This week I audited every AI workflow I run - cost vs value, no mercy.
Here's what I found:
> 70% of my workflows are net negative. Most AI setups I've built burn more time and money than they save.
> The 30% that work? Easily 10x more efficient than doing it manually.
> 65% of the winning workflows are ones I already understood end-to-end - engineering, UI/UX, long-form content, product management, research, mechanism simulations. I'd done them myself dozens of times before automating.
> The other 35% worked because there was rich existing context and clear use-cases available. I didn't always know what the output would look like, but I could learn through the process.
> Going deep in one domain >>> going wide. Trying to automate a broad range of workflows at once was the biggest cost sink - in both time and money.
> Most futile workflow: AI work planners. Overwhelm me more than they help.
Tools I've found genuinely powerful but haven't scratched the surface of: Hermes, OpenClaw, Autoresearch, Paperclip.
Honest admission: I'm still early in this journey. X makes it feel like everyone has it figured out.
