Blog

The next wave of software isn't feature-driven. It's workflow-driven. Here's why pipelines create switching distance that features never will.

Scaling content with AI is easy. Making it actually feel like you, and not generic slop, is the hardest thing about building a brand in public.

Token costs kill more AI businesses than bad ideas do. Here's the real math behind AI SaaS margins and how to stay profitable.

Building the agent is easy. Getting it to actually work reliably in production, without hallucinating, without burning tokens, without going completely off rails, that's the real problem nobody demos.

Personal AI agents are coming to work. The hard part isn't adoption. It's governance, permissions, auditability, and safe interfaces.

Personal AI will not live in more dashboards. It will need one interface layer across watch, phone, car, and headset.

A practical guide to AI agent orchestration: org charts, task boards, dispatch patterns, and lessons from running 10+ agents daily.

AI can help you ship faster, but it can also help you ship vulnerabilities faster. Here's a practical security checklist for AI-built apps before they hit production.

Why I'm building an AI operating layer to create real output, reduce screen time, and buy back more life, not just more commits.

The biggest gains in agentic engineering come from better token economics: right-sized models, tighter loops, less context bloat, and fewer wasteful check-ins.

Programming complexity has always been abstracted upward. LLMs are the next layer, and the best engineers are becoming agent orchestrators.

The model call is only one dependency. If you want AI features that survive real usage, the API contract, latency budget, fallbacks, and orchestration layer matter more than the demo.

Prompts and polished UI get attention, but most AI products actually fail in queues, retries, state, evals, and data contracts.

Five years of building SaaS before sunrise. Five products ready to sell. Zero audience. Here's what went wrong and what I'm doing about it.

AI makes code free. That changes what wins. Here's what I'm betting on instead.

What happens when you treat AI agents like employees: task boards, specializations, dispatch rules, and the software I built to manage it all.

The exact tools I use to build and ship multiple SaaS products without spending a cent on infrastructure. Neon, Vercel, Cloudflare, and more.

The thesis behind Axislabs: multiple AI-native bets, one holding company, and why the timing matters more than people think.

Practical lessons from building AI agent-powered products at Axislabs — what works, what doesn't, and where this is all heading.