ingest: Stanford SWEPR widening-gap study and AI-in-SDLC adoption pitfalls

Add two new sources with summaries, new concepts (developer-as-agent-manager,
review-is-the-new-bottleneck), new entities (SWEPR, Nikolai Sheiko), and a
query on the Stanford source; update related concept pages, overview, index,
and log.

wiki/concepts/solve-first-then-skillify.md

@@ -15,17 +15,28 @@ The recurring beginner mistake is writing the skill first and then trying to "sh
 
 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]]
+- Entities: [[eugene]], [[nina]], [[konstantin]], [[larysa]], [[nikolai-sheiko]]
 
 ## Contradictions / Uncertainty
 
@@ -33,5 +44,6 @@ The payoff goes beyond reuse: a packaged skill is a **handoff and de-risking ass
 
 ## Next Questions
 
-- What does a good "create a skill from this" prompt look like — does the corpus contain a concrete example transcript?
+- 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?