Most capability claims are bullshit. "Full-stack developer" means nothing. "10+ years experience" tells you less than you'd think.
So here's what I actually measured over one week in June 2025, when I had the tools and the time to see what I could do:
The Numbers
- 161,333 lines of code edited (AI-assisted)
- 1,016 requests to development tools
- $15.28 spent (maxed free tier, went pro, hit limits)
- 6 complete projects - 3 with live websites
- Multiple forced pauses because I ran out of budget
That's not sustainable. But it shows what happens when the bottleneck isn't me.
What I Built
- Uroboro: SQLite-based capture system. Tags, search, local-first.
- Examinator: AI-generated learning content from documents.
- Doggowoof: Monitoring and alerting. Still in development.
- Panopticron: Status dashboard for Vercel/GitHub. Thesis project.
All of these share patterns: SQLite as the coordination layer, AI integration, CLI-first interfaces. I'm not building random things. I'm building an ecosystem.
What Limits Me
Honesty means talking about what doesn't work:
- Token budgets: Hit the wall regularly. Development pauses mid-flow.
- Context windows: Large refactors don't fit. Have to break things up.
- Local compute: 8GB laptop. Can't run the big models.
- API dependency: No internet, no AI. That's a problem.
These constraints shaped how I work. Can't brute-force it. Have to be systematic.
Constraint-Driven Solutions
Ran out of Claude credits mid-project. Built Panopticron entirely on free Google AI Studio (Gemini 2.5 Pro) instead. It works. Not as elegant, but it ships.
Copy/paste context between tools was killing my flow. Built sjiek - git diff to clipboard automation. Small tool, big impact. Daily GitHub activity started after that.
The pattern:
- Hit a wall
- Build a workaround
- Keep moving
Not just using AI. Building tools to use AI better.
What This Means
Can Deliver
- Integrated tool ecosystem (working demos)
- AI-augmented development (161K lines/week when unblocked)
- Problem-solving under constraints
- Workflow optimization tools
Current Limits
- Token budget caps development depth
- Context windows limit complex refactors
- Local compute prevents big model usage
- API dependency creates interruptions
Constraints drive innovation. Limited resources meant building smarter. But there's a ceiling without better infrastructure.
Bottom line: I can show you what I built. I can show you the numbers. I can explain what's holding me back and how I work around it.
That's more than most capability claims offer.