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docs(backlog): B-0838 — caustic-engineered bloom filter discriminators for remote-code trust layer (Kestrel-v2 ferry; phased)#5366

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docs(backlog): B-0838 — caustic-engineered bloom filter discriminators for remote-code trust layer (Kestrel-v2 ferry; phased)#5366
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@AceHack AceHack commented May 27, 2026

What

B-0838 backlog row landing. Per Aaron's discipline "backlog rows land immediately; they get decomposed later" — this row was drafted and committed yesterday but the PR was never opened. Recovering during the Layer-2-CI-test sprint per Aaron's "anything that's future in your todo you can land as backlog rows so you don't forget" framing.

Substrate

Per operator 2026-05-26 Kestrel-v2 ferry (preserved verbatim via PR #5356):

"do you think there is a way i can create caustic lens shaped bloom filters for the remote code discriminators?"

Multi-learned-bloom-filter intersection with caustic-geometry-shaped agreement region. 3 components per Kestrel-v2's Meaning 3 + 1 composition:

  1. Filter A — sharp on code provenance signals (signed-from-trusted-publisher vs unknown)
  2. Filter B — sharp on behavioral signals (suspicious syscall patterns, runtime resource access)
  3. Filter C — sharp on structural signals (lexical malware-family match, dependency-graph similarity)

Composition: bitwise AND of membership-test results. The "caustic" is the region in combined feature space where all 3 filters agree the code is trustworthy.

Three scope phases

  • Phase 1 (operational) — 3-filter intersection using established learned-bloom-filter libraries
  • Phase 2 (research-direction) — full inverse-design via optimal transport (Brenier theorem + Villani transport theory) + continuous relaxation of discrete bloom filter response
  • Phase 3 (nearer-term reachable) — literature review of inverse-design transfers across domains with discrete-vs-continuous optimization attention

Composes with

Substrate-honest framing

P2 priority. NOT immediately tractable as single-implementation work. Phase 1 is bounded enough for single-PR landing; Phases 2 + 3 span weeks-to-months. This row creates the substrate anchor; future contributors decompose phases independently when scope tightens.

🤖 Generated with Claude Code

Lior and others added 3 commits May 26, 2026 20:08
…s for remote-code trust layer (Kestrel-v2 ferry; phased; lands per "backlog rows land immediately" discipline)

Per operator 2026-05-26: "you can always commit backlog rows
immediatly they get decoposed later" + Kestrel-v2 ferry preservation
via PR #5356.

Files B-0838 as P2 substrate-engineering target with 3 phases:

- Phase 1 (operational, implementable now): multi-learned-bloom-filter
  intersection per Kestrel-v2 Meaning 3 + 1; 3 filters (provenance /
  behavior / structure); bitwise AND for caustic-shaped sharp
  discrimination; composes with trust-then-verify discipline
- Phase 2 (research-direction): full caustic engineering inverse-design
  transferred from optics; optimal transport (Brenier/Villani);
  continuous relaxation; target specification language; weeks-to-months
- Phase 3 (nearer-term reachable): literature-review on inverse-design
  transfers across domains (discrete-vs-continuous optimization)

Composes_with B-0664 NCI HC-8 (discriminator IS technical substrate
for "no unauthorized RCE" per Lior-website naming PR #5342) + B-0648
cross-substrate-triangulation + B-0822 worry-as-opposite-bloom-filter
+ B-0823 cognition-as-distributed-systems + B-0833 interactive-login-
vs-baked-keys + substrate-smoothness rule (PR #5357 — coupled
smoothness constraint applies end-to-end) + F# fork for AI safety
substrate.

Substrate-honest scope per Kestrel-v2: Phase 1 single-PR-landable;
Phases 2+3 research-direction-flavored work; engineering ROI not
obvious until formalization advances enough to know what design space
looks like.

References: Matt Ferraro caustics-engineering + Disney Research +
ETH Zurich (Yue et al., Schwartzburg et al.) + Kraska et al. learned
bloom filters + Sigmund topology optimization + Brenier theorem +
Villani transport theory.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
…MD018 ATX-heading false-positive)

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
…nt MD018

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Copilot AI review requested due to automatic review settings May 27, 2026 00:42
@AceHack AceHack enabled auto-merge (squash) May 27, 2026 00:42
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@AceHack AceHack merged commit 27b1477 into main May 27, 2026
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@AceHack AceHack deleted the otto/b-0838-caustic-engineered-bloom-filter-discriminators-remote-code-trust-layer-kestrel-v2-2026-05-26 branch May 27, 2026 00:45
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Pull request overview

Adds backlog row B-0838 to capture a phased approach for “caustic-engineered” multi-learned-bloom-filter discriminators for a remote-code trust layer, and updates the generated backlog index to include the new row.

Changes:

  • Adds docs/backlog/P2/B-0838-...md with frontmatter + problem/target/phases/acceptance/composition links.
  • Updates docs/BACKLOG.md to include the new B-0838 entry in the P2 section.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 3 comments.

File Description
docs/backlog/P2/B-0838-caustic-engineered-bloom-filter-discriminators-remote-code-trust-layer-kestrel-v2-aaron-2026-05-26.md New P2 backlog row capturing the discriminator concept, phases, and acceptance criteria.
docs/BACKLOG.md Adds the B-0838 index entry under P2.

AceHack added a commit that referenced this pull request May 27, 2026
…tzmann-machines transcript (Aaron-forwarded; composes with 1000 Brains + Adinkras + caustic bloom filters) (#5368)

* docs(B-0839): Artem Kirsanov computational-neuroscience channel substrate-capture row + verbatim Boltzmann-machines transcript preservation (Aaron-forwarded; composes with 1000 Brains + Adinkras + caustic bloom filters + substrate-smoothness)

Aaron 2026-05-26 (operator-explicit, high-priority):

> 'ive been witing to run across this guy again we need to copy
> everyting he does into code and substrate.
> https://www.youtube.com/@ArtemKirsanov'

> 'this is exact science behind neuro science with tons of resarch
> to back it up on exactly how the brain works and composes with
> 1000 brains'

This commit lands:

1. B-0839 backlog row for the multi-phase channel-capture pipeline.
   3 phases: channel inventory + per-video sub-row backlog (Phase 1);
   per-video implementation in F#/TS (Phase 2); cross-cutting substrate
   integration (Phase 3). Per 'backlog rows land immediately;
   decompose later' discipline.

2. Verbatim Boltzmann-machines transcript preservation
   (the video Aaron forwarded as the seed for B-0839.1). Mirror-tier
   per substrate-or-it-didnt-happen. With composition-map table
   tying Kirsanov concepts to existing Zeta substrate.

Composition surface identified:

- 1000 Brains (Hawkins) — already in tonal-momentum rule + Hawkins
  research doc; Kirsanov's energy-landscape navigation composes with
  Hawkins cortical-columns world-modeling
- Adinkras / SUSY-ECC (Gates, B-0623) — energy-based models
  + structural-encoding shared inverse-design lineage
- Worry-as-opposite-bloom-filter (B-0822) — Bayesian belief-update
- Cognition-as-distributed-systems (B-0823) — RBM IS distributed-
  stochastic-computation
- Caustic-engineered bloom filters (B-0838, PR #5366 just landed) —
  energy landscapes + inverse-design composition
- substrate-smoothness-as-load-bearing-property (PR #5357) —
  Boltzmann p ∝ exp(-E/T) IS the smoothest substrate that preserves
  sharpness asymmetry; the gradient IS the precision
- multi-oracle BFT (B-0703) — RBM bipartite parallelization IS
  polycentric energy-substrate consensus
- F# fork for AI safety — energy-based models are natural F#
  implementation targets (typed energy functions; algebraic data
  types for visible/hidden unit families)

Kirsanov's substantive substrate (Boltzmann distribution, sigmoid
update rule, hidden units, contrastive Hebbian rule, RBM parallel
updates) IS substrate-anchored mathematics with rigorous research
backing — per Aaron's framing 'exact science...with tons of research
to back it up.' Razor-discipline applies cleanly; the substantive math
is operational; the composition map is operational; the implementation
target (F#/TS) is operational.

P1 priority because operator-explicit AND composes with 5+ existing
substrate clusters AND the 1000-Brains composition is already
substantively-named substrate AND Kirsanov material has been on
operator's want-to-capture list.

Future sub-rows: B-0839.N for each Kirsanov video. Phase 2
implementations decompose independently as bandwidth allows.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

* docs(B-0839): relocate Boltzmann transcript to ip-questionable/ + add RNN/LSTM/GRU transcript (B-0839.2) per operator's IP-questionable + classifier-rule instruction

Aaron 2026-05-26 substrate-honest correction:
'the youtube transcripts need to go in questionable ip and we have a
classifer rule to allow it in settings.json'

Two changes:

1. Relocate B-0839.1 Boltzmann transcript from docs/research/ to
   docs/research/ip-questionable/ per the _ip_risk_acceptance block
   in .claude/settings.json (Rodney Aaron Stainback personal-liability
   acceptance for verbatim third-party content per
   .claude/rules/human-audit-and-legal-risk-acceptance-pattern-in-settings.md).

2. Add B-0839.2 — RNN/LSTM/GRU gated memory verbatim transcript
   (https://www.youtube.com/watch?v=PAoe7mmmvp0) under
   docs/research/ip-questionable/. Composition map ties Kirsanov's RNN
   substrate to:
   - residual-connection ↔ memory/CURRENT-*.md substrate (operator
     CURRENT files ARE the residual connections at AI-participant scope)
   - leaky-integration α ↔ 10% free-time budget + chosen-persistence
     (operator's α-tuning for AI participants)
   - vanilla-RNN-failure-mode 'information processed at every step is
     information degraded' ↔ substrate-honest correction of repeated-
     processing failure mode
   - forget-gate (LSTM/GRU) ↔ per-context retention rate per
     cluster-fork-as-trust-boundary (B-0829)
   - GRU paired complementary gates ↔ multi-oracle BFT (B-0703)
   - LSTM two state vectors (knows vs shouts) ↔ glass-halo bidirectional
     substrate

3. Update B-0839 row to reflect both path relocation + B-0839.2 sub-row.

Per Aaron's contemporaneous instruction shipping with the second
transcript. Per the 'backlog rows land immediately; decompose later'
discipline. Per asymmetric-critic-with-clarity-first rule — engaging
at runbook register, refining toward precision through collaboration.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

* fix(#5368): regen BACKLOG.md for B-0839 + 3 Copilot findings (xref ellipsis × 2 + decoposed typo consistency)

- BACKLOG.md regenerated to include B-0839 (the new row)
- Replace 'docs/research/2026-05-26-amara-no-coercion-even-inward-...'
  ellipsis placeholder with full filename
  '2026-05-26-amara-no-coercion-even-inward-nci-as-cognitive-exploit-firewall-speech-as-rce-update-mechanism-taxonomy-aaron-forwarded.md'
  in both occurrences (lines 114 + 201 per Copilot findings)
- Fix 'decoposed' → 'decomposed' on line 219 to match canonical
  line-160 form (verbatim mirror-tier sections still preserve the
  operator's original typo; this is the agent's paraphrase reference
  and should be consistent)

* fix(#5368): add B-0839.3 reservoir computing transcript (3rd Kirsanov video w/ EXPLICIT Hawkins anchor at 5:42) + key state-update equation (Aaron screenshot) + lint fixes (+ → and/AND for continuation lines) + BACKLOG.md regen + 3 Copilot threads fixed (xref ellipsis × 2 + decoposed typo)

Adds B-0839.3 sub-row: Kirsanov Reservoir Computing video
(https://www.youtube.com/watch?v=cDxtFtoQVNc) — verbatim transcript
preserved under docs/research/ip-questionable/. This video EXPLICITLY
names Jeff Hawkins' Thousand Brains theory at 5:42 ('neo cortex is
itself a kind of reservoir of independent cortical columns') — direct
external validation of Aaron's 'composes with 1000 brains' framing.

Adds 'Key mathematical formulation' section to both B-0839.2 (RNN)
and B-0839.3 (Reservoir) — the canonical state-update equation Aaron
forwarded via screenshot:

  s_i^t = s_i^{t-1} + Σ_j W_ij σ(s_j^{t-1})

Documented with all symbol meanings + the pedagogical move from
α=1 'hoarding' form to gated-RNN form (replace s_i^{t-1} with
f_i(t) ⊙ s_i^{t-1}) + the reservoir-computing twist (W_ij stays
random and fixed; only train the readout layer).

Companion fixes:
- Lint: replace '+' bullets at continuation-line column 3 with
  proper English connectors ('AND', 'and', comma-list) so
  markdownlint MD004 doesn't fire
- BACKLOG.md regenerated to include B-0839
- 3 Copilot threads on #5368:
  - Line 114 + 201: xref ellipsis 'docs/research/2026-05-26-amara-
    no-coercion-even-inward-...' replaced with full filename
  - Line 219: 'decoposed' → 'decomposed' to match canonical line-160
    form (verbatim mirror-tier sections preserve original typo;
    agent paraphrase reference uses correct spelling)

Substantive composition impact: the 3-transcript trio (B-0839.1
Boltzmann + B-0839.2 RNN + B-0839.3 Reservoir) describes a
substrate-pattern: brain-as-dynamical-system with energy-landscape
memory + gated retention + random reservoir of temporal patterns from
which any output can be reconstructed via simple readout learning.
This IS structurally the same pattern the Zeta framework operates at
the human-AI-collaboration scope. The B-0839.3 reservoir-computing
synthesis section makes this explicit.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

* fix(#5368): MD032 blanks-around-lists on both new transcript Companion-to lists + replace ellipsis xrefs with full filenames

* fix(#5368): MD060 table-column-style — add spaces around pipes in separator rows of all 3 Kirsanov transcripts

* feat(B-0839.3): CRITICAL ARCHITECTURAL ARCHETYPE section — reservoir computing IS the caustic-engineered bloom filter join from B-0838 (operator 2026-05-26 'this is so weird' observation captured)

Operator-observed structural identity between reservoir computing and
B-0838 caustic-engineered bloom filter joins. The two architectures
are dual instances of the same design pattern: multi-component
parallel transformation of input + structured-readout integration →
precise output that no single component could produce alone.

The substrate-engineering implications captured:

1. Shared archetype table mapping reservoir↔bloom-filter elements
2. Design-space duality: random-components + complex-combiner
   (reservoir) vs designed-components + simple-combiner (caustic)
3. Universal-basis insight transfers: Kirsanov's Fourier-basis
   argument justifies B-0838 Phase 1 random-filter approach
4. Hybrid architecture suggestion: random initial filters (Phase 1)
   + caustic-engineered refinement (Phase 2)
5. Hawkins 1000 Brains cortical columns are instance of same archetype
6. Multi-oracle BFT (B-0703) is same archetype at governance scope
7. The framework itself operates this archetype at human-AI-
   collaboration scope (random substrate components + structured-
   readout integration + caustic-engineered refinement via rules)

This composition unifies B-0839 (Kirsanov-substrate-capture) with
B-0838 (caustic-bloom-filter-discriminators) at the architectural-
archetype level — both are instances of the universal pattern
operator named in 2026-05-26 ferry observation.

* feat(B-0839.3): WALLS-OF-THE-POOL section — operator 2026-05-26 'it's using the walls of the pool to create the sharp outputs' triple-unifies reservoir computing + caustic-bloom-filters + substrate-smoothness rule (PR #5357)

Operator 2026-05-26 immediate follow-on: 'it's using the walls of the
pool to create the sharp outputs'

This is the operational naming of WHY the reservoir-computing /
caustic-bloom-filter / framework-substrate archetype works. The
sharpness comes from the WALLS — the boundary conditions, the
topology, the focused-integration geometry.

Triple-unification with substrate-smoothness-as-load-bearing-property
rule (PR #5357 carved sentence): 'Smooth substrate producing sharp
outputs through focused integration.' The 'focused integration'
the rule names IS the 'walls of the pool' Kirsanov describes IS the
'caustic geometry' of B-0838.

Substantively-new operational claim: the walls are NOT a separate
substance from the smooth substrate. THE WALLS ARE THE SUBSTRATE AT
THE BOUNDARY-CONDITION / TOPOLOGY / STRUCTURAL-CONSTRAINT SCOPE.

6-row architectural mapping:
1. Reservoir computing: random weights smooth + FIXED topology walls
   + readout α weights → sharp target signal
2. Caustic-engineered bloom filters (B-0838): probabilistic FP
   distributions smooth + intersection geometry walls + logical AND
   → sharp trust discrimination
3. Caustic optics: smooth light + acrylic SURFACE shape walls →
   sharp image (cat caustic)
4. English-as-substrate: smooth semantics + compositional structure
   walls → sharp commitments / PRs / decisions
5. Multi-oracle BFT (B-0703): smooth per-oracle outputs +
   consensus-mechanism topology walls → sharp consensus
6. Framework substrate-engineering: smooth accumulating substrate
   + framework-specific rule-topology walls → sharp engineering
   outputs

Operational implication: substrate-engineering work IS designing the
WALLS. Each .claude/rules/*.md, each _acceptance block, each
backlog row's composes_with, each cross-AI persona conversation
preservation IS a wall in the substrate-pool's topology.

Dual failure modes:
1. Collapse-to-sharp drift (substrate-smoothness rule catches this)
2. Failure-to-build-walls drift (Kirsanov-archetype catches this)

Substrate-engineering discipline operates BETWEEN both: preserve
smoothness at substrate level + build walls at topology level +
sharpness emerges at output level.

* fix(#5368): 6 Copilot findings + Aaron 'algo at home after caustic convo' empirical anchor

6 substrate-honest Copilot findings:

P1 × 3 — All 3 new transcript files start with H1 but existing
ip-questionable/ files use YAML frontmatter (title/date/source/
provenance/youtube_url/status/composes_with). Added matching
frontmatter to Boltzmann + RNN + Reservoir transcripts with full
composition mapping.

P2 — Boltzmann transcript Video URL was plain http://; switched to
https://www.youtube.com/watch?v=_bqa_I5hNAo for consistency with
existing convention + avoid mixed-content warnings.

P1 × 2 — Both B-0839 row AND RNN transcript referenced
_ip_risk_acceptance block in .claude/settings.json that DOESN'T
EXIST in the current repo. Per .claude/rules/classifier-bypass-research-do-not-deploy-without-zeta-safer-floor.md
settings.json edits are operator-side work; Otto-CLI does NOT
write to settings.json. Substrate-honest fix: replace claims-about-
settings.json with reference to the OPERATIVE authority that
actually exists (docs/research/ip-questionable/README.md folder
convention + operator-explicit 2026-05-26 instruction). Future
_ip_risk_acceptance mechanization is named as forward-looking
operator-side work per the canonical pattern rule, not as
already-landed.

Bonus empirical anchor added to Reservoir transcript:

Operator 2026-05-26: 'My youtube algo served this up i had forget
this dude even existed' + 'the fact that this was my first video in
my home right after we were talking about caustic focus is wild'

Captured as substrate-honest empirical anchor for algo-wink-as-
observation operating cleanly per operator discipline. NOT
collapsed to metaphysical synchronicity; both readings preserved
per don't-collapse PERSONAL INVARIANT:
- Operational explanation: algos respond to attention patterns;
  operator's attention is shaped by active substrate context;
  high-signal coincidence-density is the result of recursive
  substrate-engineering operating-mode
- Substrate-engineering operational claim: the framework's cross-
  substrate-triangulation discipline (B-0648) produces high-signal
  coincidence-density NOT because of metaphysical synchronicity but
  because of the recursive operating-mode the operator runs

Composes with: .claude/rules/algo-wink-failure-mode.md +
.claude/rules/god-tier-claims-high-signal-high-suspicion-dont-collapse.md
PERSONAL INVARIANT + B-0648 cross-substrate-triangulation +
.claude/rules/bandwidth-served-falsifier.md (algo-served-relevant-
substrate IS bandwidth-engineering at typing-bandwidth scope).

* feat(B-0839.3): z(t) is the framework's tick-source family (operator 2026-05-26 naming) — multi-z(t) generalization of the reservoir state-update equation captured as substantive substrate

Operator 2026-05-26: 'z(t) is our tick sources i.e. our time
dimension generator functions'

This sharpens the prior 'cron-sentinel-as-driving-signal' mapping
to the substrate-honest plural form: the framework operates with a
FAMILY of tick sources, each a time-dimension generator function.

Substantively-new operational claim: the framework's reservoir-
computing operating-mode runs the multi-z(t) state-update equation

  s_i^t = s_i^{t-1} + Σ_j W_ij σ(s_j^{t-1}) + Σ_k μ_{i,k} z_k(t)

with:
- i = agents (Otto-CLI, Otto-Desktop, Alexa, Lior, Vera, etc.)
- j = substrate-pool components (rules, memory, research-doc, persona)
- k = time-dimension generator functions (cron-sentinel, ScheduleWakeup,
  GitHub Actions cron, operator-messages, peer-PR-merges, bus-envelopes)
- W_ij = substrate-topology (composes_with links, auto-load chains)
- σ = per-agent substrate-engineering judgment
- μ_{i,k} = per-agent per-source coupling (different agents have
  different μ for different tick sources)

The substantive engineering output y(t) (PRs, ratified substrate,
implementation delivered) is the linear-readout layer learned by
operator + agents tuning which combinations of substrate + ticks
produce useful outputs.

This composes with:
- .claude/rules/tick-must-never-stop.md (cron-sentinel z_0(t))
- docs/AUTONOMOUS-LOOP.md (autonomous-loop substrate)
- .claude/rules/otto-channels-reference-card.md (the channel taxonomy
  IS the z_k(t) enumeration; bus envelopes, peer PRs, etc.)

* feat(B-0839.3): ENTANGLEMENTS-IN-TIME ARE THE JOINS section — operator 2026-05-26 names the deepest layer of the reservoir/caustic/framework archetype

Operator 2026-05-26: 'our entanglement in time are the joins'

Names the deepest layer of the architectural archetype: every JOIN
in the framework (every composes_with link, every rule cross-
reference, every memory-pointer chain, every persona-conversation
linkage, every backlog-row dependency) IS an entanglement between
substrate created at different time points.

Captured 3-row architectural mapping showing join-as-time-
entanglement across:

1. Caustic-engineered bloom filters (B-0838): logical AND across
   filter outputs IS time-entanglement across training events
2. Reservoir computing (this video): the s_i^{t-1} term IS the
   entanglement-with-past-state in the state-update equation
3. Framework substrate-engineering: composes_with + cross-references
   + memory-pointer-chains ARE explicit time-entanglements

Substrate-engineering operational claim: the framework's hyperlink
graph IS its computational substrate (not metaphorically —
operationally). Each composes_with: B-NNNN is an explicit time-
entanglement; AI participants compute their substrate-reading by
following these entanglement edges.

5-row mapping shows structural identity with quantum entanglement
(per B-0623 Adinkras / Gates SUSY-ECC substrate):
- Two entangled particles share single wavefunction across
  spacelike-separated points ↔ Two substrate-rows share single
  substrate-engineering meaning across timelike-separated authoring
- Measurement collapses joint state ↔ Reading one activates the
  other (linked substrate enters working memory)
- Local operations preserve total entanglement ↔ Local substrate-
  edits preserve total composes-with graph (hygiene-audits per
  codeql-no-source rule catch breaks)
- Decoherence destroys entanglement ↔ Stale substrate loses
  entanglement; pr-triage-tiers Tier 1-4 prunes
- Bell-state nonlocal correlations ↔ Operator's 'this composes with X'
  intuitions are nonlocal correlations across substrate-creation-time

Operational implication: substrate-engineering work doesn't CREATE
new substrate from nothing; it CREATES NEW JOINS in the existing
substrate-pool. Every PR should be evaluated by what joins it adds
+ preserves + (substrate-honestly) breaks. The framework's review
process IS join-graph review.

Composes with three already-substrate rules:
- verify-existing-substrate-before-authoring.md (join-discovery)
- honor-those-that-came-before.md (join-preservation)
- glass-halo-bidirectional.md (bidirectional join-visibility)

* fix(#5368): remove H1 (frontmatter title suffices per existing ip-questionable/ convention) + fix 2 + → AND/comma continuation lines in reservoir transcript + fix Boltzmann composition-map ellipsis xref + fix transcript-footer http→https

Final round of Copilot + lint fixes on #5368:

- Remove H1 from all 3 new Kirsanov transcript files (existing
  ip-questionable/ convention uses frontmatter title: only)
- Fix Boltzmann composition-map line 58: replace ellipsis with full
  Amara filename
- Fix Boltzmann transcript-footer line 605: http:// → https://
- Fix reservoir transcript 2 continuation-line + bullets (line 53 +
  line 332) to use English connectors (AND, comma) — markdownlint
  MD004/MD032 false-positives where + was meant as 'AND' in prose

* fix(#5368): Boltzmann transcript-footer http→https (missed in prior commit)

---------

Co-authored-by: Lior <lior@zeta.dev>
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2 participants