I've been exploring a different problem space from AI agents and LLM frameworks.
Many tools focus on prompts, orchestration, and model capabilities, but production systems often fail because of runtime issues: retries, state loss, failed jobs, crashes, and recovery.
I built ALGOgent Runtime SDK, a lightweight Python toolkit that adds:
- Retry engine
- Backoff strategies
- State persistence
- Checkpoints
- Event bus
- Logging
- Metrics
The goal is simple: make automation scripts and AI workflows more resilient without requiring cloud services, GPUs, or heavy dependencies.
1 comment
[ 3.9 ms ] story [ 18.6 ms ] threadI've been exploring a different problem space from AI agents and LLM frameworks.
Many tools focus on prompts, orchestration, and model capabilities, but production systems often fail because of runtime issues: retries, state loss, failed jobs, crashes, and recovery.
I built ALGOgent Runtime SDK, a lightweight Python toolkit that adds:
- Retry engine - Backoff strategies - State persistence - Checkpoints - Event bus - Logging - Metrics
The goal is simple: make automation scripts and AI workflows more resilient without requiring cloud services, GPUs, or heavy dependencies.
Project page: https://stateflow-dev.github.io/algogent/
I'd appreciate feedback on the concept and whether this is a problem developers actually experience in production.