feat: add blog system with static site generator

- Add blog posts in Markdown (_posts/)
- Build script converts MD to HTML at container build time
- First posts: building with AI lessons, quick start guide
- AGENTS.md documents blog writing style (unixsheikh-inspired)

www/_posts/2026-03-27-building-deardiary-with-ai.md

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+---
+title: Building DearDiary with AI - Lessons from Human-AI Collaboration
+date: 2026-03-27
+author: Konrad Lother
+excerpt: What I learned from building a full-stack app using an AI coding assistant
+---
+
+# Building DearDiary with AI
+
+## A Tale of Miscommunication and Debugging
+
+I built DearDiary using an AI coding assistant. It was enlightening, frustrating, sometimes hilarious, and ultimately successful. Here's what I learned about human-AI collaboration.
+
+## The Setup
+
+DearDiary is a full-stack journaling app: Bun + Hono backend, React + Vite frontend, SQLite database, Docker deployment. Not trivial, but not rocket science either.
+
+I gave the AI context about the project structure, my preferences, and let it work.
+
+## The Problems We Hit
+
+### 1. "It Should Work, But..."
+
+The first major issue was the most classic: the AI made changes that *should* have worked according to its understanding, but didn't.
+
+We consolidated environment variables into a single `.env` file with prefixes. The AI updated most references to `DATABASE_URL` → `BACKEND_DATABASE_URL`, but missed several:
+- The Prisma schema
+- The test helpers
+- A variable in the healthcheck config
+
+The app failed to start. The error message? Cryptic Prisma errors that took time to trace back to a simple env var mismatch.
+
+**Lesson**: AI is great at systematic changes, but when it misses something, the gap is invisible to it. Always verify systematically.
+
+### 2. The Disappearing Routes
+
+The AI moved API routes into a separate file (`events.ts`) and mounted them at `/api/v1`. Simple, clean.
+
+Except the routes were at `/api/v1/events` but the frontend was calling `/events`. The AI didn't catch that the mounting path was part of the route definition.
+
+**Lesson**: AI understands code structure well, but context about how pieces connect across files is easily lost.
+
+### 3. "I Fixed That"
+
+Multiple times, the AI would say "Fixed!" and show the corrected code, but the actual file hadn't been changed. Or it would describe a solution that wasn't implemented.
+
+This is the most dangerous mode of failure - confidence without execution.
+
+**Lesson**: Never trust "fixed" without verification. Make it show you the actual changes.
+
+### 4. Permission Denied
+
+Docker entrypoint scripts kept failing with "permission denied". The AI knew about `chmod +x`, but the order of operations was wrong - file copied after chmod, or Docker cache serving old versions.
+
+**Lesson**: AI knows facts, but execution order matters. Sometimes you need to walk through the sequence step by step.
+
+### 5. The 404 Debugging Journey
+
+Events returned 404. We checked:
+1. Routes - correct
+2. Mounting - fixed
+3. Auth middleware - fixed
+4. The actual problem: nginx port mapping. Port 3000 on the host was mapped directly to the backend, not through nginx. The frontend (served by nginx) couldn't reach the API.
+
+**Lesson**: The AI focused on the obvious layers. The problem was in the infrastructure/configuration layer. AI needs explicit context about the full stack.
+
+## What Went Well
+
+Despite these issues, things also went surprisingly well:
+
+- **Feature implementation**: The core features (event capture, AI generation, search) worked on first try
+- **Consistency**: Once a pattern was established, the AI maintained it consistently
+- **Refactoring**: Moving from multiple `.env` files to one was smooth after the initial issues
+- **Documentation**: README updates, code comments, and AGENTS.md were accurate
+
+## The Communication Patterns That Worked
+
+### Be Specific About Failures
+Instead of "it doesn't work", I'd say:
+> "Events endpoint returns 404, checked docker logs and the route is registered"
+
+The more context, the better the fix.
+
+### Ask for Verification
+> "Show me the exact changes you're making before committing"
+
+This caught the "I said I fixed it" problem.
+
+### Break Down Complex Changes
+Instead of "consolidate all env vars", we did it in stages:
+1. List all current env vars
+2. Decide on naming convention
+3. Update backend
+4. Update frontend
+5. Update docker-compose
+6. Verify
+
+### State What You Know Works
+> "Previous similar changes worked with `docker compose build && docker compose up -d`"
+
+Context about what has worked before helps the AI avoid untested approaches.
+
+## The Meta-Lesson
+
+Building with AI is like working with a very knowledgeable junior developer who:
+- Has read every Stack Overflow post
+- Can write code faster than you can type
+- Sometimes confidently does the wrong thing
+- Needs supervision, especially for changes spanning multiple files
+- Gets better with clearer instructions
+
+The key insight: **Your job becomes managing the AI, not just writing code.** You need to:
+1. Provide good context
+2. Verify systematically
+3. Catch the invisible gaps
+4. Maintain the mental model of the system
+
+## What I'd Do Differently
+
+1. **Track changes more carefully** - Use a changelog when AI makes changes, not just git diff
+2. **Test incrementally** - Don't let the AI make 20 changes before testing
+3. **Be clearer about expectations** - "This should work out of the box" is less clear than explicit test criteria
+4. **Document the debugging journey** - The process of finding issues is valuable context for future fixes
+
+## Conclusion
+
+DearDiary is live. The AI and I built it together, argued about typos in environment variables, debugged at 2am, and shipped something I'm proud of.
+
+Human-AI collaboration isn't about replacing programmers. It's about amplifying what humans do well (context, judgment, verification) with what AI does well (speed, consistency, pattern matching).
+
+The future is not "AI replaces developers." It's "developers who use AI replace developers who don't."
+
+Now go build something with AI. Just keep an eye on those env vars.
+
+*— Konrad*

www/_posts/2026-03-27-quick-start-guide.md

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+---
+title: Quick Start Guide
+date: 2026-03-26
+author: Konrad Lother
+excerpt: How to get started with DearDiary in 5 minutes
+---
+
+# Quick Start Guide
+
+Getting started with DearDiary takes about 5 minutes. Here's how:
+
+## 1. Create an Event
+
+Press **Ctrl+J** anywhere in the app to open the Quick Add widget. Type your event and press Enter.
+
+That's it. It takes 3 seconds.
+
+Try these:
+- "Had coffee with Sarah at the new cafe downtown"
+- "Finished the chapter on machine learning"
+- "Rain started around 3pm, got soaked walking back"
+
+## 2. Add More Events
+
+Throughout your day, capture anything that feels worth remembering:
+- Meetings and conversations
+- Meals and what you ate
+- Exercise and how you felt
+- Thoughts and ideas
+- Photos and voice memos
+
+Don't overthink it. A short note is better than nothing.
+
+## 3. Generate Your Diary
+
+When you're ready, click the **Generate** button on today's page. AI reads all your events and writes a narrative diary entry.
+
+You can:
+- Regenerate with different instructions
+- Add context by including previous days' diaries
+- Edit the generated diary (but the events stay locked)
+
+## 4. Review and Reflect
+
+Read your generated diary. Does it capture the essence of your day? If not, regenerate with instructions like:
+
+> "Focus more on the interesting conversations I had"
+
+or
+
+> "Make it more concise, highlight the key moments"
+
+## Pro Tips
+
+- **Be specific**: "Lunch with Marcus, talked about his new hiking trip to Patagonia" beats "Had lunch"
+- **Capture emotions**: "Felt anxious before the presentation" is more interesting than "Presented to team"
+- **Use voice**: Record voice memos while driving or walking - very efficient
+
+That's it. Happy journaling!