AI AdoptedBuilt 2026-06-21
A skill library should be your first AI strategy
A source note from the desk: synopsis, claims, relevance, caveats, and the original post preserved below for context.
Summary
A Twitter thread arguing that SMEs should prioritise building a skill library—a documented repository of proven ways of working—as their foundational AI strategy, rather than starting with data access. Shah makes the case that agents become useful not through broad knowledge but through learning how a specific company approaches its work. Read the full thread on X.
Key Claims
- AI agents need to understand how a company does its work, not just have access to data; without that understanding, agents can read all available information but still miss the shape of a decision.
- A skill is a reusable packet of procedure, judgment, and edge-case awareness that captures how experienced people approach repeated work, including instructions, examples, templates, checklists, and rules of thumb.
- The most valuable skills are private and company-specific because the most valuable methods are specific to each organisation; generic marketplace skills will exist but offer little advantage.
- SMEs should start by mapping repeated work where experienced people consistently outperform others—particularly tasks involving judgment rather than effort alone—then package those approaches as reusable skills.
- A company's AI advantage comes from teaching agents to do important work well, not from choosing the best model; two firms using the same frontier model will diverge dramatically if one has a skill library and the other does not.
Quotes
- "Agents are only useful when they understand more than the task itself. They need to understand the method behind it."
- "The playbook can become active." [in the context of agents being able to load and execute documented processes]
- "A company's AI advantage will come from the work it teaches the model to do well, rather than from the model it chooses."
- "Your company already has skills. They are sitting in old docs, Slack threads, customer calls, review rituals, onboarding notes, and the heads of the people who know how the work really gets done."