Skillability: The Art of Writing Context That AI Actually Uses
PMM Mindset · April 2026
Last week I wrote about Promptability — how well your product can be evaluated by AI agents.
This week: the other side of the equation.
Because even if your product is promptable, your writing might not be skillable.
What Is Skillability?
Skillability is the inverse of promptability.
Where promptability measures whether your product can be evaluated by AI, skillability measures whether your words can be used by AI.
More precisely: skillability is how efficiently a human can write context, prompts, and instructions that an AI agent actually uses — without waste, ambiguity, or misfires.
The gap is real: most people write for humans. AI doesn't read the same way. It processes tokens. And token efficiency isn't the same as writing quality.
The Token Problem
Every word costs tokens. Tokens cost money (or context window). And most writing is full of things that humans understand but AI wastes processing power on:
- -->Fluff: "As we've discussed extensively in previous meetings and as you well know..."
- -->Context debt: The background the human knows but the AI doesn't have
- -->Ambiguity: Words that mean different things to different people
- -->Formatting noise: Complex nested structures that look good but parse poorly
Skillable writing is lean writing. Not stripped of meaning — stripped of waste.
The Three Layers of Skillability
1. Context Efficiency
How much of your context is actually used vs. ignored?
The test: ask an AI to summarize what you told it. If the summary is missing key points, the AI didn't process them — or couldn't identify them as important.
Low context efficiency:
- -->Long preamble before the actual ask
- -->Buried constraints
- -->Implied context that should be explicit
High context efficiency:
- -->Lead with the question or task
- -->State constraints first
- -->Remove preamble entirely
2. Token Economy
How many tokens does it take to communicate your intent?
This isn't about writing short — it's about writing precise. A 200-word context that's 100% useful beats a 500-word context that's 40% useful.
Token-saving techniques:
- -->Use specific names, not descriptions ("Vercel" not "that cloud platform we use")
- -->State the output format explicitly ("in three bullet points, then one paragraph")
- -->Remove filler: every word should earn its tokens
3. Action Clarity
Can the AI identify what you're actually asking it to do?
"Make this better" is not an action. "Rewrite this for a skeptical engineer who thinks AI is overhyped" is an action.
Action clarity comes from:
- -->Specific audience definition
- -->Output format specification
- -->Constraint statements
- -->Example outputs (when possible)
A Skillability Audit
Test your writing with this simple exercise:
- -->Take any prompt or context you've written
- -->Strip all the preamble, greeting, and filler
- -->Ask: what actually needs to be there?
- -->Measure: what's the ratio of necessary words to total words?
Good skillable writing: 80%+ necessary Average writing: 50-60% necessary Typical enterprise copy: 30-40% necessary
Why PMMs Should Care
PMMs live in the gap between product and customer. We're constantly translating — product capabilities into customer language, customer problems into product requirements.
That translation work is increasingly AI-mediated. Your product descriptions become prompts. Your case studies become training context. Your messaging becomes the frame that shapes how AI understands your product.
If your writing isn't skillable, AI will use your competitors' writing instead.
The Skillability Checklist
Before you ship any context to AI:
- -->[ ] Is the task/question in the first sentence?
- -->[ ] Are constraints stated explicitly, not implied?
- -->[ ] Is the output format specified?
- -->[ ] Is the audience defined specifically?
- -->[ ] Can I strip 20% of words without losing meaning?
- -->[ ] Is there an example of the desired output?
Related
- -->The Promptability Score — How to grade whether AI agents can recommend your product