type: axiom

principle: Cloudflare Workers Limitations

statement: Cloudflare Workers are unsuitable for Python AI workloads due to memory constraints and lack of ML library support.

evidence: Report 1


principle: Cost-Efficient Model Selection

statement: Select models like Gemini 2.5 Flash or Groq Llama 3.3 70B for cost-effective bulk processing in RLM deployment.

evidence: Report 2


principle: Mycelial Network Resilience

statement: Implement Mycelial network principles to ensure robust and resilient AI memory architectures.

evidence: Report 3


principle: Python ML Runtime Challenges

statement: Avoid Python ML workloads in Cloudflare Workers due to Pyodide's limited ML library support.


principle: Optimal Model Context Window

statement: Choose models with larger context windows (e.g., DeepSeek-R1-Distill-32B) for handling long texts in RLM.