https://github.com/sshh12/coding-agents-workshop
Workshop: Optimizing Codebases for Agents — Coding Agents Conference, March 3, 2026
https://github.com/sshh12/coding-agents-workshop
claude-code coding-agents workshop
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Workshop: Optimizing Codebases for Agents — Coding Agents Conference, March 3, 2026
- Host: GitHub
- URL: https://github.com/sshh12/coding-agents-workshop
- Owner: sshh12
- Created: 2026-02-21T19:57:25.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2026-03-01T23:39:37.000Z (4 months ago)
- Last Synced: 2026-03-02T01:34:08.952Z (4 months ago)
- Topics: claude-code, coding-agents, workshop
- Language: HTML
- Homepage: https://html-preview.github.io/?url=https://github.com/sshh12/coding-agents-workshop/blob/main/slides.html
- Size: 5.75 MB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Optimizing Codebases for Agents
[](https://blog.sshh.io/)
[](https://github.com/sshh12)
[](https://x.com/ShrivuShankar)
[](https://linkedin.com/in/shrivushankar)
[](https://sshh.io/coffee-chat)
**Conference:** Coding Agents: AI Driven Dev Conference
**Date:** March 3, 2026
**Location:** Computer History Museum, Mountain View, CA
**Speaker:** Shrivu Shankar (VP AI, Abnormal Security)
> Your agent isn't broken. Your codebase is.
## What This Is
This repo contains the materials for the "Optimizing Codebases for Agents" workshop. It includes a demo app in two versions (before and after optimization), an AI-readiness scorecard, and agent race narrator notes.
## Prerequisites
- A laptop with a development environment
- An AI coding tool installed and authenticated (Claude Code, Gemini CLI, Codex CLI, or Cursor)
- Python 3.10+
- A repository you want to audit (open source or personal). If you don't bring one, you can audit the `A/` demo app.
## Quick Start
```bash
git clone https://github.com/sshh12/coding-agents-workshop.git
cd coding-agents-workshop
```
### Run the "Before" app (Version A)
```bash
cd A
pip install -r requirements.txt
python app.py
# Open http://localhost:8000
```
### Run the "After" app (Version B)
```bash
cd B
pip install -r requirements.txt
python manage.py run
# Open http://localhost:8000
```
### Run tests (Version B only)
```bash
cd B
pytest
```
## Repo Structure
```
coding-agents-workshop/
README.md # You are here
scorecard.md # AI-Readiness Audit (use during the workshop)
race.md # Agent Race narrator notes
slides.html # Workshop slides (speaker notes embedded as HTML comments)
A/ # "Before" -- messy demo app (deliberate anti-patterns)
B/ # "After" -- agent-optimized (same functionality)
```
## Workshop Materials
- **[Slides](https://html-preview.github.io/?url=https://github.com/sshh12/coding-agents-workshop/blob/main/slides.html)** -- Full slide deck (press N for speaker notes, arrow keys to navigate)
- **[scorecard.md](scorecard.md)** -- Score your codebase 0-9 across three dimensions. Bring this up during the audit sprint.
- **[race.md](race.md)** -- Narrator notes for the live agent race demo. Two terminals, same prompt, different codebases.
## Run the Scorecard on Your Repo
You can have Claude Code audit any repo against the scorecard automatically:
> Use web fetch to read https://raw.githubusercontent.com/sshh12/coding-agents-workshop/refs/heads/main/scorecard.md and then spawn tasks in parallel to perform and report an audit of the current repo
Paste this as a prompt to Claude Code inside the repo you want to audit.
## The Demo App
Both `A/` and `B/` implement the same ML Experiment Tracker with dashboard:
- Track experiments (name, description, status)
- Log runs with hyperparameters and metrics (accuracy, loss, latency)
- Compare runs side-by-side with charts
- Dashboard with status badges, metric charts, and activity feed
The difference is how the code is organized. Version A is a realistic mess. Version B is optimized for coding agents.
## License
MIT