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agent-orchestration

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Meta Engineering 2026-10-23-3

The Thin Orchestrator: How We Made Our AI Agents More Reliable by Giving the Router Less to Do

Meta's orchestrator is 1,300 lines, routes 20+ workflows to 14 subagents and does no domain work; only step 6 of its fixed 7-step protocol involves an LLM. A single agent hit 70-80% success with per-task manual prompts and 10-20% without, and column config prep fell from 3-4 days to under an hour (self-reported). It is the same move as 1Password's, applied to routing: the model gets isolated context to be creative in, and nothing deterministic is left for it to hallucinate.

YouTube (Corey Gallon, Rexmore) 2026-10-14-1

I Believe Everything My Agents Tell Me: Three Levels of Review — Corey Gallon, Rexmore

Gallon's agent produced a letter whose numbers were right to the cent and whose premise was wrong, which is exactly the failure reconciliation can't see. Only the role-based cold reviewers attacked the frame; the invoice check would have passed it. In about 4 in 10 analysed 2026 sessions an agent got something wrong that mattered, so self-reported completion plus a spot-check is no longer a defensible default, and verification effort will have to scale with stakes.

Microsoft Blog 2026-05-05-3

Microsoft's Frontier Firm Has a Comp-System Problem

Microsoft's Frontier Firm post buries the binding constraint on enterprise AI value capture in plain sight. Only 13 percent of workers say they are rewarded for reinventing work with AI even when results do not materialize. Until that compensation-design number moves, Cowork, the plugin ecosystem, and the four-pattern taxonomy are downstream of the actual problem.

Fortune 2026-04-25-3

Cursor used a swarm of AI agents powered by OpenAI to build and run a web browser for a week—with no human help

Every AI headline reports the model that did the work. Wrong unit of analysis. GPT-5.2 didn't build a browser; Cursor's planner-worker-judge harness built one using GPT-5.2 as substrate. Value accrues to whoever owns the orchestration layer, not to whoever trained the weights.