Exercise 1: First Session¶

Duration: 15 min | Module: 1 — SDLC Productivity

Objective¶

Launch agy-cli, explore a codebase, and create an AGENTS.md that makes every future session smarter.

Setup¶

You need a Git repository to work with. Use the sample app in this repo or bring your own:

# Option A: Use this workshop repository (you're already here)
# No need to cd — just start agy from the repo root

# Option B: Use any of your own Git repos
cd /path/to/your/project

Part 1: First Interactive Session (5 min)¶

agy

At the prompt, ask:

> What does this project do? Give me a one-paragraph summary.

Then follow up:

> What are the top 3 files I should read to understand the core logic?

> Are there any obvious code quality issues or tech debt?

Notice: agy read your files without you having to specify them. It indexed the git repo automatically.

Part 2: Deep Dive (5 min)¶

Pick one file from agy's suggestions and go deeper:

> Explain [filename] in detail. Walk me through what each function does and how they connect.

> If I wanted to add [a simple feature], where would I start?

Part 3: Create AGENTS.md (5 min)¶

Now codify what you've learned so every future session starts with context:

> Based on our conversation, generate an AGENTS.md file for this project. Include: project purpose, tech stack, key conventions, and anything I should tell an AI assistant before asking it to modify this code.

Review what agy generates. Edit it if anything is wrong. Then write it:

> Write that AGENTS.md to the project root.

Start a new session and verify it works:

agy --print "What do you know about this project?" --print-timeout 30s

Completion Criteria¶

[ ] agy launched and responded in interactive mode
[ ] Explored at least 3 follow-up questions
[ ] AGENTS.md exists at the project root
[ ] agy --print "What do you know about this project?" returns accurate info