Hi HN, I’ve spent the last few months researching why standard AI agents fail in low-resource environments (like Lagos or rural areas) and building architectural patterns to fix it.

This repo contains the Python reference implementations for "Contextual Engineering",a framework for adapting LLMs to hostile infrastructure.

It includes:

Sync-Later Queue: A mechanism to decouple user intent from network availability (so agents don't crash when offline).

Hybrid Router: Logic to route prompts between a local SLM (quantized Llama-3) and Cloud LLMs based on battery/latency.

Constitutional Sentinel: A safety layer for high-stakes environments.

I also wrote a full open-access book explaining the theory, which you can find linked in the README.

I’d love to hear your feedback on the OfflineAction serialization logic.