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intermediateTechnical AI
Building Your First Production AgentA hands-on course for engineers who already call LLM APIs and want to ship a tool-using agent that survives production: recovering from failed tool calls, capping runaway spend, extending itself with an MCP server, passing task-completion evals, and deploying with logging enabled.
Matching modules
7 modules- Module 1Why LLM Outputs Break: Understanding Prompt Driftin Evaluating LLM Output Quality · 3 lessonsai-for-engineersai-for-product-managersai-for-data-analystsprompt-engineeringai-evalsquickfoundational
- Module 2Structured Output as a Contractin Evaluating LLM Output Quality · 3 lessonsai-for-engineersai-for-data-analystsprompt-engineeringai-evalsquickfoundational
- Module 1Start Herein How to Tell If Your AI Is Any Good · 1 lessonai-for-leadersai-evalsquickfoundational
- Module 2Reading the Benchmark Landscapein How to Tell If Your AI Is Any Good · 3 lessonsai-for-leadersai-evalsquickfoundational
- Module 3From Score to Production Signalin How to Tell If Your AI Is Any Good · 3 lessonsai-for-leadersai-evalsquickfoundational
- Module 4Interrogating the Vendorin How to Tell If Your AI Is Any Good · 4 lessonsai-for-leadersai-evalsquickfoundational
- Module 3How Agents Fail in Productionin What an Agent Actually Is (and What It Cannot Do) · 4 lessonsai-for-product-managersai-for-leadersai-for-foundersagentic-aiai-evalsresponsible-aiquickfoundational