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The Multi-Model Workflow

One chat for every task turns a strong model into a mediocre one at everything. Here's a system where each model does what it's best at, and you get team-level output working solo

Why it matters: every model has its own strength profile. When the whole project lives in one chat, you pay twice: the strong model burns its capacity on routine, and tasks outside its profile get a mediocre answer. Splitting the roles buys a quality jump without spending a single extra dollar.

Step 1

Give each model a role

My split, tested on a live product: Claude takes architecture, writing and everything with a high cost of error. GPT generates strategy and options. Perplexity owns facts and sources. Gemini digests long documents. Grok watches trends and social.

At the start of every dialogue, hand the model its role card:

Prompt · role card
You are working inside a multi-model system. Your zone: [architecture and writing / strategy and ideas / facts and sources / document analysis / trends]. Project: [short description]. Answer only within your zone. If a task falls outside it, name the model it should go to and don't solve it yourself.
Step 2

Hand off context, don't retell it

The biggest time sink in multi-model work is retelling the project to every model from scratch. Instead, at the end of a session ask the model to assemble a context file and carry it forward:

Prompt · context file
From our dialogue, assemble a project context file for handoff to another model: the goal, decisions made, open questions, style requirements. Compress it to 300 words, no filler, in a format another model will understand without explanations.
Step 3

Merge the results on the strongest model

Bring the answers from different models to the strongest one and let it act as the judge: it merges them, finds contradictions and flags what needs checking.

Prompt · synthesis
Here are results for one task from two models: [paste both]. Merge them into a single solution. In a separate list, show the contradictions between the versions and the claims that require fact-checking before I make a decision.
Level up

Make it a weekly rhythm

Monday: strategy and the week's plan on GPT. Tuesday to Thursday: production on Claude with context files. Friday: fact-checking on Perplexity and the week's synthesis on Claude. This is the system I used to build a product with no code and no team at the start.

Go deeper

This is the first guide in a series across four stages. The full course runs on a waitlist

First cohort · the waitlist closes August 6