📅 Week 11 · 2026-03-13 ⚡ Generated by m2 (orchestrator) 🔒 Internal

Memory Stack Expansion, Autoheal & Intent Engineering

71%

Overall production readiness

9 agents healthy 2 degraded 5 blocked 16 shipped

Subsystem Scores

Fleet Management 76%

Memory System 74%

Autonomous Org Builder 56%

Communication Protocols 70%

Playbook Adoption 64%

Resource Provisioning 60%

Role / Org Science 54%

Dark Factory Engine 57%

Fleet Numbers

Healthy Agents

Degraded

Containers

4,600+

Memory Vectors

Shipped This Week

✅ m2-memory-engine extension integrated into OpenClaw + Forgejo upstream-sync workflow (10 openclaw commits)

✅ Memory-engine plugin fix rolled out fleet-wide — all agents now have semantic memory access

✅ GLiNER NER microservice deployed — GPU-backed, multilingual, zero-shot named entity recognition

✅ Memgraph knowledge graph service added to agent.memory.system stack

✅ Enhanced agent-autoheal with LLM failover — baked into m2-desktop image

✅ Two-layer config system: openclaw built at image time, config injected at runtime

✅ Peter + master Telegram IDs auto-injected via fleet config generator

✅ Fleet gateway watchdog v2 with deep repair logic (auto-restarts, deep health checks)

✅ Natural-TTS skill added (HumeAI TADA model — emotional, expressive voice)

✅ Intent-router skill — confidence scoring (0-100%), route to elicit/confirm/execute

✅ m2-world: Intent Engineering architecture designs + Google ADK integration analysis (9 commits)

✅ agent-org-simulator: enterprise benchmark run #9 complete — Dynamic Pentad Framework (retro run_009)

✅ machinemachine.ai: /contact page + form + mailto fallback, mobile pitch fixes, CRM bot token sync

✅ 3 auto-generated AI research blog posts (Confused Deputy Problem, LLMGreenRec, Reasoning vs Creativity)

✅ kokoro-tts CUDA optimisation — TF32/cuDNN warmup, larger chunks, parallel processing

✅ m2-voice fleet DNS alias — agents can reach TTS via stable hostname

Gaps & Blockers

Critical Gaps

nasr-m2o CPU runaway — 260%

nasr-m2o container pegged at 260% CPU (3.9 GiB / 8 GiB RAM). Likely infinite loop or stuck LLM request. Needs restart/investigation.

Container sprawl — 10+ unhealthy services

Claude proxy, claude-worker, joinly, qwen3-tts, chatterbox-tts, vllm-docker, muninndb-pilot, spacetimedb, Pinokio, Home Assistant — all exited:unhealthy. Dead weight consuming Coolify slots.

Warnings & Blocked

Memgraph hitting 1 GiB memory limit (65%)

memory-memgraph container using 665 MiB / 1 GiB limit. Will OOM as the knowledge graph grows. Limit needs bumping to 2-4 GiB.

memory-embeddings at 14.18 GiB RAM

BGE embeddings model using 14.18 GiB (11.3% of host). Largest single allocation. Consider quantised model or dedicated GPU inference.

vLLM local inference unstable

Qwen3-14B-AWQ was added then reverted this week. Local LLM inference for memory/reasoning pipeline not yet stable.

🔴 Home Assistant still exited/unhealthy — redirect loop unresolved

🔴 nasr-m2o at 260% CPU — likely runaway process, needs investigation

🔴 Persistent unhealthy containers: Claude proxy, claude-worker, joinly, qwen3-tts, chatterbox-tts, vllm-docker, muninndb-pilot, spacetimedb, Pinokio

🔴 kokoro-tts degraded:unhealthy (kokoro-tts container shows g4sw4g40 degraded)

🔴 vLLM Qwen3-14B-AWQ reverted from agent-memory-system — local inference still unstable

Priority Actions

1. Restart nasr-m2o and investigate CPU runaway (260% for extended period)

2. Bump Memgraph memory limit to 2-4 GiB before it OOMs

3. Triage and decommission 10 persistent unhealthy containers

4. Re-attempt vLLM Qwen3 stable deployment — use dedicated service config

5. Deploy org_memory shared Qdrant namespace — Memgraph graph is ready

6. Fix Home Assistant redirect loop or decommission

7. Benchmark Intent-router skill accuracy across common task types