Building Systems That Remember
A practical architecture for long-running AI agents
Building Systems That Remember is easy to describe as a feature and much harder to build as a dependable system. The interesting work begins when an idea must survive changing context, imperfect inputs, and long periods of operation.
A practical architecture for long-running AI agents. That requires explicit state, measurable outcomes, and boundaries that make failure visible rather than mysterious.
Building for durable intelligence
The practical lesson is to design the surrounding architecture with the same care as the model call itself. Good systems preserve useful information, discard noise, and make important transitions inspectable.
This article examines the tradeoffs, implementation patterns that hold up in practice, and the questions teams should ask before turning a promising demonstration into durable software.
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By Rohan Varma · 3,741 subscribers
Writing about AI systems, persistent agents, and what it takes to move intelligence beyond the chat window.
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