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/skills-as-memory.md

@@ -27,6 +27,7 @@ The **method** for populating skills is [[solve-first-then-skillify]]: reach the
 - ~3-message correction-loop heuristic; skills as the non-programmer ceiling (with CLAUDE.md) — [[2026-07-14-yulia-interview]].
 - Cross-session memory loss as the #1 practitioner pain; "memory is the worst thing agents have"; skills committed as the webinar remedy — [[2026-07-21-larysa-interview]].
 - Counter-evidence: no skills, no MCP, no slash commands at a 99%-AI-written company; `AGENTS.md` + codebase + rich prompt as the substitute — [[2026-07-28-agentic-engineering-10x-developer]].
+- **A second practitioner vote *for* the skills layer** (2026-07-30): [[nikolai-sheiko]]'s "Agentic Evolution" makes skill-building-plus-verification the difference between living on defaults and "vertical growth," and he flatly rejects embeddings/RAG over code ("don't use them unless you understand *very* well why") — siding with the load-on-activation camp in the skills-vs-RAG contradiction below. His verification protocol (context-free subagent re-solves the task from the skill alone) is the closest thing yet to the falsification test this page asks for — [[2026-07-30-rakes-in-ai-sdlc-adoption]].
 
 ## Related Pages
 
@@ -43,10 +44,10 @@ The **method** for populating skills is [[solve-first-then-skillify]]: reach the
   1. **Situational.** He works daily in *one codebase he controls*, where context can live in the code and `AGENTS.md`. Skills earn their keep when work is spread across many ad-hoc tasks with no codebase to encode into — which is exactly the corpus's HR/BA audience ([[nina]], [[yulia]], [[larysa]]). Under this reading both are right and the disagreement is about who is speaking.
   2. **The abstraction is premature.** Skills are scaffolding for models that needed it; a strong model plus a rich prompt plus a good repo may simply beat a skills library, making the whole layer a 2025 artifact. This is the uncomfortable reading for the webinar's central promise.
   3. **He has skills under another name.** AMP's Oracle/Painter/Puck sub-agents and a maintained `AGENTS.md` *are* curated, reusable, two-stage context — just authored by the vendor and the team rather than the user. Under this reading the dispute is about who curates, not whether curation is needed.
-  Status: tentative. Note the evidential asymmetry — his is a first-hand report of daily practice at scale, where the pro-skills case rests on Konstantin's architecture argument plus self-reported individual workflows. **Presentation-safe restatement:** [[2026-07-28-webinar-theses]] reframes the claim as *context you author beats context that's inferred*, which holds under all three readings — Konstantin's skills, Allie's foundation docs, Eugene's anti-memory position and Thorsten's `AGENTS.md` are all authored context.
+  Status: tentative. Note the evidential asymmetry — his is a first-hand report of daily practice at scale, where the pro-skills case rests on Konstantin's architecture argument plus self-reported individual workflows. *(Asymmetry softened 2026-07-30: [[nikolai-sheiko]] adds a second practitioner voice on the pro-skills side, from multi-company adoption work rather than one codebase — though his cases are anonymous anecdotes, so the readings above remain unsettled.)* **Presentation-safe restatement:** [[2026-07-28-webinar-theses]] reframes the claim as *context you author beats context that's inferred*, which holds under all three readings — Konstantin's skills, Allie's foundation docs, Eugene's anti-memory position and Thorsten's `AGENTS.md` are all authored context.
 
 ## Next Questions
 
 - ~~What's a starter skill set for a non-engineer?~~ Answered in [[2026-07-14-best-first-skill-for-beginner]] (skill-creator as meta-skill; tone-of-voice + anti-AI-language as first content skill).
 - Do skills actually solve *cross-project* context, or only per-procedure recall? Larysa's complaint may be the former, which skills don't obviously address.
-- Is there a test that would separate reading 1 from reading 2 above? The cheapest one available: give a non-engineer the same task with and without a skill and compare drift — the corpus has never run it, and the webinar's promise rests on the answer.
+- Is there a test that would separate reading 1 from reading 2 above? The cheapest one available: give a non-engineer the same task with and without a skill and compare drift — the corpus has never run it, and the webinar's promise rests on the answer. *(Adjacent evidence 2026-07-30: Sheiko's context-free-subagent protocol — [[solve-first-then-skillify]] — runs the with-skill half in practice, but never the without-skill control, so the question stands.)*