# Before you can automate anything

*13 Sept 2026* · Stella Ellervee

Most companies can't get value out of the AI tools they already have, and the reason is almost never the model.

_Placeholder — written by Claude, not by Stella_

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Everyone's shopping for the next model. Most companies haven't sorted out the
two boring things that actually gate whether any of it works. Neither one is
a technology problem.

## Your documentation has to be AI-ready

That starts lower than it sounds. First, it has to *exist*. A huge amount of
"documentation" at most companies is really tribal knowledge — the thing
Sarah knows, the thing that got explained once in a meeting nobody recorded.
An agent can't read what was never written down, and neither can the new
hire who replaces Sarah.

Once it exists, it has to be consumable in a token-efficient way. A wiki
written for a human skimming with their eyes, full of preamble and repeated
context and screenshots standing in for the words that should be next to
them, is expensive and lossy to hand to a model. And it has to be organised
and searchable — not just present somewhere in a space with four hundred
other pages, but findable by whatever is looking for it, whether that's a
person or an agent doing the search itself.

Existing, efficient, findable. Skip any one of the three and the docs
function as decoration, not infrastructure.

## Workflows have to be mapped — and agreed on

The second gap is that a lot of workflows were never written down either,
because they never had to be. A process survived for years as "ask whoever's
done it before," which works fine when the person who's done it before is
always around. It stops working the moment you want to hand the process to
something that can't ask around.

Worse, plenty of workflows don't actually have one agreed version. Different
people do the same job differently, and nobody's had to reconcile that,
because human variation absorbs it quietly. You can't automate a workflow
that has three unspoken versions — you have to pick one, or explicitly branch
it, before there's anything to automate at all.

Mapping the workflow comes first. Getting people to actually agree on it
comes right after, and is usually the harder of the two — not because the
mapping is hard, but because agreeing on "this is the correct way to do it"
means someone has to actually decide, out loud, instead of everyone quietly
doing their own thing. Once that's done, the rest is comparatively easy:
somebody just has to hit approve.

## Neither of these is about the model

This is the same shape as the liability gap I wrote about separately — the
scaffolding to automate a given piece of work usually already exists on the
model side. What's missing is company-side infrastructure: documentation
good enough to hand to something that can't ask a follow-up question in the
hallway, and workflows clear enough that there's actually one version to
automate. Solve those two and the "we tried AI and it didn't really help"
story mostly goes away on its own.