Lesson 835 of 2116
Turning Your Domain Expertise Into a Custom GPT
A custom GPT (or Claude Project) loaded with your accumulated domain documents becomes a portable asset you can demo, sell, or hand off in interviews.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1What you have that AI doesn't
- 2custom GPT
- 3Claude Project
- 4domain knowledge
Concept cluster
Terms to connect while reading
Section 1
What you have that AI doesn't
A Claude Project or custom GPT is just a pre-baked system prompt plus a folder of reference documents. Most working AI tools are 80% prompt engineering and 20% data. As a 20-year veteran, you have the data — your binders, internal manuals, sample work, training decks. Most of which the public model has never seen.
The 4-hour build
- 1Pick a job you used to do that took an hour and was repetitive (proposal review, claim triage, lesson plan QA).
- 2Write a 1-page system prompt: who the assistant is, what it should always check, what tone to use, what it should never do.
- 3Upload 5-10 anonymized examples of inputs and the gold-standard output you'd produce.
- 4Test it with 3 fresh inputs from real life. Note where it's wrong. Update the prompt.
Anonymization is non-negotiable
Showing it in interviews
In an interview, you can say: 'Want to see what I mean? I built a small assistant that does first-pass [task] using my industry experience as the guardrails. Here's a 90-second demo.' This converts an abstract claim into a concrete artifact. Most candidates can't do this. You now can.
Key terms in this lesson
The big idea: a domain-loaded assistant is the cheapest portfolio piece you'll ever build, and the highest-leverage thing you can show a hiring manager.
End-of-lesson quiz
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