — pre and post tool execution hooks that let you enforce linting, run tests automatically, validate changes, and build custom CI-like workflows.
Every Claude Code slash command explained with usage examples — from /compact for context management to /review for code reviews and /init for project setup.
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