The 7-day roadmap / day 2 of 7
Day 2: The Basics.
You'll learn how LLMs, agents, and tools work together: the building blocks of every AI coding assistant. Understanding these basics helps you use and evaluate tools with confidence.
- 7 topics
- 5 practice exercises
- 18 min of reading
- Free, no email
The 7 topics
- 01How Large Language Models WorkTokens, context windows, attention mechanisms, and why LLMs are surprisingly good at code, and where they still fail.TheoryPractice3 resources3 min
- 02Prompt Engineering for EngineersHow to craft prompts that produce consistent, reliable results, and how the same techniques are used offensively to break AI systems.TheoryPractice2 resources3 min
- 03From Autocomplete to AgentsThe evolution from single-turn code completion to autonomous multi-step agents: what defines an agent, how the agentic loop works, and when to use agents versus simpler approaches.Theory2 resources2 min
- 04Building an Agent in 50 Lines of CodeA ground-up look at what an agent really is under the hood: an inference client, a set of tools, and a while loop, using Hugging Face's Tiny Agents as a concrete reference.TheoryPractice1 resource3 min
- 05Memory and State in Agent WorkflowsHow agents retain and retrieve information across steps and sessions: short-term context, long-term memory, and practical strategies to prevent context rot.TheoryPractice1 resource2 min
- 06AI Failure Modes Every Engineer Must KnowHallucination, confident wrongness, context drift, and the foundational security risks that arise when AI agents can take actions in the world.TheoryPractice2 resources3 min
- 07Human in the LoopWhy keeping humans in the decision loop is essential when working with AI agents, and how to design workflows that stay under control.Theory1 resource2 min
What you will watch and read
The roadmap is the shortest route to the ideas in AI-Native Software Engineering (O'Reilly Media). If you would rather work through them with your team, the canvas turns them into a workshop.