Always-on AI agents turn infrastructure into a continuous learning loop
Cognition's Devin now runs the full software lifecycle—planning, code, review, production. That requires infrastructure that learns continuously.
Why it matters
AI agents are moving from point-task automation to continuous lifecycle roles, requiring infrastructure that supports real-time feedback loops and on-the-fly training—a shift from traditional ML pipelines to always-on learning systems.
The key facts
4 to knowCognition AI's Devin expands from code writing to planning, review, and production problem response
Agent infrastructure must support continuous inference-feedback-training cycles at scale
CoreWeave and Fully Connected infrastructure partners enabling continual-learning agent deployments
Shift from episodic agent tasks to always-on roles across full software development lifecycle
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Publisher excerpt: AI agent infrastructure is evolving to support systems that move continuously among inference, feedback and training. Cognition AI Inc.’s Devin now assists throughout the software development lifecycle, from planning and writing code to reviewing it and responding to production problems. That…