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.

raw/notes/Webinar script.md

@@ -638,6 +638,32 @@ Your harness is unique to you.
 
 You don't buy it. You build it — one small tool at a time.
 
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+And don't take my word for why this matters *now*.
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+Stanford measured it.
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+Their researchers tracked 46 teams working with AI — matched against 46 similar teams without it — for more than two years.
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+The teams that really learned it pulled away from the ones that just... had it.
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+In spring 2023, the spread between them was under five percent.
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+By summer 2025 — nineteen.
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+The gap quadrupled in two years. And the curve is still bending upward.
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+And remember — everyone had the same models the whole time.
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+The difference was never the model.
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+It was who built something around it.
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+_note: source — Stanford SWEPR, difference-in-differences analysis, Apr 2023 → Jul 2025 (see wiki/sources/2026-07-30-stanford-swepr-widening-gap.md). Honest caveats if asked in Q&A: talk-published, not yet peer-reviewed; measures software teams, not office workers; Stanford says "quality of usage" decides, without naming which practice._
+
+---
+
 We started this journey by pasting an email into a chat box.
 
 We're ending it with a button that already knows what the email said.