How do you manage skills files?: SKIP, 35/100 | Ideas Lab

A management system for organizing and maintaining LLM prompt skills/templates until AI models make them obsolete.

The pain

People using LLMs are accumulating prompt templates and techniques (skills) across multiple places, notebooks, GitHub repos, Discord servers. They lose track of what works, can't easily find the right prompt for a task, and don't have a systematic way to test if their prompts still work as models update.

The gap

No dedicated tool exists for version control, organization, and validation of prompt templates. Existing solutions are either too generic (note apps, GitHub) or too narrow (single-use prompt libraries). The founder acknowledges this is temporary, models will eventually absorb these capabilities, which limits the addressable market size and exit potential.

Build angle

Start by validating whether people actually experience this as a painful problem worth paying for. Interview 20-30 power users of Claude/GPT who maintain prompt libraries. Measure: Do they spend meaningful time searching for prompts? Do they lose prompts? Do they test prompts after model updates? If yes, build a lightweight tool that combines tagging, search, version history, and a simple test runner. Position it as a bridge tool, not a permanent solution.

Strengths

Real problem for active LLM users, prompt management is genuinely scattered today
Low technical complexity to build an MVP
Founder has honest perspective about market lifespan
Could integrate with existing workflows (VS Code, browser extensions)

Risks

Founder's own thesis undermines the business, if skills become obsolete, why build it? This signals low conviction and makes fundraising/hiring difficult
Market size is small and shrinking. Only power users maintain large prompt libraries; most people use 3-5 prompts repeatedly
High churn risk. As models improve, the need for manual prompt engineering decreases monthly
No clear monetization path. Hard to charge for a tool people view as temporary
Competitive threat from LLM platforms themselves adding native prompt management (OpenAI, Anthropic could ship this in weeks)
Requires ongoing maintenance as models change, but declining revenue makes this unsustainable

Fly Labs Method

Is the pain real, is there a gap, is it the right time, can one person build it.

35

Value Equation

Dream outcome and how likely it feels, against the time and effort it costs.

28

One-Person Business

Curiosity pull, identity fit, and a path from free value to paid for a solo creator.

42

Viral Frameworks

Hook strength, shareability, and how cheaply it can be tested.

38

Builder Lens

Evidence the problem exists, timing, defensibility, and a model that fits on a napkin.

31

Five lenses, one composite. How scoring works

The angle

Start by validating whether people actually experience this as a painful problem worth paying for. Interview 20-30 power users of Claude/GPT who maintain prompt libraries. Measure: Do they spend meaningful time searching for prompts? Do they lose prompts? Do they test prompts after model updates? If yes, build a lightweight tool that combines tagging, search, version history, and a simple test runner. Position it as a bridge tool, not a permanent solution.

No market research recorded for this idea yet.

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