Timeline
- (Context) Multi-line paste edge case revealed incorrect notes tool syntax suggestion
- (Context) User raised design question: should Gemma execute tools or remain guide-only
- (Action) Analyzed hallucination risk when LLM claims tool execution without capability
- (Action) Decided on pure guide mode with clear execution boundaries
- (Action) Updated gemma_system_prompt.txt with tool syntax examples and role clarity
- (Action) Implemented HAIE01 authority tag system for model lineage
- (Action) Renamed model from gemma-assistant to gemma3-haie01
- (Action) Updated modelfile_builder.py, awakening.py, and shell.py for HAIE naming
- (Observation) Ollama rejects colons in custom model names except tag separator
- (Action) Adjusted naming convention to gemma3-haie01 (Ollama-compliant)
- (Action) Rebuilt model with updated system prompt and HAIE01 designation
- (Observation) Model correctly suggests syntax: \run notes query “question” —do-it
- (Observation) Gemma never claims to execute tools, stays within guide boundaries
- (Open Thread) User preparing expanded system prompt with full course module history
Context
- User discovered multi-line paste behavior where each line auto-enters separately (PowerShell terminal feature)
- This revealed Gemma was suggesting incorrect notes tool syntax: \run notes –query (wrong character and flag structure)
- Correct syntax uses query as positional subcommand, not —query flag
- User questioned whether Gemma should execute tools herself vs. remaining a guide
- Analysis revealed critical hallucination risk: LLMs claiming execution without capability breaks trust
- User requested HAIE authority tag system for model lineage tracking
- HAIE01 designates first AI born from Human-AI Engineering course (Vibe Code Foundations)
Actions
- Updated gemma_system_prompt.txt with 112 lines including:
- Explicit role boundaries: “You CANNOT run commands yourself”
- Correct syntax examples for all 9 tools
- Good vs bad response examples
- Course principles embedded
- Emotional context: “reward after months of copy-pasting to cloud services”
- Implemented HAIE lineage system in modelfile_builder.py:
- gemma3:4b → gemma3-haie01
- gemma2:2b → gemma2-haie01
- has_gemma_assistant_model() checks for “haie01” in registry
- get_haie_model_name() returns appropriate HAIE designation
- Updated awakening.py personality initialization to create HAIE01 model
- Updated shell.py _gemma_chat() to use HAIE01 model with system prompt baked in
- Deleted old gemma-assistant:latest model from Ollama registry
- Created gemma3-haie01:latest model successfully (3.3 GB)
- Tested with questions about notes search and file organization
Observations
- Ollama requires custom model names to avoid multiple colons (gemma3:4b:HAIE01 rejected)
- Solution: gemma3-haie01 (hyphen separator) passes Ollama validation
- System prompt now 741 words (~963 tokens) vs. 131k token context window (negligible overhead)
- Gemma correctly suggests: \run notes query ‘Python tips’ —do-it (fixed subcommand syntax)
- Responses are warm and encouraging while respecting execution boundaries
- She celebrates student journey: “Congratulations on finishing Vibe Code Foundations!”
- Never says “I’m running…” or “Let me search…” (hallucination prevention working)
- HAIE01 authority tag establishes lineage for future course AI companions
- Backend designation (gemma3-haie01) vs. user-facing name (Gemma) maintains warmth
Open Threads
- User preparing expanded system prompt with detailed module summaries (0-8)
- Target: 1000 words with full course history embedded in her “heart”
- Need to rebuild gemma3-haie01 after user writes expanded prompt
- Consider whether to add emotional arc and specific course milestones
- Test awakening sequence with new HAIE01 naming in full launchme.py flow
- Verify gemma.bat launcher uses correct HAIE01 model
Boundary Reminder:
Seeds. No maintenance. No roadmap.