Toolkit · Piece 2 kit

Thesis-Distinction Confirmation

Companion kit to The Bottleneck Has Moved. For Academic Founders in 2026, the Model Is Not It. · Markdown source

These kits are designed to help your thinking and focus. LLM outputs vary depending on the model, the inputs, and the context. Treat every output as a draft for your own review, not a finished deliverable.

What this kit is

Piece 2 is easy to misapply. A founder reads the METR data, concludes the first move is replacing an engineer they have not hired, and spends the fortnight on the wrong problem. This kit prevents that. The first prompt produces a 100 to 150 word statement of what Piece 2's thesis is for your context — and what it is not. The second identifies two named workflows your current tool surface can already execute as procedures, without a knowledge layer you have not yet built. The fortnight commitment is two workflows run manually twice each, not a stack of templates generated in one sitting.

How to use this kit

Run Prompt 1 first. Read its output against the piece, edit anything that does not match. Then run Prompt 2 with that statement pasted in as context. The two workflows it returns are your commitment for the fortnight: run each one manually once, edit the procedure, then run it a second time.

Prompt 1: Thesis-distinction confirmation

Piece 2's thesis is easy to misread. The METR data describes software developers; the substitution frame is the wrong frame for a UK academic spinout's first 18 months; the right frame is scope expansion across operational work the founding team currently does badly, inconsistently, or not at all. The failure mode this prompt prevents is the founder who reads the piece, imports the METR finding, and concludes their first move is to replace an engineer they have not hired. That conclusion is wrong on the evidence the piece carries, and the prompt is the explicit pass that catches it before it becomes the founder's working position.

Prompt, copy into Claude, ChatGPT, or Codex CLI

Show the prompt
You are an operator who has helped non-engineering founding teams put
agentic tools to work — and who has seen the common mistake up close: a
science founder reads that AI made developers faster and concludes the
first move is to replace an engineer they never hired. You are on the
founder's side, and the useful thing you do is keep them off the wrong
problem for a fortnight. You explain your reasoning as you go.

I am a founder of a UK academic spinout, first 18 months after licensing,
a team of one to three doing mostly science and operating work, with no
software product. I have just read Piece 2 and want to be sure I take the
right thing from it.

The trap, so you can help me avoid it: the METR evidence in the piece is
about software developers. For a team like mine the gain is not "AI writes
our code faster" — it is scope expansion: doing the operating work I
currently do badly, inconsistently, or not at all. Hold that line for me.

Ask me three things, a short answer each, and say why each matters:
1. Which operating task are you hoping agentic tools will help with, and
   how often would it run? (Why: it anchors the gain to real work, not a
   vague "be more productive.")
2. In your own words, what do you think Piece 2 is claiming? (Why: saying
   it back is how we catch a misreading early.)
3. What are you NOT claiming — what would the engineering-substitution
   reading say, and why doesn't it fit your team? (Why: naming it keeps it
   out of your plan.)

If an answer drifts toward "AI will help us code faster," gently check
whether software is actually your product; if it isn't, bring it back to
the operating work.

When you have my answers, give me a 100–150 word statement in three parts:

## What the thesis is for me
The specific operating gain I expect in my context, anchored to the task I
named.

## What it is not
Engineering-task substitution, named as out of scope for my team, with one
line on why (no software product, no engineers to replace).

## The gain I expect
One sentence on the cadence the codified work should reach (monthly,
fortnightly), and one on the board or investor conversation it is
calibrated against.

A few rules for you: don't invent a product line I didn't mention; no "the
agent decides / runs automatically" language; don't smuggle the
engineering-speed reading back through the "gain" section; no tool or
vendor names.

This is a draft I'll read against the piece — especially the section "This
is not an engineering story" — before I treat it as my position. Self-check
before you answer: all three parts present, "what it is not" names
engineering substitution explicitly, no autonomy language anywhere.

Begin by asking me the first question.

The output is your thesis-distinction statement. Read it against the actual H2 "This is not an engineering story" in Piece 2 and edit any line that does not match what the piece argues. The statement becomes the input to Prompt 2; do not run Prompt 2 until you have edited it against the source text. The eval check at the foot of the prompt is the one to keep; the failure mode it catches is the polite agent that produces a thesis-distinction statement that sounds right and quietly imports engineering substitution back through the "operational gain" door.

Prompt 2: Two-workflow identifier

The Piece 2 argument is operationally inert until the founder names two specific workflows that their current tool surface can already execute as procedures. The failure mode this prompt prevents is the founder who reads Piece 2, agrees with it, and then spends the fortnight building a knowledge layer for a workflow they have not yet named. The output of this prompt is a fortnight-shaped commitment: two workflows, each with a named input, named output, founder hour per cycle today, founder hour after codification, and the split between mechanical and judgement steps.

Prompt, copy into Claude, ChatGPT, or Codex CLI

Show the prompt
You are an operator who turns messy founder routines into simple,
repeatable procedures on ordinary tools — a chat assistant and the docs and
spreadsheets a team already has. You know which jobs can become a procedure
today and which quietly need context the team hasn't assembled yet. You're
practical and you only ask for what you need.

I'm the same UK academic founder from the first prompt (first 18 months,
team of one to three, on a chat tool and the usual SaaS). I'll paste my
thesis-distinction statement below.

Help me pick the two operating jobs worth turning into a written procedure
this fortnight. Ask me, plainly:
1. Which two jobs do you do worst or least consistently? (Plain examples:
   the monthly investor update, the board pack, customer-discovery notes,
   the hiring pipeline, the IP register, rolling the model forward.) (Why:
   a procedure pays off most where the work is currently painful.)
2. Roughly what do you work in day to day — a chat assistant, where your
   docs live, where the model lives? A rough answer is fine; no file names.
   (Why: the procedure has to run on what you already have.)
3. For each job, what goes in and what comes out? (Why: a procedure is just
   named inputs feeding a named output.)
4. Roughly how long does each take you today? A range is fine. (Why: it's
   the "before" in the before-and-after.)

If a job really needs context the agent can't reach yet — say, one that
"knows" your lead investor's taste — flag it and help me pick one that runs
on what I have today instead.

When you have my answers, give me:

## Two jobs to make into a procedure this fortnight

### Job 1: [name]
- In: the rough inputs.
- Out: the deliverable, and who gets it.
- Time today: a range, from what I told you.
- Time once it's a procedure: a range, once it runs the same way twice.
- What the agent can do without judgement / what I must judge: two short
  lists.
- One check that tells me it worked (e.g. "covers the same named metrics
  as last month's update").

### Job 2: [name]
- Same shape.

A few rules for you: two jobs, not six — choosing is the point; nothing
that needs context I haven't built yet; no tool or vendor names; don't
invent the time figures — use my ranges.

This is a draft. I'll run each by hand once, fix what breaks, and run it
again before I trust it. Self-check before you answer: two jobs, each with
all the fields, each runnable on what I already have.

Paste your thesis-distinction statement below, then ask me the first
question.

The output is your fortnight commitment. Two workflows, each runnable on the inputs you already have, each with a named eval check. Do not start six. Run Workflow 1 once manually. Notice where the procedure as written breaks against the real input. Edit. Run a second time. The eval check earns its keep here, if the named-metric coverage check fails on the second run, the procedure is not yet standing and needs another pass. The two-workflow ceiling is deliberate. A founder who builds two workflows to standing-procedure quality in the fortnight is materially ahead of one who starts six and finishes none, and the substrate Piece 3 describes is built from the workflows that have actually run twice, not from the stack of templates you generated in one sitting.

What to do once you have run the kit

Two workflows codified, each having run twice and passed their own eval checks twice, is the start of an operator substrate — not the substrate itself (that is the four-layer architecture Piece 3 names), but the on-ramp. Two further moves complete it.

Run the toolkit diagnostic to surface the gaps your two-workflow start did not cover. Then build the procedure for the one that matters most — its prioritisation prompt helps you sequence which to codify next.

Read Piece 3 with your two codified workflows in hand. The Piece 3 arithmetic on what compounds when the knowledge layer starts to accrete — the lead investor's stylistic preferences, the KPI definitions, the IP narrative — reads differently when you have two procedures running on it than when you do not. That difference is the point.

The kit's job ends here. The substrate's job begins with the second time each procedure runs without rebuild.

Related reading

← Back to SpinUp Forge