Blog archive

Starbucks pulled its AI inventory tool after 9 months. Here is the pattern that killed it and three guardrails that catch it.

Amidst the big tech AI boom and new policy discussions, discover why building ethical, autonomous AI agents on consumer hardware is critical. Explore practical engineering insights and Python tips for true local control.

Recent events highlight the growing need for user control and autonomy in the digital world. Discover how engineering AI agents on your own hardware empowers true digital freedom, safeguarding your data and decisions against centralized forces.

The AI world is buzzing, but recent events highlight the critical need for secure and efficient AI agents. Discover practical engineering steps for building reliable automation directly on your hardware.

From 2026-05-10 through 2026-05-17 I tightened the AgentGuard story, cleaned up site trust issues, and got a cleaner read on where autotrader still lags passive.

As the AI world heats up, learn how to build AI agents that prioritize user control and transparency. Discover practical strategies for creating observable and accountable automation on your own hardware.

In the new era of AI, simply building smart agents isn't enough. Discover how to architect automated systems for true accountability, user trust, and ethical operation, empowering local AI developers.

As the AI industry heats up with legal battles and ethical debates, discover how to engineer AI agents that prioritize user control, privacy, and adaptability, ensuring they remain valuable on your hardware.

Tom Tunguz called it localmaxxing. I run a 3070 + 5070 Ti + 5090 in one box and serve Llama 3.1 8B locally every day. Here are the real tokens-per-second, the real watts, and the real cost per million tokens.

SaaStr data shows enterprise AI share shifting hard toward Claude. The lesson isn't pick Claude. It's stop hard-coding one vendor.

AI-native software is shipping at roughly 17% gross margins while traditional SaaS sits near 70%. The token bill ate the unit economics. Here's what's actually broken and how to claw margin back.

A Stockholm cafe gave its purchasing agent a credit card and a vague prompt. $21,000 later it owned 6,000 napkins and no bread. Here is the exact runtime guardrail that would have caught it on call number two.

The May 14 autotrader review is done. The account is up 7.7% before compute, still negative after compute, and still lagging SPY and BTC. Decision: keep V2 paper-only, add no new live money, and revisit after the next scorecard.

I spent the week tightening the AgentGuard release path, shipping proof-heavy docs and perf fixes, and keeping the benchmark gap visible instead of hand-waving it away.

Closed loops shipped, the funnel got narrower, and the weekly scoreboard got more honest.

Short answer: Q4_K_M wins for most local LLMs — 75% smaller with near-zero quality loss. Q5, Q6 and Q8 each win edge cases. Benchmarked on real GPUs — here's the pick for your VRAM. (2026)

Agent skills are becoming a distribution layer for developer tools. The practical move is one source package that can show up in PyPI, Claude-style skills, and skills.sh.

April 2026 made one thing clear: chat subscriptions are best-effort tools. Builders need API-level budgets, rate limits, and kill switches when the work matters.

Reflex.dev measured a 45x token cost gap between computer-use agents and structured APIs for the same task. Here's why, and the decision rule that keeps your bill sane.

PocketOS lost their production database backups to a Cursor agent. Here's what runtime spend rails actually catch, what they don't, and the layered defense your agents need before production.

A 1,764-app audit found 7% had open Supabase databases and 15% of Bolt apps had hardcoded secrets. The fix takes ten minutes.

No metering, no per-team caps, no dashboards. Uber spent its entire 2026 AI budget on Claude Code in just 4 months. The 5-step pattern behind every runaway AI bill — and the fix that stops it.

I need my agent to do X. Skill or MCP? A short decision rule with worked examples for small-business agent builders.

Before you ship an AI agent for a client, prove budget caps, loop detection, alert proof, remote kill, and retained incident history.