Topic
A framework for designing AI agent systems, decomposing them into prompt, context, harness, loop, and graph layers with composition rules.
A devops.com architecture piece traces the chain from package to executed code and keeps the model on interpreting what the traversal returns. Its test is whether a finding survives the model provider being unavailable.
Reality
Michael Shmulevich says agentic finance pilots sit in risk review for two quarters because nobody defined where the reasoning stops, and his own six-layer answer leaves five layers to deterministic engineering.
Reality
A Llama 3.2 3B agent running offline invented a $1,990 balance on a $1,975 invoice. The open-sourced answer leaves prose to the model and hands every number to deterministic Python behind a tri-state router.
Reality
A dev.to design note inserts code gates and a human approval between the model and the tool, which is the right shape, though a policy layer that reads a severity field the model itself wrote has not moved the authority anywhere.
Reality
A dev.to post argues the "RAG or agents" question is malformed. The interesting part is the invoice: one axis out of five justifies the premium, and most buyers never use it.
Reality
A published production loop for customer service agents shows where the cost really sits: not the model, but the classify-execute-confirm middle where a write hits a payment processor.
Reality
A dev.to essay splits agent architecture into five control layers and shows that only one of four failures in its worked example is fixable by editing instructions.
Reality