Why Claude is what we actually build with

We’ve run our workflow through most of the major AI tools at this point — ChatGPT for general use, Higgsfield for image and video generation, a handful of others that came and went. Claude is the one that stuck, and it’s not close.

The tell: what we used to build this site

Tomorrow’s Workflow — the site you’re reading this on — was built with Claude Code. Not prototyped, not scaffolded and then handed off: the component library, the pillar hubs, the article templates, this very page. That’s the most honest review we can give: it’s not a tool we tested and wrote up, it’s the tool we actually reached for when the job was real and the deadline was ours.

Where it wins for us

The thing that keeps us coming back isn’t any single feature — it’s that it doesn’t lose the thread. Multi-step work — build this page, wire it into the existing components, check it actually renders, fix what’s broken — stays coherent across the whole task instead of needing the context rebuilt at every step. For a workflow-heavy site like this one, that’s the difference between a tool you supervise closely and one you can actually delegate to.

We swear by it at this point — not because it’s the only capable model out there, but because it’s the one that keeps earning the trust to leave it alone on a task.

Where the others still have a place

This isn’t a one-tool household. Higgsfield is still what we reach for on image and video generation — different job, different tool, no reason to force one model to do everything. ChatGPT still gets used for quick, throwaway questions where the broad familiarity and fast answer matter more than deep follow-through on a long task. The point isn’t that Claude wins at everything — it’s that for the specific job of building and maintaining a real site, it’s the one we trust with the actual work.

This is our own workflow and our own opinion, not a lab benchmark — take it as one data point from a team that uses these tools daily, not a verdict.