# V9 — State-of-the-Art Research (Metis: A Curious Ape's Guide to Reality) Status: research briefing that grounds `V9_PRODUCT_ANALYSIS.md`, `V9_features.md`, and `V9_ARCHITECTURE.md`. Date compiled: 2026-06-13. Audience: product, learning-science, generative-AI, science, and research leads scoping V9. This document captures the external state of the art for AI-powered educational content generation and "learn anything in a fun way" products as of mid-2026. Every architecture decision in `V9_ARCHITECTURE.md` cites a row here. The repo's "wire real data, no stubs" rule applies: these techniques are to be **implemented and composed**, not name-dropped. **Cutoff note.** The authoring model's knowledge cutoff is January 2026; this briefing was researched in June 2026. Items dated after January 2026 are flagged **[POST-CUTOFF]**. Claims that could not be verified against a primary source are flagged **[UNVERIFIED]** and must not be cited as fact. Several developments materially change V9's design relative to a Jan-2026 view — most importantly the **shutdown of OpenAI's Sora app** (do not build on it) and the **consumer launch of DeepMind's Project Genie**. --- ## 1. Source-grounded study assistants & multi-format generation The decisive 2026 lesson: **Socratic chat tutoring is commoditized; the differentiation has moved to grounded, multi-format, interactive generation.** | Technique / product | Source | What V9 takes from it | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **NotebookLM** — source-grounded generation into Audio Overviews (interruptible), Video Overviews, Mind Maps, flashcards + quizzes, infographics, slide decks; outputs restricted to _your_ sources, which is the antidote to hallucination. **[POST-CUTOFF]** 2026 adds: Cinematic Video Overviews (Mar 2026), 10 infographic styles (Mar 20 2026), grounded flashcards/quizzes with cross-session progress (Mar 2026), default Gemini 3.5 + secure code execution (Jun 2026). | blog.google / workspaceupdates.googleblog.com (2026) | The **grounding-first** principle (Aletheia G1) and the **multi-format output** model (text, audio, film, explorable). V9's wedge beyond NotebookLM: embodiment, _computed_ simulation, and a mastery loop — NotebookLM summarizes your docs; V9 guides you through reality. | | **Gemini Guided Learning** (LearnLM lineage, folded into Gemini 2.5; launched Aug 6 2025) — Socratic step-by-step tutoring with multimodal output (images, diagrams, videos, interactive quizzes). LearnLM is no longer a standalone model. | ai.google.dev/gemini-api/docs/learnlm ; blog.google (Aug 2025) | Confirms Socratic + multimodal is table-stakes; pedagogically-tuned models exist. V9 differentiates on grounding + embodiment + interactivity, not on "we have a tutor mode." | | **ChatGPT Study Mode** (Jul 29 2025) — Socratic scaffolding across Free/Plus/Pro/Team. **Key weakness:** runs on general ChatGPT, _not_ vetted sources, so it can present fabricated material. | technologyreview.com (Jul 2025); openai.com/index/chatgpt-study-mode | The cautionary tale that makes the **Aletheia gate non-negotiable**: an ungrounded tutor _will_ fabricate, and that is fatal for a learning product. Grounding is the moat. | | **Claude Learning Mode / Claude for Education** (Apr 2 2025; opened to all users Aug 2025) — Socratic "guide discovery, don't answer"; Claude Artifacts produce runnable interactive widgets in-chat. | anthropic.com/news/introducing-claude-for-education | The **generative-explorable primitive** (Artifacts) as the cheap path to on-demand interactivity (Hephaestus, §4), plus the integrity-mode discipline (Metis already has teach/hint/practice/do-not-complete). | | **Khanmigo / Khan Academy** — real mastery curriculum + GPT-4 coach. **[POST-CUTOFF]** Khan publicly admitted only **~15% of students with access use Khanmigo**, ran Oct 2025–Apr 2026 tests, and is shipping a 2026 redesign reoriented around **motivation, not just mastery**. | edtechinnovationhub.com (2026); blog.khanacademy.org (Jan 7 2026) | The **engagement constraint** is the binding one, not model quality. V9's game/awe/story craft is the structural answer to exactly the failure Khan named. | **Net rule for V9:** ground everything (NotebookLM's trust), tutor Socratically (commodity, but required), and win on the layer no incumbent unifies — _embodied + computed-interactive + mastery-tracked + awe-driven._ --- ## 2. Embodied teachers & accurate explainer video The critical constraint: **cinematic generative video models cannot reliably render accurate on-screen text, equations, or diagrams, and produce only short clips.** For real teaching, the viable paths are (a) script-driven avatars and (b) programmatic precise animation. | Technique / product | Source | What V9 takes from it | | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Synthesia 3.0** (Oct 1 2025) — Express-2 full-body avatars; **Video Agents** (real-time two-way interactive avatars). **[POST-CUTOFF]** $200M Series E at $4B (Jan 26 2026) funding the agentic rollout. Avatar reads _your_ script ⇒ no fabricated facts. | synthesia.io/post/synthesia-3-0 ; cnbc.com (Jan 26 2026) | Validates the **embodied-presenter** path for Chiron. V9's advantage: the script is grounded+computed (Aletheia), and the avatar is Oshun's own Psyche stack (cross-session memory, emotion-aware), not a SaaS talking head. | | **HeyGen** — **LiveAvatar** (real-time WebRTC avatar, BYO-LLM); **Avatar V** (studio-quality from ~15s of footage, performance/appearance separated). **[POST-CUTOFF]** Avatar V API ~$0.05/s, Custom Motion, HyperFrames (Apr–May 2026); legacy Interactive Avatar sunset Mar 31 2026. | heygen.com/blog (2026) | The **real-time conversational-tutor** pattern (Chiron live), and the proof that low-latency embodied dialogue is production-ready in 2026. | | **D-ID V4 Expressive Visual Agents** **[POST-CUTOFF]** (Mar 16 2026) — up to 4K, sub-0.5s latency, LLM-driven expressions, **inline interactive UI** (charts, forms, quizzes) overlaid on the avatar. | d-id.com/news (Mar 16 2026) | The **interactive-overlay** pattern: an embodied teacher with live charts/quizzes embedded — directly informs Chiron + Hephaestus integration. | | **Cinematic models — illustrative, not explanatory.** Veo 3.1 (Oct 15 2025; **[POST-CUTOFF]** 4K + free 720p tier ~Apr 2026) is best-in-class for _narrated B-roll_ with native audio. Runway Gen-4.5 (Dec 2025) for consistency. **Sora 2 (Sept 30 2025) — [POST-CUTOFF] app shut down Apr 26 2026, API winding down Sept 24 2026; Disney deal collapsed. DO NOT build on Sora.** Pika = social, not teaching. | developers.googleblog.com ; variety.com / en.wikipedia.org (Sora shutdown, 2026) | Cinematic models are a **component for illustrative scenes only** (provenance-stamped), never the teacher or the source of facts/equations. The Sora shutdown is a direct architectural warning: do not anchor a teaching product on a single cinematic video vendor. | | **Programmatic precise animation — Manim + LLM-to-Manim** (the only path to _accurate_ on-screen math/physics). **TheoremExplainAgent** (arXiv 2502.19400, ACL 2025 oral) plans+codes 5-min Manim explainers (o3-mini 93.8% on TheoremExplainBench/240 theorems). **[POST-CUTOFF]** Math-To-Manim agentic pipeline on "Claude Mythos"; ManiBench (arXiv 2603.13251, ~Feb 2026) measures visual-logic drift / syntactic hallucination; a 2026 training paper reports Qwen3-Coder-30B at 94% render-success **[UNVERIFIED figures]**. | arxiv.org/abs/2502.19400 ; manim.community ; github.com/HarleyCoops/Math-To-Manim | The **computed-correct explainer-film path** (V9 §9): for math/physics, generate Manim from the _verified_ Kalika derivation, not from free text. Reliability (render-success, visual-logic drift) is the known open problem ⇒ a validation/self-repair loop is mandatory (the Aletheia + G5 discipline). | **Net rule for V9:** Chiron is a **script-driven, grounded, embodied** teacher (Psyche/Synthesia-class), not a cinematic-video hallucination; STEM visuals are **computed** (Kalika→Manim, Nyx render), and cinematic clips are illustrative B-roll only, vendor-diversified. --- ## 3. Adaptive learning, ITS, and knowledge tracing Production SOTA is the decades-old, deployed-at-scale mastery paradigms (now with an LLM tutor bolted on), plus an active attention/Transformer + LLM knowledge- tracing research frontier. | Technique / product | Source | What V9 takes from it | | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Mastery engines in production** — ALEKS (Knowledge Space Theory; ALEKS-for-Calculus Sep 15 2025), Carnegie Learning MATHia (ACT-R cognitive tutor; CODiE 2025 winner Oct 22 2025), DreamBox, Duolingo Birdbrain (IRT/half-life regression + GPT-4 features). | mheducation.com ; carnegielearning.com ; blog.duolingo.com/birdbrain | The **mastery-engine-does-sequencing, LLM-does-conversation** split. V9's Mnemosyne plays the mastery/sequencing role; Chiron plays the conversational role. Duolingo is the **engagement bar** to clear. | | **Knowledge tracing lineage** — BKT (Corbett & Anderson 1994) → DKT (Piech 2015, LSTM) → attention/Transformer KT: **AKT** (KDD 2020, arXiv 2007.12324), **SAINT/SAINT+** (Riiid, EdNet, arXiv 2010.12042). **Critical caveat:** **pyKT** (NeurIPS 2022, arXiv 2206.11460) showed many deep-KT gains shrink under fair evaluation — AKT/DKT remain strong baselines; cross-paper AUCs are not comparable. | arxiv.org/abs/2007.12324 ; arxiv.org/abs/2206.11460 | V9's mastery model uses a **proven KT family (AKT-class)** as the backbone, evaluated honestly (pyKT discipline), not a fragile bleeding-edge claim. Mnemosyne already implements BKT/DKT-style tracing. | | **2025–26 KT frontier** — LLM-representation KT: **NTKT** (next-token KT, arXiv 2511.02599, v2 Jan 26 2026) for cold-start generalization; **HISE-KT** (arXiv 2511.15191) for _explainable_ KT; **FlatFormer** (arXiv 2512.06629, Dec 2025) efficient flat Transformer with forgetting-curve bias **[UNVERIFIED self-reported SOTA]**. | arxiv.org/abs/2511.02599 ; arxiv.org/abs/2511.15191 | The **cold-start** path (a new learner's first wonders) benefits from LLM-representation KT and from content-semantic embeddings (Sophia/Nous) — adopt cautiously, behind the AKT baseline, with honest evaluation. | | **Strongest causal efficacy evidence — human-AI hybrid.** Stanford **Tutor CoPilot** RCT (2024–25): +4 p.p. mastery (+9 p.p. for students of lower-rated tutors) at ~$20/tutor/yr. Fully-autonomous LLM tutors lack comparable causal evidence. | nssa.stanford.edu/studies/tutor-copilot | V9's **"escalate to a human"** path (Metis already supports human/hybrid tutor types) is evidence-based, not a fallback afterthought; the strongest results are hybrid. | **Net rule for V9:** a **proven mastery/KT backbone** (Mnemosyne, AKT-class, honestly evaluated) drives sequencing and the flow channel; the LLM (Chiron) does conversation; the human is an evidence-backed escalation, not a stub. --- ## 4. Generative interactive simulations, explorables & world models The "fun, interactive learning" frontier bifurcated by mid-2026 into (a) cheap, on-demand **LLM-generated explorables** and (b) heavyweight **world models** — with strong evidence that interactivity beats passivity for learning. | Technique / product | Source | What V9 takes from it | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **Explorable explanations lineage** — Bret Victor "Explorable Explanations" (2011) + "Ladder of Abstraction"; Nicky Case (explorabl.es, _Parable of the Polygons_); Distill.pub (dormant since 2021). The modern shift: **LLMs make explorables generatable on demand** (Claude Artifacts, ChatGPT Canvas → p5.js/three.js/React widgets). | worrydream.com/ExplorableExplanations ; explorabl.es ; distill.pub | The **explorable-on-demand** primitive is Hephaestus's cheap path: for any idea without a pre-built kernel, generate a runnable, _verified_ interactive widget. This is "the most under-exploited fun-learning primitive." | | **Peer-reviewed prompt-to-sim efficacy** — a 2026 physics-education study (Phys. Rev. PER; arXiv 2509.22929) found students who **generated their own simulations via AI prompting** reached conceptual understanding **equal to using pre-built sims**, and **both digital methods beat physical labs** (on electric potentials). | arxiv.org/pdf/2509.22929 | The **strongest academic validation** of V9's interactive pillar: generated, manipulable sims genuinely teach. Justifies investing in Hephaestus's generative-explorable path, not just hand-built kernels. | | **PhET Interactive Simulations** (CU Boulder, ~159 sims, billion+ uses) — the **correctness gold standard**, but a _finite hand-built library_ with no generative layer. | phet.colorado.edu | The **correctness bar** for explorables. V9's edge: Nyx/Kalika make our explorables _computed and correct_ (PhET-quality accuracy) **and** generative (beyond a finite library). | | **World models** — DeepMind **Genie 3** (Aug 5 2025, 720p/24fps, minutes-consistent navigable worlds); **[POST-CUTOFF] Project Genie** consumer launch Jan 29 2026 (AI Ultra, 60-sec sessions). Decart **Oasis 3** (Jun 10 2026, hours of photorealistic driving). World Labs **Marble** (persistent downloadable 3D worlds; $1B raise Feb 2026). | deepmind.google/blog/genie-3 ; the-decoder.com (Jan 29 2026); worldlabs.ai | World models are a **P2/P3 horizon** for immersive explorables, _not_ a P1 dependency: they are not accurate enough for STEM facts/equations and sessions are short. V9's P1 explorables are computed (Nyx/Kalika) + generative-widget, which are correct _today_. | **Net rule for V9:** P1 interactivity = **computed kernels (Nyx/Kalika) + verified generative widgets** (correct _and_ on-demand); world models are a later immersive layer, never the source of factual accuracy. --- ## 5. Learning-science backing (canonical, citable) V9's pedagogy implements established research, most of which **Mnemosyne already encodes** (`libs/mnemosyne/`). All citations independently verified against primary/DOI records; caveats are stated, not buried. | Principle | Canonical source | What V9 does with it | Honest caveat | | --------------------------------------- | ------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------- | | **Bloom's 2-sigma** | Bloom (1984), _Educational Researcher_ 13(6), DOI:10.3102/0013189X013006004 | Aspiration for one-to-one mastery tutoring at near-zero marginal cost (Chiron + Mnemosyne). | **Never replicated at full 2σ**; real tutoring meta-effects ≈ 0.3–0.4σ (Nickow/Oreopoulos/Quan 2020). Cite as aspiration, not promise. | | **Mastery learning** | Bloom (1968), "Learning for Mastery"; Kulik (1990) meta-analysis | Mnemosyne mastery gates: advance on demonstrated mastery, time variable. | ~+0.5σ in meta-analysis; ~1σ in Bloom's framing. | | **Spaced repetition** | Ebbinghaus (1885); Cepeda et al. (2006), _Psych. Bulletin_ 132(3) | FSRS/SM-2 scheduling in `libs/mnemosyne/core` — review just before forgetting. | Robust across 1,300+ effect sizes. | | **Retrieval practice / testing effect** | Roediger & Karpicke (2006), _Psych. Science_ 17(3), DOI:10.1111/j.1467-9280.2006.01693.x | Every lesson ends in active recall, not re-reading (G3, the Mnemosyne checkpoint). | 1-week recall ~61% (tested) vs ~40% (restudy). | | **Cognitive load theory** | Sweller (1988), _Cognitive Science_ 12(2), DOI:10.1207/s15516709cog1202_4 | Prometheus scopes each lesson to the prerequisite frontier (Atlas) to minimize extraneous load. | Intrinsic/extraneous/germane triad is from the 1990s (Sweller/van Merriënboer/Paas 1998), not the 1988 paper. | | **Desirable difficulties** | Bjork (1994); Bjork & Bjork (2011) | Interactives withhold answers until the learner predicts; spacing/interleaving by design. | "Desirable" only if the learner has the background — hence Atlas scoping. | | **Flow** | Csikszentmihalyi (1990), _Flow_ | Mnemosyne knowledge-tracing tunes difficulty into the challenge-skill flow channel. | Flow needs high challenge matched by high skill (between anxiety and boredom). | | **Awe & learning** | Keltner & Haidt (2003), _Cognition & Emotion_ 17(2), DOI:10.1080/02699930302297; Keltner (2023), _Awe_ | The Theia/beauty pillars as a deliberate awe→curiosity engine. | Awe → curiosity/openness is supported; awe → measured learning gains is suggestive, **not** RCT-proven. Design for it; don't oversell. | --- ## 6. What the landscape tells us about V9's scope - **No incumbent unifies the five pillars.** NotebookLM grounds but doesn't embody or simulate; Synthesia/HeyGen embody but don't ground or simulate; PhET simulates but doesn't generate; Khan tutors but can't engage; world models generate worlds but aren't accurate. V9's novelty is **composition**, exactly as V8's novelty was composition. - **Engagement and trust are the binding constraints, not model quality.** Khan's ~15% admission (trust-of-attention) and Study Mode's fabrication risk (trust-of-truth) are the two failures V9's two structural bets (delight + the Aletheia gate) directly target. - **Grounding + computation is the moat.** The only durable defense against the fabrication that plagues open tutors is binding claims to sources (Sophia) and computing values with real kernels (Nyx/Kalika) — capabilities the monorepo already has and a wrapper-of-an-LLM competitor does not. - **Build P1 on what is correct today.** Computed kernels + verified generative widgets + script-driven embodied avatars are production-ready and accurate in 2026; world models and cinematic video are illustrative/immersive layers for later, never the factual core. The Sora shutdown is the cautionary tale for over-anchoring on a single generative-video vendor. **Bottom line:** every component V9 needs has a published, working 2026 precedent, and most exist in the Oshun monorepo already. The work is integration, grounding, and the consumer experience — not invention. --- ## Sources AI study assistants & grounded generation - NotebookLM 2026 features — https://workspaceupdates.googleblog.com/2026/03/new-ways-to-customize-and-interact-with-your-content-in-NotebookLM.html ; https://techcrunch.com/2026/06/08/notebooklms-new-update-will-help-you-build-source-repository-from-chat/ - Gemini Guided Learning / LearnLM — https://blog.google/outreach-initiatives/education/guided-learning/ ; https://ai.google.dev/gemini-api/docs/learnlm - ChatGPT Study Mode — https://www.technologyreview.com/2025/07/29/1120801/openai-is-launching-a-version-of-chatgpt-for-college-students/ ; https://openai.com/index/chatgpt-study-mode/ - Claude for Education — https://www.anthropic.com/news/introducing-claude-for-education - Khanmigo engagement / 2026 redesign — https://www.edtechinnovationhub.com/news/only-15-percent-of-students-with-access-to-khanmigo-actually-use-it-khan-academy-admits ; https://blog.khanacademy.org/khan-academy-reimagined-for-districts-2026/ Embodied teachers & explainer video - Synthesia 3.0 / Series E — https://www.synthesia.io/post/synthesia-3-0 ; https://www.cnbc.com/2026/01/26/nvidia-alphabet-vc-arms-back-synthesia.html - HeyGen 2026 — https://www.heygen.com/blog/heygen-may-2026-release ; https://www.heygen.com/blog/announcing-avatar-v - D-ID V4 — https://www.d-id.com/news/v4-expressive-visual-agents-real-time-llm-connected-interaction/ - Veo 3.1 — https://developers.googleblog.com/introducing-veo-3-1-and-new-creative-capabilities-in-the-gemini-api/ - Sora 2 shutdown — https://en.wikipedia.org/wiki/Sora_(text-to-video_model) ; https://variety.com/2026/digital/news/openai-shutting-down-sora-video-disney-1236698277/ - TheoremExplainAgent — https://arxiv.org/abs/2502.19400 ; Manim — https://www.manim.community/ ; Math-To-Manim — https://github.com/HarleyCoops/Math-To-Manim ; ManiBench — https://arxiv.org/html/2603.13251 ; Manimator — https://arxiv.org/html/2507.14306v1 Adaptive learning, ITS, knowledge tracing - ALEKS — https://www.mheducation.com/about-us/news-insights/press-releases/mcgraw-hill-releases-ai-powered-aleks-for-calculus.html ; https://www.aleks.com/about_aleks/knowledge_space_theory - Carnegie Learning — https://www.businesswire.com/news/home/20251022158855/en/Carnegie-Learning-Wins-CODiE-Awards-for-MATHia-and-Patterns - Duolingo Birdbrain — https://blog.duolingo.com/birdbrain/ - AKT — https://arxiv.org/abs/2007.12324 ; SAINT+ — https://arxiv.org/abs/2010.12042 ; pyKT — https://arxiv.org/abs/2206.11460 - NTKT — https://arxiv.org/abs/2511.02599 ; HISE-KT — https://arxiv.org/abs/2511.15191 ; FlatFormer — https://arxiv.org/abs/2512.06629 - Tutor CoPilot — https://nssa.stanford.edu/studies/tutor-copilot-human-ai-approach-scaling-real-time-expertise Interactive sims, explorables, world models - Explorable Explanations — https://worrydream.com/ExplorableExplanations/ ; https://explorabl.es/ ; https://distill.pub/2020/communicating-with-interactive-articles/ - Prompt-to-sim physics efficacy — https://arxiv.org/pdf/2509.22929 - PhET — https://phet.colorado.edu/ - Genie 3 / Project Genie — https://deepmind.google/blog/genie-3-a-new-frontier-for-world-models/ ; https://the-decoder.com/google-deepmind-opens-project-genie-to-us-subscribers-for-real-time-ai-world-generation/ - Decart Oasis 3 — https://techcrunch.com/2026/06/10/decarts-new-world-model-can-simulate-hours-of-photorealistic-driving-with-some-caveats/ - World Labs Marble — https://www.worldlabs.ai/blog Learning science - Bloom 2σ — https://doi.org/10.3102/0013189X013006004 ; 2-sigma critique — https://www.educationnext.org/two-sigma-tutoring-separating-science-fiction-from-science-fact/ - Mastery learning — https://eric.ed.gov/?id=ED053419 - Retrieval practice — https://doi.org/10.1111/j.1467-9280.2006.01693.x - Cognitive load — https://doi.org/10.1207/s15516709cog1202_4 - Flow — Csikszentmihalyi (1990), _Flow_, ISBN 9780060162535 - Awe — https://doi.org/10.1080/02699930302297 ; Keltner (2023), _Awe_, ISBN 9781984879684 --- ## Verification caveats - **Independently verified (primary/official sources):** Sora 2 shutdown (Apr 26 2026 app / Sept 24 2026 API); Synthesia 3.0 + Series E; D-ID V4; HeyGen 2026 releases; NotebookLM 2026 features; ChatGPT Study Mode; Claude for Education; Gemini Guided Learning; Genie 3 + Project Genie; Decart Oasis 3; TheoremExplainAgent; and all pedagogy + KT baseline citations. - **Flagged [UNVERIFIED] — do not present as fact:** FlatFormer/DenoiseKT self-reported SOTA; the 2026 Manim training-paper render-success figures; Squirrel AI 2025–26 corporate/efficacy specifics; any "Genie 4"; exact Veo 3.1 4K/length specs; HeyGen "Avatar 5"/15-second-training claim. Several 2026 arXiv IDs (26xx prefixes) are recent and were not all fetched in full. - This briefing executed no pipeline; product-side capability judgments are cross-referenced to `V9_GAP_ANALYSIS.md` (source reads), not to checkbox ledgers.