I started by bundling AI usage, token metering, and workflow in one product, then realized token billing was becoming its own business. Here’s why I’m testing a bring-your-own-AI-subscription model for PailFlow.
My project scope process kept breaking when I treated scoping as "inputs in, draft out." This post explains the stage-gated method I now use to separate thinking from writing and produce more reliable client-ready artifacts.
Recently, I shared how I built a target account list with a browser agent. This follow-up shows how I turned that one-time list into a repeatable enrichment workflow I can trust for outreach.
I needed a reliable target account list for PailFlow, not a random pile of leads. This is the simple 4-step system I used to source, enrich, score, and rank 50 accounts while I worked on other priorities.
I stopped trying to prompt my way to consistent writing and moved style into a reusable system artifact. The result is faster first drafts that sound like me without daily prompt tuning.
Coding agents work because they show you exactly what changed. That same pattern needs to exist for every kind of knowledge work agents touch.
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