Loop engineering is the new label. The hard part is the one it has always been. Verification.
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There is a line doing the rounds. Boris Cherny, who created and now heads Claude Code, told the Fortune Brainstorm Tech audience in June that he no longer writes the prompts himself. His phrasing was that it is now another Claude doing the prompting. On a given morning he is managing hundreds of agents, sometimes thousands.
The framing that has grown up around this is "loop engineering." The pitch goes in three phases. 2024 was writing good prompts. 2025 was running agents in parallel. 2026 is building the loop that runs the agents for you. You stop typing prompts and start designing the system that types them.
That framing is fine as far as it goes. It also buries the part that decides whether your loop ships anything. A loop is a generator wired to a verifier. The generator was never the bottleneck. The verifier is.
## What a loop actually is
Strip the language back. A loop replaces the human cycle of prompt, read, prompt again with a self-running cycle: discover, plan, execute, verify, repeat until a condition is met. The agent drives its own iterations. You design the track it runs on.
The simplest version is a single agent looping over its own output. Research, draft, compare against the goal, fix the weak spots, repeat until it clears the bar. It is a person rewriting a draft, except the person does not get bored.
The larger version is a fleet. A goal goes to an orchestrator. The orchestrator splits it and hands pieces to specialists. Specialists hand detailed work to sub-agents. The tree runs discover, plan, execute, verify at every level until the goal is met. One is a single author. The other is a team running a project end to end.
None of this is new in kind. It is the same agent loop you already run, with the human stepped out of the inner cycle and moved up to the design of it.
## Open and closed
There are two shapes, and the difference is the whole game.
An open loop gives the agent a wide exploratory space. Conditions and a goal, but freedom in between. It can find paths you did not specify and produce things you did not plan for. This is where genuinely novel output comes from. It also burns tokens at a rate most budgets cannot absorb, and on loose criteria it turns into a slop machine. The freer the loop, the more it depends on the thing checking its work.
A closed loop pins the passes down in advance. Clear goal, defined steps, evaluation at each step, a stopping condition or a handoff to a human with the run data attached. The agent still loops, but inside a frame you built. It runs on a normal budget because the paths are bounded.
Closed loops are what produce results today. People credit the autonomy for that. The autonomy is not the reason. The evaluation gate is. The gate is what stops a confident wrong answer from propagating into the next iteration, and the next.
This is where most loop content goes quiet. Everyone draws the discover, plan, execute, verify diagram. Almost nobody says anything precise about the verify box. That box is the product. The rest is plumbing.
## Where the loop comes from
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