Evaluating Continuous Learning in Open-Source Environments
aakashgupta · x · 2026-07-14
This post recaps a 1-hour AI agent course covering practical topics like self-improving agents, memory systems, and debugging loops.
More importantly, it provides context that Skyfall AI tested Morpheus using frontier models including GPT-5.5 and Gemini 3.1 Pro, pointing out that high benchmark scores don't necessarily equate to continuous learning capabilities in real-world scenarios.
Morpheus offers an evaluation framework that allows researchers to test model adaptability in realistic, constantly changing environments; these environments have been open-sourced for the research community.
Related event: Skyfall AI's Morpheus Benchmark: Frontier LLMs Lack Continual Learning(6 posts)→
More from coding & agent
- He benchmarks new models by having them build their own copilot — $28 of compute — bucolucas · 2026-10-27
- Should agents be allowed to change plans mid-task? Reddit debates the drift boundary — wistfulcracker84 · 2026-10-27
- HeyGen + Canva MCP turns slide speaker notes into an avatar presentation video — HeyGen · 2026-10-27
- Local beats cloud: Qwen 3.8 FN handles private student data as well as frontier models — dr_lm · 2026-10-27
- LLM Tails cuts agent input tokens 80% by making agents read before they write — savadks1818 · 2026-10-27
- 10 practical ways to run Astra computer use on Premiere Pro for video editing — beechinour · 2026-10-27