# Solve First, Then Skill-ify

#concept

## Summary

The core method both HR interviews teach: **don't build a skill speculatively — solve the task with the AI once, correct it until the output is right, then say "now create a skill from this."** The skill freezes a *proven* workflow, not a guess about one.

## Current Understanding

The recurring beginner mistake is writing the skill first and then trying to "shove it somewhere." The working loop is: do your real task through the AI → watch the result → correct it → freeze the final state into a reusable skill. Two trigger heuristics exist in the corpus:

- **Eugene:** turn any correction loop longer than **~3 messages** into a skill.
- **Konstantin:** auto-create a skill after **>5 tool calls** on a task (the [[hermes]] curator variant).

The payoff goes beyond reuse: a packaged skill is a **handoff and de-risking asset** — "a person with not even a third of your HR experience can deliver a decent result," which cuts onboarding and lets the expert take a vacation. This is how [[skills-as-memory]] gets *populated* in practice — the method side of that architecture, and the fix for "don't teach the AI abstractly."

**Agentic Evolution — the strongest formulation, plus the missing verification step** (added 2026-07-30). [[nikolai-sheiko]] frames the same method as onboarding an employee: asking the expert "how do you do this?" yields theory; instead **take the new employee (the agent) by the hand through hard real tasks, show it the rakes, then say: "remember all of this and write the manual for the next one."** Without this you live on defaults; with it "vertical growth begins." He then adds what the corpus's earlier heuristics lacked — a **verification protocol** for the frozen skill:

1. Write the skill together with the agent.
2. Don't go to lunch.
3. Launch a **subagent with no context** — it must solve the same task from scratch using only the skill.
4. The main agent watches what fails and fixes the skill.
5. The mentor agent thus onboards the next agent.

This is the first source to describe actually *running* something close to the skills falsification test proposed on [[skills-as-memory]] (same task, with-skill vs from-scratch) — though it tests the skill's completeness for one task, not whether the skill beats no-skill. His do-tomorrow extension: a skill that analyses your own sessions daily, automated via schedules/routines — evolution as a standing loop rather than a one-time freeze.

## Evidence

- "You first solve a task with Claude; the moment you reach the final solution, you say — now create a skill from this"; ~3-message heuristic — [[2026-07-14-yulia-interview]].
- Do-the-task-then-freeze framing; skill-as-handoff to a junior hire; vacation/de-risking angle — [[2026-07-14-nina-interview]].
- >5-tool-calls auto-creation heuristic and curator pruning — [[2026-07-14-skills-based-on-git]].
- Skills prescribed specifically as the workaround for cross-session memory loss, and as the constraint on drift — [[2026-07-21-larysa-interview]].
- Agentic Evolution (walk the agent through tasks → have it write the manual); the context-free-subagent verification protocol; session-analysis skill as a daily loop — [[2026-07-30-rakes-in-ai-sdlc-adoption]].

## Related Pages

- Concepts: [[skills-as-memory]] (the architecture this method feeds), [[levels-of-ai-usage]] (skills are the top practical rung), [[personal-ai-operating-system]], [[leave-less-room-for-imagination]] (why a *proven* spec beats a written-ahead one)
- Entities: [[eugene]], [[nina]], [[konstantin]], [[larysa]], [[nikolai-sheiko]]

## Contradictions / Uncertainty

- Whether the resulting skill is personal IP or employer work product is unresolved (Eugene vs [[sebastian]]) — [[2026-07-14-nina-interview]].

## Next Questions

- What does a good "create a skill from this" prompt look like — does the corpus contain a concrete example transcript? *(Partially answered 2026-07-30: Sheiko's "remember all of this and write the manual for the next one" after a guided run is the best prompt-shape the corpus has.)*
- How do the ~3-message and >5-tool-call heuristics compare in practice; is one strictly better for non-programmers?
- Does the context-free-subagent check catch skill *quality*, or only completeness for the one task it was frozen from?