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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.
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8 modules- Module 3Failure-Resilient Agent Loopsin Building Your First Production Agent · 4 lessonsai-for-engineersagentic-aiai-evalsworkflowsquickintermediate
- Module 6Evaluation for Task Completionin Building Your First Production Agent · 3 lessonsai-for-engineersai-for-data-analystsagentic-aiai-evalsquickintermediate
- 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 3Corrective Retries: Recovering from Validation Failuresin Evaluating LLM Output Quality · 3 lessonsai-for-engineersai-for-data-analystsprompt-engineeringai-evalsworkflowsquickintermediate
- Module 4Measuring What Matters: Evaluation Metricsin Evaluating LLM Output Quality · 4 lessonsai-for-engineersai-for-product-managersai-for-data-analystsprompt-engineeringai-evalsquickintermediate
- Module 5Putting It Together: A Production-Ready Evaluation Pipelinein Evaluating LLM Output Quality · 3 lessonsai-for-engineersai-for-product-managersai-for-data-analystsprompt-engineeringai-evalsworkflowsquickadvanced
- Module 2LLM Evaluation (Evals): Building Rigorous Testing Pipelinesin LLM Guardrails, Evals and Agentic Memory · 4 lessonsai-for-engineersai-for-data-analystscontext-ragai-evalsquickintermediate