# Quick Wins Implementation Plan - This Week

**Goal**: Make immediate, high-impact improvements to move toward top 0.1%
**Timeline**: 5 days
**Total Time**: ~13 hours

---

## Day 1: Demo GIF (Most Critical) 🎬

**Time**: 2-3 hours
**Impact**: VERY HIGH - This is the #1 converter

### Step 1: Prepare Demo Session (30 min)

```bash
cd /home/nistrator/Documents/github/amplifier/ai_working/agent_debugger

# Ensure you have a good demo session
python scripts/seed_demo_sessions.py

# Start the server
peaky-peek --port 8000
```

### Step 2: Record Screen (1 hour)

**Use**: `peek` (Linux), `kap` (Mac), or `screenToGif` (Windows)

**Script to follow**:
1. Open browser to `http://localhost:8000`
2. Show session list (2 seconds)
3. Click a session with failures (1 second)
4. Show timeline view (2 seconds)
5. Click failure event → show details (3 seconds)
6. Click "Decision Tree" tab → expand reasoning (5 seconds)
7. Click "Replay" button → show time-travel (5 seconds)
8. Show failure cluster panel (3 seconds)
9. End on success/insight moment (2 seconds)

**Total**: < 30 seconds

### Step 3: Edit & Optimize (30 min)

- Add text overlays: "See Why", "Replay Failures", "Find Patterns"
- Cut dead time
- Optimize to < 5MB
- Save as `docs/assets/demo-30s.gif`

### Step 4: Update README (15 min)

```markdown
# After the headline, add:

![Peaky Peek Demo](./docs/assets/demo-30s.gif)

**See why your AI agent did that. In 30 seconds.**
```

**Commit**:
```bash
git add docs/assets/demo-30s.gif README.md
git commit -m "docs: add 30-second demo GIF showing core workflow"
git push
```

---

## Day 2: Landing Page Deployment 🚀

**Time**: 3-4 hours
**Impact**: HIGH - Enables discovery

### Execute Existing Plan

The plan is already complete in `docs/superpowers/plans/2026-03-23-landing-page.md`

**Quick execution**:

```bash
cd /home/nistrator/Documents/github/amplifier/ai_working/agent_debugger

# Step 1: Create nojekyll
touch docs/.nojekyll

# Step 2: CSS already exists at docs/style.css (verify it's there)
ls -la docs/style.css

# Step 3: HTML already exists at docs/index.html (verify it's there)
ls -la docs/index.html

# Step 4: Test locally
cd docs
python -m http.server 3000
# Open http://localhost:3000 to verify

# Step 5: Commit and push
git add docs/.nojekyll docs/style.css docs/index.html
git commit -m "feat: add landing page for GitHub Pages"
git push

# Step 6: Enable GitHub Pages
# Go to: https://github.com/acailic/agent_debugger/settings/pages
# Source: Deploy from branch
# Branch: main
# Folder: /docs
# Save
```

**Verify** at: `https://acailic.github.io/agent_debugger/`

---

## Day 3: Improved README Positioning 📝

**Time**: 1-2 hours
**Impact**: HIGH - First impression

### Create New README Hero Section

Create a new file `README_NEW.md` with improved positioning:

**Key changes**:
1. Sharper headline: "See WHY Your AI Agent Did That"
2. Demo GIF right after headline
3. Comparison table vs competitors
4. Simplified quick start
5. "Questions this answers" format

### Backup and Replace

```bash
cd /home/nistrator/Documents/github/amplifier/ai_working/agent_debugger

# Backup current README
cp README.md README_OLD.md

# Replace with new one
mv README_NEW.md README.md

# Commit
git add README.md README_OLD.md
git commit -m "docs: improve README positioning and onboarding"
git push
```

---

## Day 4: One-Command Demo Command 🎮

**Time**: 3-4 hours
**Impact**: MEDIUM-HIGH - Reduces friction to zero

### Add `peaky-peek demo` CLI Command

**File**: `cli.py`

Add a demo subcommand that:
1. Seeds demo data from benchmarks
2. Starts the server
3. Opens browser to pre-loaded UI
4. Shows helpful onboarding text

### Update README

Add to Quick Start:

```markdown
## Try It Now (2 minutes)

**Zero-code demo** (see it in action):
```bash
pip install peaky-peek-server
peaky-peek demo  # Opens browser with pre-loaded examples
```
```

---

## Day 5: First Blog Post 📝

**Time**: 3 hours
**Impact**: MEDIUM - Builds awareness

### Write Blog Post

Create `blog/2026-03-why-i-built-ai-agent-debugger.md`

**Outline**:
1. The problem: Agent failed, no idea why
2. Traditional tools don't help (logs miss reasoning)
3. The solution: Record decisions + replay from checkpoints
4. Demo: Walk through real debugging session
5. Open source + local-first philosophy
6. Try it: `pip install peaky-peek-server`

**Publish on**: Dev.to, Medium, Reddit r/MachineLearning

---

## Success Metrics (Track Daily)

| Metric | Day 0 | Day 7 | Goal |
|--------|-------|-------|------|
| GitHub Stars | ? | ? | +50 |
| PyPI Downloads | ? | ? | +200 |
| Demo GIF Views | 0 | ? | 1000+ |
| Landing Page Views | 0 | ? | 500+ |
| Blog Post Views | 0 | ? | 500+ |

---

## Quick Reference: File Locations

| What | Where |
|------|-------|
| Demo GIF to create | `docs/assets/demo-30s.gif` |
| Landing page HTML | `docs/index.html` |
| Landing page CSS | `docs/style.css` |
| README to update | `README.md` |
| CLI to enhance | `cli.py` |
| Demo seed script | `scripts/seed_demo_sessions.py` |
| Blog post to create | `blog/2026-03-why-i-built-ai-agent-debugger.md` |

---

## Next Actions (Pick One)

1. ✅ **Start with Demo GIF** (highest impact, 2-3 hours)
2. ✅ **Deploy landing page** (already planned, 3-4 hours)
3. ✅ **Improve README** (quick win, 1-2 hours)
4. ✅ **Add demo command** (reduces friction, 3-4 hours)
5. ✅ **Write blog post** (builds awareness, 3 hours)

**Recommendation**: Do #1 (Demo GIF) first, then #2 (Landing Page). These two alone could 10x your visibility.
