Human-in-the-Loop Agent Approvals: A Mastra Pattern
Prompt-based approval gates fail because the model decides whether to ask. Mastra's requireApproval primitive removes that decision entirely. Here's how to implement it.
Production AI Engagements
Most AI projects die
between demo and production.
I'm Damian Galarza. I work with engineering teams on retainer to ship reliable AI features, harden the AI stack, and make agentic systems that survive past the demo.
15+ years building production software. Former CTO at Buoy Software where we shipped FDA-cleared medical device software. Currently senior engineer at August Health building August Intelligence. The patterns I bring are tested with real users, real token budgets, and real error rates — not adapted from blog posts.
15+
years building production software
0 → 50+
engineers scaled as CTO
FDA
cleared medical device software shipped
1+ yr
daily Claude Code user, documented publicly
01.
How I Work
$12,000 · 2 weeks
Foundation Sprint
A focused 2-week engagement that produces a written architectural assessment and one shipped foundation piece. Either side can walk away after, or convert to retainer.
$15k–$60k/month
Production AI Retainer
Ongoing engagement at the intensity you need — Advisory, Embedded, or Full. Flat monthly rate, flexible hours, direction reset every two weeks. Two-month minimum after Foundation Sprint, then 30-day notice.
Backed by a 30-day money-back guarantee. Also available: 1:1 coaching for engineers shipping production agents and the leaders defending the spec.
02.
What Clients Say
"He quickly understood where we were with AI tooling and gave us immediately actionable advice, not generic frameworks. He identified gaps we hadn't considered, walked us through how he architects agent loops in production, and helped us think through our product-level agent strategy without over-engineering it."
"I found his videos especially clear-headed. I booked a couple of private sessions to discuss OpenClaw, and to my delight, he was equally clear-headed in person."
03.
Start With The Topic You Care About
Production AI Engineering
Ship AI systems that survive real users, real costs, and real failure modes.
Architecture, evals, observability, governance, and the production tradeoffs most teams skip until it hurts.
Claude Code
Build workflows around Claude Code instead of using it ad hoc.
Context windows, MCP servers, CLAUDE.md systems, rollout patterns, and real-world development workflows.
AI Agent Architecture
Design agents with memory, tools, and boundaries that actually hold up.
Memory systems, orchestration, tool use, governance, and the production patterns behind agentic systems.
04.
Recent Writing
May 27, 2026
May 13, 2026
Your AI Team Doesn't Need More People — It Needs Agents
What 'supported by a fleet of agents' means in practice: which tasks automate, which don't, and where the ROI breaks down. Evidence from Stripe, Coinbase, Ramp, and Shopify.
May 6, 2026
Claude Code Routines: Auto-Maintaining PR Evolution Numbers
A backend PR kept colliding with other merges on database evolution numbers. Four manual rebases later, I described the problem to Claude and let it write a routine to handle the rest.
Apr 30, 2026
Claude Opus 4/7 + Claude Code: 7 Practical Tips for Maximizing Extended Context
Practical tips for getting the most from Claude Opus 4.7's 1M context window in Claude Code. Effort levels, proactive compaction, subagent delegation, and session management from daily production use.
Apr 22, 2026
Governing AI Agents Without Killing Them: What Actually Works in Production
Most AI agent governance advice targets boards, not builders. Three failure patterns, real TypeScript examples, and what a CTO should do Monday morning.
Apr 20, 2026
Adding Audio Narration Revealed the Bugs in My Writing
How I added ElevenLabs TTS audio narration to my Hugo blog, cloned my own voice, and discovered my writing had patterns no voice model could read.
05.
Start a Conversation
Schedule a Free Intro Call
30 minutes. No pitch deck. We'll talk through what you're working on and I'll tell you honestly whether I can help.
No pressure, no upsell. Just a conversation to see if there's fit.
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Insights on AI integration, engineering leadership, and building production systems. Written from ongoing practice, not past experience.
Occasional emails. No fluff.