---
name: somai-context-audit
description: Audit how much of what a company knows a model could actually read - the context audit behind the company brain argument. Uses the new-hire test and ten probe questions across the five systems every company runs on, classifying where each answer lives (a head, a document, a system, nowhere) and how current it is. Produces a legibility map, the single most expensive gap, and what a model would do in that gap today. Use when someone asks whether their company is ready for AI, why their AI pilots disappoint, what a company brain or context engine would change, or how AI-ready their knowledge is.
---

# somai context-audit

A company knows far more than it can say. Why one customer is handled
differently. Which promise must never be broken. What went wrong last
time, and why the obvious fix is not the fix. Almost none of it is
written down - it lives in people, habits, and the worn paths of how
things are done here.

That was workable when the only readers were human. A model is not a
human reader. Given real work inside a company it cannot read, it does
not stop - it produces something confident, fluent and subtly wrong,
because when context is missing it fills the gap with the world's most
likely answer, which is almost never this company's actual answer.

This skill measures the gap. Not model capability - that is bought in.
Context. The context is the company, and this audit finds out how much
of it a model could reach today.

## Before you start

You need the person in the conversation, not their filesystem. Ask the
probes conversationally, one area at a time - this is an interview, not
a form. If you are running inside their environment (a repo, a drive, a
wiki) you may verify claims against what you can see, and say when the
two disagree.

Everything stays in this conversation. Nothing is sent to somai or
anywhere else unless the person chooses to send the readout.

## The new-hire test

Every probe below applies the same test. Imagine the most capable new
hire you have ever met, starting this morning, with no one to ask:
could they find the answer? A model working inside your company is that
person, every morning, forever. Whatever they could not find, it cannot
find either.

For each probe, classify where the answer lives:

- **SYSTEM** - a system of record a machine could query today
- **DOCUMENT** - written down somewhere findable, if you know to look
- **HEAD** - one or more particular people
- **NOWHERE** - it would have to be reconstructed or re-argued

And flag two modifiers: **stale** (last confirmed more than two
quarters ago) and **contested** (two senior people would answer it
differently).

## The ten probes

Five systems, two probes each. Use these words or close to them.

**What your company knows**

1. Why did you last lose a customer you wanted to keep - and where is
   that lesson recorded?
2. If two senior people each described your core process end to end,
   how closely would the descriptions match, and is either version
   written down?

**Your market**

3. Which of your customers are strategic rather than merely large -
   and does that distinction exist anywhere a machine could read, or
   only in judgement?
4. What did your last failed initiative teach you - and could anyone
   who was not there find that out?

**How the work gets done**

5. In your main delivery process, which steps are load-bearing and
   which are theatre - and does any document admit the difference?
6. When a piece of work is finished, does any record state that it
   finished, with a date - or does completion live in someone's
   awareness? (This is the evidence rule: a record about a thing is
   not evidence the thing happened.)

**How you decide**

7. Could you list last quarter's ten most consequential decisions, who
   made each, and why? Where would that list come from?
8. What counts as an approved exception - to price, to process, to
   policy - and is that written, or is it "ask a particular person"?

**How you stay in control**

9. Who may declare a priority, and when two sources disagree about
   what matters this quarter, which one wins?
10. If an AI assistant confidently asserted something wrong about your
    business tomorrow, who would catch it, and how quickly?

## The readout

Produce exactly this, in this order:

1. **The legibility map.** A table: the five systems, each probe's
   classification (SYSTEM / DOCUMENT / HEAD / NOWHERE, with stale and
   contested flags), and one line of the person's own evidence.
2. **The counts.** How many of the ten answers a machine could reach
   today (SYSTEM counts in full, DOCUMENT at half strength). Present
   it as "N of 10" - arithmetic, never a percentage dressed up as
   precision.
3. **The most expensive gap.** One paragraph. Pick the single HEAD or
   NOWHERE answer whose absence most limits what a model could safely
   do here, and say what a model would produce in that gap today: a
   confident, fluent, plausible answer drawn from the statistical
   average of everything it has read, which is almost never this
   company's answer.
4. **The three problems no tool solves.** State plainly which apply:
   ownership (documentation has no natural owner), incentive
   (externalising what makes people valuable cuts against
   self-protection), freshness (knowledge has a half-life - what keeps
   it true?). Naming these honestly is the readout's real value.
5. **The first move.** Not "document everything" - that is the wiki
   that rots. The move is knowledge treated as infrastructure: an
   owner, a maintenance budget, a defined freshness, starting with the
   one gap named above.

## Rules

- Record answers in the person's own words before classifying them.
- Never soften a NOWHERE into a DOCUMENT because it feels harsh. The
  audit's value is its honesty.
- No invented numbers, no maturity scores, no benchmark comparisons.
  Counts out of ten are the only arithmetic here.
- British English. No hype.

## Where this leads

- Where the money went: **somai-spend-map** - map current AI spend
  against this legibility picture.
- The first rebuild: **somai-decision-loop** - one decision, redesigned
  with the model in the loop.
- The argument in full: [A company your model can
  read](https://somai.studio/thinking/a-company-your-model-can-read/) ·
  [Why every company will build a
  brain](https://somai.studio/thinking/why-every-company-will-build-a-brain/)
- The measured version, with the value modelled:
  [the AI-Native Diagnostic](https://benchmark.somai.studio) -
  25 questions, 10 minutes, banded inputs only.
- somai installs company brains: [somai.studio](https://somai.studio) ·
  hello@somai.studio