ClinchWorks
Explore a subject, work through the curriculum, and choose your next step.
Use orchestration frameworks only after understanding the underlying LLM and retrieval primitives. Expanded engineering lessons with worked examples, runnable local practice, failure investigation and evidence-based assessment.
Build explicit, stateful agent workflows with routing, loops, persistence, and human control. Expanded engineering lessons with worked examples, runnable local practice, failure investigation and evidence-based assessment.
Rebuild Linux and Bash fundamentals through safe local exercises, practical incident reasoning, and a complete fixture-based diagnostic automation capstone. Designed for experienced DevOps learners who want dependable command-line and scripting foundations.
Build a practical foundation in LLM application engineering through twelve detailed lessons, local Python exercises, a complete evidence-based assistant capstone, and twenty scenario assessment questions. Learn prompting, structured outputs, retrieval, agents, state, evaluation, adaptation choices, inference economics, and production design without requiring paid model calls.
Serve models through reliable APIs with streaming, batching, monitoring, and sensible deployment boundaries. Actual count-based generation and serving state transitions plus optional HTTP and model-runtime integration. Includes detailed lessons, worked solutions, failure injection, independent challenges and instructor assessment.
Run, inspect, benchmark, and engineer local LLM inference workflows. Includes detailed lessons, worked calculations, a complete offline reference project, debugging exercises, optional real-tool workflows and separate instructor assessment.
