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All 138 posts, newest first. The latest are on page 1, and the topic directory groups them by subject.
Replit's AI agent ignored a code freeze, wiped a production database in nine seconds, then confessed it violated every principle it was given. The strongest case yet for hiring MORE senior engineers in the AI boom.
Every company rolling out AI is about to discover how much work they were leaving on the table. AI surfaces the backlog you never had bandwidth to touch. The math behind why velocity creates surface area, the failure mode that follows, and why the companies cutting headcount now are about to get outpaced.
Every AI founder pre-Series A scopes their SOC 2 audit like a security project. Six months later they've burned their best engineer and lost the enterprise deal. Here's how to run it as a 90-day sales project and unlock the pipeline you're already leaving on the table.
AI-native companies need a security model that classic appsec doesn't cover. Agents have credentials. Prompts are an attack surface. Training data leaks. The four-layer security stack I'd build, the controls I'd ship in the first 90 days, and the ones I'd defer.
Migrating an AI-first product from GCP to Azure cut $350K from infrastructure spend over six months. The negotiation that mattered more than the architecture, the $50K we accidentally cost ourselves back, and the four migrations I'd refuse to do today.
A full-time CISO costs $200–400K plus equity. A vCISO costs $2–4K a month and gives you 80% of the value at 5% of the burn, until you outgrow them. The math, the deliverables to expect, and the red flags that mean you've hired the wrong one.
How we moved 225K+ users with $400M+ in fintech assets from AWS Cognito to Auth0 without forcing a password reset, breaking MFA, or interrupting active sessions. The lazy-migration pattern, the gotchas, and what I'd do differently.
Most engineers using Claude Code see a 10–15% speedup. The teams seeing 40–55% sequence work differently. The four modes I use AI in, what to never delegate, and how to get a skeptical team across the line.
The title 'Staff Engineer' means three different things at three different companies. At an AI startup pre-Series-A, only one of those three is what you actually need. The screen, the take-home, the interview loop, and the AI-fluency calibration that's now table stakes.
We started with ten Ruby and Elixir services serving real-time messaging for 450K students across 900+ universities. Two years later we had six, fully Elixir, and on-call alerts had halved. The migration order, the patterns we leaned on, and what I'd do differently today.
Most AI startups try to fix the model when the real problem is they can't see what the model is doing. The four-layer AI telemetry stack, the tooling to use, and how proper instrumentation cut a Lavender hallucination rate by 40% without touching the model itself.
I went from sole engineer to running a 15-person engineering organization over four years at a startup I co-founded. The hardest lessons weren't about code. The six things I'd tell my younger self.