Jonathan Haas
AI agents are moving into production faster than most teams can measure them. I work on the evals, review loops, agent infrastructure, and operating habits that make delegated AI work trustworthy.
I am building EvalOps. Start with the writing, or read more about me, what I am doing now, and what I use.
Recent writing
- The Real Work of Orchestrating AI Coding Agents
Three concurrent coding agents taught me the actual bottleneck: not prompting, but assignment, evidence, review, and release control.
- Building Kestrel: A Context-Aware AI Desktop Assistant in One Session
How I built a full LittleBird clone with screen context reading, meeting recording, arena mode, and MCP tool support — from scratch to packaged .app in a single coding session.
- DiffScope: What Happens When You Give a Code Review Agent Real Context
Most AI review tools see a diff. DiffScope sees the diff, the callers, the type hierarchy, the team history, and knows when to shut up. Here is how.
- The 10-Minute AI POC That Becomes a 10-Month Nightmare
Five lines of Python and an API key produce a working demo. The gap between that demo and a production system contains failure modes the prototype...
- Why Your AI Strategy is Actually a Spreadsheet Strategy
Most enterprise AI transformations are solving problems that spreadsheets handle at 1/50th the cost. The misalignment is driven by career incentives,...
- The AI Agent Gold Rush: Why Everyone's Building Picks and Shovels
Most AI agent infrastructure is premature. The agents themselves barely work. The industry is selling Formula 1 equipment to people still learning to...
- From Consumer NUC to Production-Grade Homelab: My Journey with Proxmox and Infrastructure as Code
How I transformed two ASUS NUC 15 Pro+ machines into an enterprise-grade homelab using Proxmox, Terraform, Ansible, and 100% Infrastructure as Code
- The CLI Renaissance: How AI is Driving the Command Line Revolution
AI coding assistants output shell commands, not GUI instructions. That single fact is reversing a decade of developer tooling trends.
- Building a Developer Environment That Actually Works: My Dotfiles Journey
Most developer environments are optimized for keystrokes. The actual bottleneck is context transfer between you and your AI tools.
- Useful AI Code Review Needs Product Context
AI review only becomes valuable when it can reason about behavior, blast radius, user impact, and the evidence required to trust a change.