cd /Users/Ali/PKM/scratch/pkm-deepdive
./vds-exec.sh run 'set +e
export PATH=$PATH:/usr/local/bin
echo "== codex procs =="; pgrep -af "codex exec" | grep -v pgrep | wc -l
echo "== gemini-newkey report? =="; ls -la --time-style=+%H:%M /srv/aina/ops/gemini-newkey-report.md 2>/dev/null
echo "== newkey lane final =="; tail -1 /srv/aina/ops/codex-gemini-newkey.log 2>/dev/null | tr -d "\000" | python3 -c "import sys,json
try:
 o=json.loads(sys.stdin.read());t=o.get(\"type\")
 if t==\"turn.completed\":print(\"COMPLETED\")
 elif t==\"turn.failed\":print(\"FAILED:\",o.get(\"error\",{}).get(\"message\",\"\")[:120])
 elif o.get(\"item\",{}).get(\"type\")==\"agent_message\":print(\"MSG:\",o[\"item\"][\"text\"][:400])
 else:print(\"(running)\",t)
except:print(\"(running)\")"
echo "== COO-dispatched builds → PRs? open PRs (academy) =="; gh pr list --repo ainative-academy/aina-academy --state open --json number,headRefName --jq ".[]|\"\(.number) \(.headRefName)\"" 2>/dev/null | head -15
echo "== backlog movement (was 89 todo/2 inprog/2 done) =="; paperclipai issue list --json 2>/dev/null | python3 -c "import sys,json;from collections import Counter;d=json.load(sys.stdin);i=d if isinstance(d,list) else d.get(\"issues\",d.get(\"data\",[]));n=[x for x in i if \"council-2026-06-29\" in (x.get(\"description\") or \"\")];print(\"93-backlog:\",dict(Counter(x.get(\"status\") for x in n)))"
echo "== lesson-shell-port running? =="; tail -1 /srv/aina/ops/codex-lesson-shell-port.log 2>/dev/null | tr -d "\000" | head -c 80; echo

cd /Users/Ali/PKM/scratch/pkm-deepdive
./vds-exec.sh run 'set +e
export PATH=$PATH:/usr/local/bin
echo "PROCS:"; pgrep -af "codex exec" | grep -v pgrep | wc -l
echo "NEWKEY-REPORT:"; ls -la --time-style=+%H:%M /srv/aina/ops/gemini-newkey-report.md 2>/dev/null || echo none
echo "NEWKEY-LANE-LASTTYPE:"; tail -1 /srv/aina/ops/codex-gemini-newkey.log 2>/dev/null | tr -d "\000" | grep -oE "\"type\":\"[a-z.]+\"" | tail -1
echo "OPEN-PRS:"; gh pr list --repo ainative-academy/aina-academy --state open --json number,headRefName --jq ".[]|\"#\(.number) \(.headRefName)\"" 2>/dev/null
echo "PORT-LANE:"; tail -1 /srv/aina/ops/codex-lesson-shell-port.log 2>/dev/null | tr -d "\000" | grep -oE "\"type\":\"[a-z.]+\"" | tail -1' 
echo "---BACKLOG---"
./vds-exec.sh run 'export PATH=$PATH:/usr/local/bin; paperclipai issue list --json 2>/dev/null > /tmp/il.json; python3 -c "import json;from collections import Counter;i=json.load(open(\"/tmp/il.json\"));i=i if isinstance(i,list) else i.get(\"issues\",i.get(\"data\",[]));n=[x for x in i if \"council-2026-06-29\" in (x.get(\"description\") or \"\")];print(\"93-backlog:\",dict(Counter(x.get(\"status\") for x in n)))"'

cd /Users/Ali/PKM/scratch/pkm-deepdive
./vds-exec.sh run 'sed -n "1,60p" /srv/aina/ops/gemini-newkey-report.md 2>/dev/null'

cd /Users/Ali/PKM/scratch/pkm-deepdive
./vds-exec.sh run 'export PATH=$PATH:/usr/local/bin
python3 - <<"PY"
import subprocess,json
def pc(*a): return subprocess.run(["paperclipai",*a],capture_output=True,text=True)
iss=json.loads(pc("issue","list","--json").stdout); iss=iss if isinstance(iss,list) else iss.get("issues",iss.get("data",[]))
ids={x.get("identifier"):x.get("id") for x in iss}
v=("NEW-KEY Interactions test (Ali key, 2026-06-29): the new AQ. key does NOT unlock Interactions (no surface returned 200+interactionId; ceiling 0). BUT it WORKS for key-based Vertex Express generateContent on both models — confirms a direct KEY-HEADER path from Cloudflare Workers WITHOUT ADC for standard Gemini generation (good for the launch tutor). Interactions still blocked: this is a valid GENERATION key but cannot call the Interactions METHOD. To get Interactions, Ali needs a BILLING-ACTIVE Developer API credential, OR Google to enable Interactions models on Vertex project aina-495702. DECISION UNCHANGED: launch tutor on standard Vertex generateContent (key-based, Workers-ready); Interactions = optional post-launch. Old key backed up. PR #119.")
for ident in ("AIN-174","AIN-133"):
    i=ids.get(ident)
    if i: print(ident, pc("issue","comment",i,"--body",v).returncode==0)
PY'

cd /Users/Ali/PKM/scratch/pkm-deepdive
cat > learner-flow-doctrine.txt <<'EOF'

---
## LEARNER FLOW + INTERFACE DOCTRINE (Ali 2026-06-29) — "everything flows through here only"
- **THE card-based chat shell (recovered, 3-col) is the SINGLE PRIMARY INTERFACE.** NO separate media/video/audio pages or routes. ALL content — lessons, media, video, audio — flows INLINE through this one shell (cards + stream). One interface; everything through it.
- **LESSONS ARE DETERMINISTIC — no live LLM, no tutor agent.** The lesson flow is a SELECTOR over pre-authored content + cards (the deterministic tier = "selector by default"). It works FULLY WITHOUT a live LLM. The tutor / Gemini-Interactions API is NOT needed for lessons.
- **PROGRESSION / UNLOCK:** lesson (deterministic) → learner CLEARS it → unlocks **MISSIONS + PRACTICE ARENA** → learner chooses: advance to the next lesson, OR do the practice arena (can return to the arena later). Practice arena unlocks after lesson completion / after a few lessons.
- **LIVE LLM = OFF by default everywhere; toggled ON ONLY in the PRACTICE ARENA for MISSIONS** (the "gated generation by exception" tier). Lessons never call the LLM; only arena missions do — and even there the pure-sim / no-LLM mode exists (see ARENA-DOCTRINE).
- **REPRIORITIZE: the Gemini-tutor / Interactions API is NOT on the lesson critical path** (lessons are deterministic). It only matters for arena missions (optional, behind the LLM toggle). Drop its urgency. Priority = the deterministic lesson flow (the chat shell) + the unlock progression + the arena LLM-toggle. This IS the two-tier engine: deterministic lessons (selector) + gated-LLM arena missions.
- Supersedes the "separate video-lesson page" framing (AIN-91): video flows INLINE through the shell, not a separate route. "We had discussed this" — aligns with the two-tier engine + ARENA-DOCTRINE (with/without LLM).
EOF
base64 < learner-flow-doctrine.txt | ./vds-exec.sh runl '
  T=$(base64 -d)
  echo "$T" >> /srv/aina/ops/FACTORY-GUARDRAILS.md
  for f in lane-lesson-shell-port.md lane-practice-arena-v2.md; do [ -f /srv/aina/ops/lanes/$f ] && echo "$T" >> /srv/aina/ops/lanes/$f; done
  echo FLOW_DOCTRINE_LOGGED'

cd /Users/Ali/PKM/scratch/pkm-deepdive
./vds-exec.sh run 'export PATH=$PATH:/usr/local/bin
python3 - <<"PY"
import subprocess,json
def pc(*a): return subprocess.run(["paperclipai",*a],capture_output=True,text=True)
iss=json.loads(pc("issue","list","--json").stdout); iss=iss if isinstance(iss,list) else iss.get("issues",iss.get("data",[]))
ids={x.get("identifier"):x.get("id") for x in iss}
notes={
 "AIN-91":"RE-SCOPED (Ali flow doctrine 2026-06-29): video is NOT a separate page/route — it flows INLINE through the single card-based chat shell (the one primary interface). Build video as an inline card in the shell, not a standalone video-lesson page.",
 "AIN-133":"DE-PRIORITIZED (Ali flow doctrine 2026-06-29): lessons are DETERMINISTIC (selector + cards, NO live LLM, no tutor agent) — the Gemini tutor/Interactions API is NOT on the lesson critical path. Live LLM is toggled ON only in the PRACTICE ARENA for missions. Move any LLM-tutor work to the arena-missions toggle; not needed for the lesson flow.",
 "AIN-92":"Per flow doctrine 2026-06-29: audio flows INLINE through the chat shell (no separate audio page); audio remains founder-owned (Ali) + off the agent critical path.",
}
for ident,n in notes.items():
    i=ids.get(ident)
    if i: print(ident, pc("issue","comment",i,"--body",n).returncode==0)
    else: print(ident,"not found")
PY'

cd /Users/Ali/PKM/scratch/pkm-deepdive
cat > arena-sim-primary.txt <<'EOF'

---
## ARENA SIMULATION IS PRIMARY (Ali 2026-06-29 confirm — "always been the plan")
- The Practice Arena's PRIMARY / DEFAULT mode = **SIMULATE LLM behavior** (the flight simulator): deterministically program LLM behavior — errors, mistakes, context-window limits, drift, hallucination, refusal, latency — sourced from OUR OWN learnings (the "15 things" + PKM gotchas). This IS the point, NOT a fallback. Privacy-safe, no data egress, reproducible.
- **Live LLM = OPTIONAL toggle in the arena, "if needed" — NOT the default.** (Client-side LLM / Gemma-Chrome is the other privacy-safe option.)
- THEREFORE **the WHOLE PLATFORM runs WITHOUT any live LLM by default**: lessons = deterministic (selector + cards); arena = simulated LLM behavior. Live LLM is optional, arena-only, behind a toggle.
- This de-prioritizes live-LLM / Gemini-Interactions EVEN FURTHER: the platform is fully functional + launch-ready with ZERO live LLM. Gemini/live-LLM = a later optional enhancement, NEVER a launch blocker. Build the arena SIM-FIRST (the simulation engine + the failure-mode catalog), with live-LLM as an optional behind-flag mode.
EOF
base64 < arena-sim-primary.txt | ./vds-exec.sh runl '
  T=$(base64 -d)
  echo "$T" >> /srv/aina/ops/FACTORY-GUARDRAILS.md
  echo "$T" >> /srv/aina/ops/reference/ARENA-DOCTRINE.md
  [ -f /srv/aina/ops/lanes/lane-practice-arena-v2.md ] && echo "$T" >> /srv/aina/ops/lanes/lane-practice-arena-v2.md
  echo SIM_PRIMARY_LOGGED'

cd /Users/Ali/PKM/scratch/pkm-deepdive
cat > adaptive-llm-off.txt <<'EOF'

---
## ADAPTIVE ENGINE WORKS LLM-OFF (Ali 2026-06-29)
- The ADAPTIVE ENGINE + PERSONALIZATION + DYNAMIC ADAPTATION work with LLM OFF — they personalize + adapt by SELECTING content/path DETERMINISTICALLY over RECORDED learner data points, NOT live LLM inference. This IS the deterministic "selector" tier.
- **learnerDO (Durable Object) + coach agent keep RECORDING data points with LLM off**: lesson completion, attempts, scores, time, choices, posture, mindset slot, workflow fingerprint, learning-events. Data capture + adaptation continue regardless of LLM state.
- Live LLM is NOT required for personalization/adaptation — only the OPTIONAL arena-mission toggle uses it.
- **FLAGGED REVIEW (Ali "may need to look again"):** verify how the LLM-off architecture affects the engine's working + personalization + dynamic adaptation — confirm the engines run deterministically over the recorded signals; flag any logic that wrongly assumes/requires a live LLM. Review lane dispatched (adaptive-engine-llm-off-review.md).
EOF
base64 < adaptive-llm-off.txt | ./vds-exec.sh runl '
  T=$(base64 -d); echo "$T" >> /srv/aina/ops/FACTORY-GUARDRAILS.md; echo CANON_OK'
cat > lane-adaptive-llm-off-review.md <<'EOF'
# Lane: Review adaptive engine / personalization / dynamic adaptation under LLM-OFF (Ali "look again")
## AUTONOMY: ANALYZE + REPORT (do NOT rebuild); honest; gpt-5.5. Repo /srv/repos/aina-academy (+ the personalization engine repos).
## Context (Ali 2026-06-29): the adaptive engine + personalization + dynamic adaptation must work with LLM OFF (deterministic selector over recorded data points). learnerDO (Durable Object) + coach agent keep RECORDING data points with LLM off. Canon: deterministic lessons + simulated arena; live LLM optional/arena-only. Look again at how LLM-off affects the engines.
## Do (analysis)
1. Map the adaptive/personalization stack as built: the personalization substrate/engine (AIN-96/97/98), the **learnerDO** durable object (what data points it records + when), the **coach agent** (what it records + does), the adaptation/selector logic (postures, mindset slots, tool variants, workflow fingerprint, the 3 tiers, the diagnose→teach→practise→evaluate→improve→progress loop), and the learning-event/telemetry pipeline.
2. For EACH, determine: does it work LLM-OFF? Personalization + dynamic adaptation should run by DETERMINISTICALLY selecting content/path from the RECORDED data points (completion, attempts, scores, time, choices, posture, mindset, fingerprint) — NOT live LLM inference. Confirm learnerDO + coach keep recording with LLM off.
3. FLAG any place that wrongly assumes/requires a live LLM for personalization/adaptation (e.g. an evaluator or adaptation step that calls the LLM at runtime) and how to make it deterministic (selector + pre-authored + the recorded signals). Note: the evaluator scoring path is canon selector-only (First-Principles doc); generation only assists building calibration, never live scoring.
4. Confirm the two-tier framing holds: deterministic selector (lessons + adaptation, LLM-off) + gated generation (arena missions, optional LLM toggle, sim-first).
## Deliver: report /srv/aina/ops/adaptive-engine-llm-off-review.md — per-engine LLM-off readiness, the data points learnerDO+coach record, what works deterministically vs what needs rework (with the fix), and whether the engine's personalization/dynamic-adaptation is preserved LLM-off. Honest. gpt-5.5. (Analysis only — route fixes after.)
EOF
base64 < lane-adaptive-llm-off-review.md | ./vds-exec.sh runl '
  base64 -d > /srv/aina/ops/lanes/lane-adaptive-llm-off-review.md
  export PATH=$PATH:/usr/local/bin
  C5="exec --json --dangerously-bypass-approvals-and-sandbox --model gpt-5.5 -c model_reasoning_effort=high --skip-git-repo-check -"
  cd /srv/repos/aina-academy
  nohup bash -c "cat /srv/aina/ops/lanes/lane-adaptive-llm-off-review.md | codex $C5" > /srv/aina/ops/codex-adaptive-review.log 2>&1 &
  echo "adaptive-llm-off-review lane pid=$!"'

cd /Users/Ali/PKM/scratch/pkm-deepdive
cat > inline-coach-correction.txt <<'EOF'

---
## CORRECTION — the live LLM IS the inline chat coach (Ali 2026-06-29)
Refines the flow doctrine (do NOT read the earlier "no coach/agent at all" too literally):
- The **LIVE LLM = the inline chat provider / coach agent** WITHIN the chat shell — the conversational coach/agent layer. It is **OPTIONAL and toggle-able OFF.**
- The **CONTENT (lessons, cards, media) flows DETERMINISTICALLY** through the shell regardless — the always-on backbone (works fully LLM-off).
- The inline-chat coach (live LLM) is an OPTIONAL overlay on that backbone: toggle ON = live-LLM coach converses inline; toggle OFF = platform runs fully on deterministic content + recorded data + the adaptive engine (and the coach can be SIMULATED when off — the flight-simulator approach).
- The COACH has TWO aspects: (1) **data/signal recorder = ALWAYS ON, deterministic** (learnerDO + coach keep recording data points regardless of LLM); (2) **live-LLM inline conversationalist = OPTIONAL toggle.** "Tutor agent not needed" meant the CONTENT doesn't depend on the LLM — the coach exists as the optional live-LLM chat layer.
- So live LLM = the optional inline-chat coach (in the shell AND arena missions), toggle-off everywhere; sim/deterministic is the default. Platform fully functional with the coach toggled off.
EOF
base64 < inline-coach-correction.txt | ./vds-exec.sh runl '
  T=$(base64 -d)
  echo "$T" >> /srv/aina/ops/FACTORY-GUARDRAILS.md
  for f in lane-lesson-shell-port.md lane-adaptive-llm-off-review.md lane-practice-arena-v2.md; do [ -f /srv/aina/ops/lanes/$f ] && echo "$T" >> /srv/aina/ops/lanes/$f; done
  echo COACH_CORRECTION_LOGGED'