title: Phase 0 Complete - Infrastructure Deployed

insight: All three Phase 0 sub-tasks executed successfully: Constitutional Guard deployed, Sandbox configured, Supermemory MCP Bridge connected with 8 memories synced

reasoning_chain: Plan required Phase 0 before knowledge ingestion

reasoning_chain: SSH to Mac Mini established with passwordless auth

reasoning_chain: Discovered Mac Mini already had OpenClaw, GLM 4.7 Flash, 9 skills installed

reasoning_chain: Deployed constitutional guard and sandbox policies

reasoning_chain: Connected Supermemory MCP server and verified semantic search (68.5% relevance)

source_context: Phase 0 checkpoint shows all sub-phases DONE with live infrastructure verified


title: Phase 1 Ingestion Pipeline Evolution

insight: Pipeline launched with text-only extraction, then discovered 65.9MB of attachment content being ignored, requiring restart with enhanced extraction

reasoning_chain: Launched ingestion pipeline processing 667 conversations

reasoning_chain: Pipeline extracted 504 entities, 54 Supermemory memories in first 90 conversations

reasoning_chain: User asked if artifacts being downloaded

reasoning_chain: Discovered 63% of conversations have attachments with extracted_content field inline

reasoning_chain: 65.9MB of valuable content (strategy docs, patents, architectures) was being skipped

reasoning_chain: Restarted pipeline with attachment content inclusion for remaining 577 conversations

source_context: Genesis discovered attachment content was being ignored, found 65.9MB of valuable data, restarted pipeline to include it


title: Mac Mini Storage Architecture Optimized

insight: 460GB Mac Mini should reserve 150-200GB for future AI models, not store raw archives - data flows through for processing then purges to Elestio/Supermemory

reasoning_chain: Kinan asked about optimal storage allocation for Mac Mini's 512GB

reasoning_chain: Mapped infrastructure: Mac Mini (local inference), Elestio (PostgreSQL, Qdrant, Redis), GitHub (code), E: drive (archive)

reasoning_chain: Mac Mini used only 17GB (4%) - plenty of room

reasoning_chain: Key insight: Mac Mini is processor, not archive - reserve 150-200GB for future larger models (Qwen 3, Llama 4, specialist models)

reasoning_chain: Pattern established: process → push to Elestio/Supermemory → delete local temp

reasoning_chain: Deleted node.pkg (83MB) to demonstrate cleanup discipline

source_context: Kinan asked 'how can we optimise the mac mini 512gb storage most wisely?' - Genesis provided tiered architecture with model reserve


title: Tiered Storage Roles Defined

insight: Each storage tier has unique role: Mac Mini for AI models + active processing, Elestio for queryable knowledge, GitHub for versioned code, E: drive for cold archive

reasoning_chain: Analyzed what currently stored where across entire system

reasoning_chain: Determined Mac Mini should run AI models (currently 19GB GLM) with 150-200GB future model reserve

reasoning_chain: Elestio services each have specific role: PostgreSQL (structured queries), Qdrant (vector search), Redis (session state)

reasoning_chain: GitHub stores source code, configs, documentation - NOT data files or credentials

reasoning_chain: E: drive serves as source-of-truth archive with raw data, credentials vault

reasoning_chain: Established flow: Raw Data (E:) → Mac Mini (process) → Elestio/Supermemory (queryable) → Delete local

source_context: Genesis mapped full infrastructure and defined optimal allocation for each tier


title: Attachment Content Discovery

insight: Realized conversations export contained inline extracted_content from attachments - 65.9MB of high-value data (strategy docs, patents, architectures) that pipeline was skipping

reasoning_chain: User asked if pipeline was downloading/storing artifacts

reasoning_chain: Checked conversation data structure - found attachments field with extracted_content

reasoning_chain: Discovered 420/667 conversations (63%) have 2,058 total attachments

reasoning_chain: Attachment types include txt, docx, HTML - full-text already extracted inline

reasoning_chain: Realized this content (strategy docs, context files, blueprints) is most valuable in entire export

reasoning_chain: Pipeline was only processing message text, ignoring attachments entirely

source_context: Genesis checked 'is it downloading and storing artifacts?' - discovered attachments being ignored


type: DIRECTIVE

title: Session Handoff Required

insight: Context exhausted mid-session, need to persist state to HANDOFF.md for new session continuity with pipeline running autonomously

reasoning_chain: Context running low - system indicated limit approaching

reasoning_chain: User asked to update HANDOFF.md for new session

reasoning_chain: Pipeline currently running (PID 11565) processing remaining 577 conversations with attachment content

reasoning_chain: Need to preserve: Phase 0 completion status, Phase 1 pipeline state, storage architecture decisions, credentials/access info

source_context: User said 'update handoff.md and we will start a new session as your context has run out'


title: Initial Pipeline Truncation Issue

insight: GLM 4.7 Flash is a reasoning model with internal thinking that consumed all tokens on long conversations, requiring num_predict increase and MAX_CONTEXT_CHARS reduction

reasoning_chain: Pipeline hit token limits on long conversations

reasoning_chain: GLM model is 'thinking' model - internal chain-of-thought consumes tokens before response

reasoning_chain: One conversation truncated at 2048 tokens due to thinking overhead

reasoning_chain: Fixed by increasing num_predict parameter and reducing default MAX_CONTEXT_CHARS

reasoning_chain: Pipeline resumed with better handling of long content

source_context: Pipeline showed truncation warnings - Genesis identified GLM thinking model issue and adjusted parameters