Pitfalls of Multi-Agent Content Workflows: Which Parts Should Never Be Agentic?
Typical-Baker9262 · reddit · 2026-08-03
A developer is building a human-approved multi-agent content workflow on a VPS, where agents handle research, filtering, drafting, and visual briefs, while the human retains final approval for all public actions.
The creator is trying to solve four engineering problems before scaling:
- Model Routing: Routing hard judgment tasks to stronger models and routine extraction/classification to faster ones.
- Cost Control: Capping token spend without lowering the evidence bar.
- Inspectability: Keeping handoffs, source freshness, and agent states inspectable.
- Deterministic Checks: Using deterministic code wherever LLM judgment is unnecessary.
The author seeks concrete failure modes and design patterns from practitioners, asking which parts of a workflow should never be automated, how to route models effectively, what evaluations catch hidden failures, and how to make human approval useful rather than a bottleneck.
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