matiasmolinas/evolving-agents

The project addresses 'evolving' agents, which was a highly experimental and novel niche about a year ago (410 days). With 450 stars, it clearly captured initial developer interest. However, the velocity of 0.0/hr suggests the project has stagnated. In the interim, heavyweights like Microsoft (AutoGen), LangChain (LangGraph), and CrewAI have emerged, offering much deeper integration, better documentation, and more robust execution environments. The concept of 'evolution' (refining prompts or tools based on experience) is now being subsumed into standard RAG and memory-augmented agent architectures. Without active maintenance or a unique high-moat dataset/runtime environment, this project serves more as a reference implementation or an educational resource rather than a defensible production toolkit. Frontier labs are also building these capabilities natively (e.g., OpenAI's focus on persistent memory and 'Swarm' frameworks), making the displacement risk for standalone agent wrappers extremely high.