Study Plan
8/5/2026, 5:11:46 PM
A five-module study path (foundations, reflection, tools, evals, planning/multi-agent) with a weekly learn-build-observe-evaluate-reflect routine.
Study Plan
Recommended five-module path
| Phase | Focus | Deliverable | Exit criterion |
|---|---|---|---|
| 1 | Foundations and decomposition | One deterministic multi-step workflow | Trace shows every step and stop condition |
| 2 | Reflection | Draft-critic-revision loop | Paired evaluation beats direct baseline |
| 3 | Tools | Two safe read-only tools | Schemas, validation, errors, and logs tested |
| 4 | Evals and error analysis | Task and component eval suites | Prioritized error table drives a measured fix |
| 5 | Planning and multi-agent patterns | Bounded planning capstone | Budgets, permissions, topology, and regression tests pass |
Weekly routine
- Learn: Read a section and restate the concept without notes.
- Build: Implement the smallest runnable example.
- Observe: Save the complete trace and annotate decisions.
- Evaluate: Run at least five representative cases and one adversarial case.
- Reflect: Record one failure, its earliest cause, and the next experiment.
Design decision sequence
Learning map
Page 1 of 40 in DeepLearningAI > Agentic AI. First page in the series. Continue to "1.1 Course Overview" next. All 37 numbered lesson pages (1.1-5.7) share one template — state, contracts, controls, observability, and evaluation, introduced in full in 1.1 Course Overview — so this page assumes that shape and focuses on what's unique to its own topic.
Get hands-on — step by step
Use the five-phase table to schedule your own pass through this series, then run the weekly learn-build-observe-evaluate-reflect routine for one module before moving to the next.
Top 3 sources
- 1Claude Docs: Prompt Engineering Overview
Anthropic's official guidance on structuring prompts and multi-step model interactions.
https://docs.claude.com/en/docs/build-with-claude/prompt-engineering/overview
- 2DeepLearning.AI Course Catalog
The broader DeepLearning.AI curriculum this study guide's structure is organized around.
https://www.deeplearning.ai/courses/
Links are AI-suggested — worth a quick sanity check before diving in.