Revenue models are easy to list and hard to price. Here are seven with the actual monthly running cost attached — including the three that quietly stop working once volume goes up.
I cannot access that is a permissions statement, not a capability limit. This guide connects Codex to live tools: first server in under 10 minutes, which servers a beginner actually needs, config.toml field by field, and the security traps to avoid.
Already running MCP servers? This is the operator's manual: which server to reach for in each workflow, the pitfalls that bite in production, permissions, context bloat, leaked keys, surprise invoices, and the audit prompts that keep it lean and secure.
I take one industry's real workflow at a time, rebuild it with AI agents, and show the whole thing.
AI can already do more than most professions have figured out how to use.
That gap — between what the models can do and what actually runs in your day-to-day work — is what this is about.
I take one industry's real workflow at a time, rebuild it with AI agents, and show the whole thing: the setup, the failures, the numbers, and the parts that still need a human.
Getting agents to finish real work under real constraints is where most AI projects die. That's the part I work on.
Every model release is another round. Same workflow, new generation, what changed and what didn't.
AI — the capability is already here.
Workflow — but how the work actually gets done is different in every field.
Pro — and the people doing it are the only ones who know where it breaks.
Pro here reads as profession, not professional. The professions — law, accounting, medicine, the trades — are exactly the people this is for.
If you work in an industry — law, contracting, accounting, real estate, anything with real procedures and real constraints — this is about your actual work, not about AI in general. You get the workflow, the numbers, and an honest account of where it still needs you.
If you build AI systems — indie developer, automation consultant, technical lead — you get the skeleton and the judgment calls behind it. Everything demonstrated in a video is in the repo.
Not for you if you want "What is ChatGPT" explainers, a "10x your output" pitch, or someone to do the work for you. That content lives everywhere else on the internet. It doesn't live here.
I've been chasing the same question for years: how do you make a thing run without sitting here clicking through it every time? Chasing that question took me through four generations of tools — SaaS low-code, self-hosted open source, AI coding, and now the early shape of multi-agent coordination. The tools keep churning. The question underneath them never does.
Every wave left me with something that looked impressive at the time and looks naive in hindsight. What's worth reading isn't the impressive parts. It's what I threw out, why I threw it out, and what's still standing.
I don't take money from any AI vendor. No sponsorships, no affiliate links, no paid reviews. Nobody pays me to say a tool is good.
That's why this costs money. You're the only one paying me — which is the only way the numbers stay honest.
Browse the latest posts or explore the topic archive, then subscribe for new write-ups. Whenever you've built enough of your own workflow, unsubscribe with no hard feelings. Clean break.
Something wrong, or I missed a case? Email me at [email protected].
— Leo
When I rebuild one with AI agents, you get the write-up — including the parts that didn't work. No weekly roundup, no "5 tools you need."