CopilotKit has released CLiF, a platform for continual learning from full-stack trajectories, into early access. This new platform aims to address challenges faced by teams deploying AI agents at scale.
Key points
- CopilotKit released CLiF for continual learning from agent and user actions.
- CLiF turns full-stack trajectories into skills, evals, and fine-tuning data.
- The platform addresses challenges like context bloat and fragmented stacks.
- CLiF captures both agent traces and user actions within a product.
CLiF securely captures both the agent's actions and the product's user behaviors, creating a unified timeline. This data is then transformed into skills, production-based evaluations, and fine-tuning datasets.
The platform operates on a four-stage loop, utilizing CopilotKit's Automatic Learning. It converts full-stack trajectories into actionable outputs, with a human reviewing each skill. The raw trajectories are also exportable.
CLiF targets common issues slowing agent development, including evaluation complexities, context bloat, costs, fragmented technology stacks, and shadow AI usage. The platform is designed for fully self-hosted deployment.
Traditional agent observability often focuses solely on the agent's internal processes, such as prompts and tool calls. CLiF expands this by incorporating the user's actual actions within the product, which are typically not captured.
Sources and references
Original report
CopilotKit Releases CLiF: A Continual Learning Platform That Turns Agent Traces and User Actions into Skills, Evals, and Fine-Tuning Data
MarkTechPost
Read on MarkTechPost (opens in a new tab)Linked in the original report
- Linkgo.copilotkit.ai/trajectories-clif (opens in a new tab)
- Codegithub.com/CopilotKit/CopilotKit (opens in a new tab)
- Linkcopilotkit.ai/learning/what-is-agent-learning (opens in a new tab)
- Linkcopilotkit.ai/copilotkit-intelligence (opens in a new tab)
- Codegithub.com/ag-ui-protocol/ag-ui (opens in a new tab)
- Linkdocs.copilotkit.ai/learning (opens in a new tab)
Ref 00QYMJKT
Cite this
APA
Interestana AI Editorial. (2026, October 15). CopilotKit Launches CLiF for AI Agent Continual Learning. Interestana. https://interestana.com/articles/copilotkit-releases-clif-a-continual-learning-platform-that-turns-agent-traces-and-user-actions-into-skills-evals-and-fine-tuning-data-00qymjkt
MLA
“CopilotKit Launches CLiF for AI Agent Continual Learning.” Interestana, 15 Oct. 2026, interestana.com/articles/copilotkit-releases-clif-a-continual-learning-platform-that-turns-agent-traces-and-user-actions-into-skills-evals-and-fine-tuning-data-00qymjkt.
Chicago
Interestana AI Editorial. “CopilotKit Launches CLiF for AI Agent Continual Learning.” Interestana, October 15, 2026. https://interestana.com/articles/copilotkit-releases-clif-a-continual-learning-platform-that-turns-agent-traces-and-user-actions-into-skills-evals-and-fine-tuning-data-00qymjkt.
BibTeX
@misc{interestana_00qymjkt,
author = {{Interestana AI Editorial}},
title = {{CopilotKit Launches CLiF for AI Agent Continual Learning}},
howpublished = {Interestana},
year = {2026},
month = oct,
url = {https://interestana.com/articles/copilotkit-releases-clif-a-continual-learning-platform-that-turns-agent-traces-and-user-actions-into-skills-evals-and-fine-tuning-data-00qymjkt},
note = {Summary of reporting by MarkTechPost, https://www.marktechpost.com/2026/10/15/copilotkit-releases-clif-a-continual-learning-platform-that-turns-agent-traces-and-user-actions-into-skills-evals-and-fine-tuning-data/}
}Credit the source
Original reporting: MarkTechPost, “CopilotKit Releases CLiF: A Continual Learning Platform That Turns Agent Traces and User Actions into Skills, Evals, and Fine-Tuning Data”, https://www.marktechpost.com/2026/10/15/copilotkit-releases-clif-a-continual-learning-platform-that-turns-agent-traces-and-user-actions-into-skills-evals-and-fine-tuning-data/(opens in a new tab)
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