Safety
Don't try to build a self-improving AI agent without evals. You are just wasting time and compute. An agent can't improve from traces it can…
Don't try to build a self-improving AI agent without evals. You are just wasting time and compute. An agent can't improve from traces it can't evaluate. This is why it's exciting to see @FutureAGI_ go
Don't try to build a self-improving AI agent without evals. You are just wasting time and compute. An agent can't improve from traces it can't evaluate. This is why it's exciting to see @FutureAGI_ going fully open source with their platform. It combines the best of all the eval tools and methods in one stack. They've shipped a set of tools to make it easier for AI devs to reliably ship self-improving agents. There is a lot to like here: - Evals for hallucination, groundedness, PII, toxicity, tool-use correctness, bias, and any custom metric. Every evaluator is readable and modifiable, not a black-box score. No vendor lock-in to worry about. - Six prompt optimization algorithms (GEPA, PromptWizard, ProTeGi, and others) that take production traces and feed them back as training signals. - Multi-turn simulation before launch, including voice agents through LiveKit, VAPI, Retell, and Pipecat. You stress test edge cases before users ever hit them. - Real-time guardrails for jailbreaks, prompt injection, and PII leaks. - OpenTelemetry-native tracing with 4+ languages (Python, TypeScript, Java, and C#), 50+ framework instrumentors (LangChain, LlamaIndex, CrewAI, AutoGen, DSPy, Haystack). - An OpenAI-compatible gateway with 100+ providers, routing strategies, and caching. If self-improving agents are the direction the field is moving, we need eval infrastructures we can actually trust and build on top of. This is that infrastructure, and now it's open. Check it out here: http://github.com/future-agi/future-agi Generous free tier cloud-based offer here: https://shorturl.at/cxYOd
Related
- Governed Capability Evolution for Embodied Agents: Safe Upgrade, Compatibility Checking, and Runtime Rollback for Embodied Capability Modules
- Learning Without Losing Identity: Capability Evolution for Embodied Agents
- On Safety Risks in Experience-Driven Self-Evolving Agents
Source: DAIR.AI (X) | 2026-04-27