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06:00

Harness, Loop, Graph: Which Layer Actually Broke Your Agent

Agent 修不好,先查是哪一层坏了:harness、loop、graph

The author splits agent failures into three layers: the harness (everything around the model — tools, memory, permissions, traces), the loop (a check that can genuinely fail, plus feedback and exits), and the graph (dependencies and state handoff between loops). The claim is that each layer fixes a different class of failure, and that most engineers burn weeks editing prompts or swapping models when the real defect lives elsewhere. Concrete patterns include a task contract with an explicit done_when field, an AGENTS.md file that acts as a map instead of a manual, retry loops that exit when the same evidence appears twice, and an early-start test that removes fake arrows between steps. The author concedes most tasks should collapse back to a single loop, and that drawing a twelve-node graph first is a common mistake. Suited to engineers building agent workflows. Second-hand synthesis, no original measurements.

06:00

The Harness Is the Machine: Task Contracts, Worktrees, Receipts

把 Agent 关进 harness:任务契约、worktree 隔离与变更回执

A long-form X post outlining a production architecture for coding agents. The thesis: when an agent fails a multi-file refactor, the problem is not the prompt or the model but the environment around it — the harness. The author lays out a seven-stage pipeline: Opus compiles a task_contract.json with path allowlists and a cost/turn/timeout budget; the harness spawns an isolated git worktree; Sonnet edits only inside the boundary; Haiku validates every tool call parameter; a separate model acts as adversarial skeptic against the diff; a pre-commit hook checks test exit codes and signs a receipt.json; failures crystallize into rules, skills, and regression evals. Includes contract schema, isolate_worktree.sh, pre-tool.sh, receipt format, and a 10-point pre-flight checklist. Caveat: the Opus/Sonnet/Haiku/Fable 5.5 model names and the 18%→95% success numbers are unsourced, and the post ends with a Telegram funnel link.

06:00

Loops and Graphs: stop babysitting agents, approve only the last step

别再替 agent 盯每一步:loop 放进节点,graph 放在节点之间

Two layers, split cleanly: a loop lives inside a node (produce, check, correct until green), a graph lives between nodes (what work exists, what runs in parallel, where results return). The argument is that a loop without a check that can actually fail is just a scheduler, and that most teams build the work first and bolt a model-based review onto the end. The graph layer gets four node types — splitter, worker, code node, gate — plus two return edges: a short correction edge that fixes the current run, and a long learning edge that feeds an accepted result back into the splitter's brief as a constraint. Gates should open by blast radius, not model confidence, with irreversible work in a lane that never opens. Written for engineers still approving every step by hand.