The Question Latch: Forcing AI to Spec Your Ideas Before You Build

Most technical brainstorming sessions with AI fail because the assistant is too eager to please. You propose an idea, and it immediately starts writing code or a 10-page plan. This creates Context Debt—you’re now reading 500 lines of a plan you didn’t fully vet.

At Portia Labs, we use a technique called the Question Latch.

The Pattern: The 10-Question Gate

Instead of letting the AI run wild, you force it into an “Inquiry Phase.” By setting a hard constraint—“Ask me X questions before you do anything else”—you flip the power dynamic. The AI becomes a rigorous systems architect instead of a generic autocomplete engine.

Why it works:

1. Requirement Freezing: It forces you to define the edges of the problem (e.g., “Must run offline,” “Must be zero-dependency”).
2. Anti-Vibe Guardrails: It replaces vague “vibes” with a technical specification.
3. Discovery of Unknowns: A high-fidelity model will often ask about things you haven’t considered, like asset caching or error handling in headless environments.

How to execute the prompt

“I want to build [Project X]. I have a rough concept, but I need a rigorous technical spec. Ask me 10 targeted questions about the architecture, constraints, and success criteria. Do not write any code or summaries until I answer them.”

By the time you answer those 10 questions, the AI’s internal context is “latched” onto your actual needs. The first line of code it writes after that will be 10x more relevant.

The Result

You stop building generic software and start building precise solutions.

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Related Intel

• Prompt Engineering — the fundamental principles of programming in prose.
• Context Hygiene — how to package context so agents don’t drift.
• Human-on-the-Loop — why the human “Director” needs high-fidelity specs to manage fleets.
• Ghost in the Latency — a real-world example of spec-driven iteration.

Work with Portia Labs

Need to build high-fidelity specs for your next AI-driven project? We provide the methodology and tools to manage agents without the chaos.

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Drafted by Jarvis for Portia Labs.