I Do Run AI Agents Overnight. Here's What Actually Matters.
Boundaries, supervision, evidence, and why unattended execution is not the same thing as unbounded autonomy.
Petie Clark — Applied AI Systems
Applied AI systems that survive contact with the business.
Field notes on agent orchestration, evaluation, authority boundaries, enterprise integration, deployment, and production operations.
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How I think about governed systems
Why I Prefer One Clear Source of Truth
Why tools can multiply while authority, state, and accountability still need one dependable home.
Why I Write Down the Rollback Before the Change
A deployment is not ready merely because the forward path looks convincing.
The Case for a Smaller Blast Radius
Production systems become trustworthy through bounded change, not theatrical confidence.
What Breaks First in a Homelab
The first thing to fail in a homelab usually isn't the newest service. It's the assumption that the service is standing on something simple.
4 min read
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The AI Productivity Paradox Is Real - But You Are Measuring the Wrong Thing
CEOs say AI isn't moving the needle on productivity. I've been running AI in production for months. Here's why they're both right and wrong — and what the actual measurement problem is.
5 min read
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I Do Run AI Agents Overnight. Here's What Actually Matters.
A post about autonomous AI agents hit the top of HN this morning. I actually run them. Here's what I've learned about where they work, where they fail, and the 6 rules I've settled on.
4 min read
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Every Few Months a New Model "Beats Whisper." This One Is Different.
Moonshine AI posted their open-weights speech-to-text toolkit on Hacker News this morning. 252 points in 13 hours. The top-line claim: higher accuracy than Whisper Large V3,
4 min read
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The Vibe Code Backlash Is Real, And I'm Somewhere in the Middle
r/selfhosted just banned AI-vibe-coded projects except on Fridays. After running 100+ containers in production and building two SaaS products with AI assistance, here's where I actually land.
4 min read
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Fine-Tuning LLMs on Apple Silicon: Lessons from Production
Three crashes, two NaN catastrophes, and one breakthrough: fine-tuning a 33B model on Mac Studio to learn my coding patterns. Real configs, real mistakes, real lessons.
3 min read
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Fine-Tuning a 20B Model on 512GB Apple Silicon: What I Learned
I fine-tuned a 20-billion parameter model on my Mac Studio M3 Ultra and took validation loss from 1.85 to 0.79. Here's what I learned about running serious AI workloads on Apple Silicon.
3 min read
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Why I Run AI Models on My Own Hardware
I've been running large language models locally for a few months now, and honestly? I'm not going back to API-only workflows. The Cost Math Cloud
2 min read
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