Agreed on the main claim that multi-agentic software development is a distributed systems problem, however I think the distributed consensus point is not the tightest current bottleneck in practice.
The article mentions the Partial Synchronous model (DLS) but doesn't develop it, and that's the usual escape hatch against FLP. In practical agentic workflows it's already showing up as looped improvement cycles bounded by diminishing returns. Each iteration is effectively a round, and each agent's output in that round is a potentially faulty proposal the next round refines. Painful in cost yes, but manageable. If models continue to improve at current rates, I think it's reasonable to assume the number of cycles will decrease.
The more interesting objection is that "agent misinterprets prompt" isn't really byzantine. The 3f+1 bound assumes independent faults, but LLM agents share weights, training data, and priors. When a prompt is ambiguous they don't drift in random directions, they drift the same way together. That isn't majority vote failing loudly, it's consensus succeeding on a shared bias, which is arguably worse.
Agreed on the main claim that multi-agentic software development is a distributed systems problem, however I think the distributed consensus point is not the tightest current bottleneck in practice.
The article mentions the Partial Synchronous model (DLS) but doesn't develop it, and that's the usual escape hatch against FLP. In practical agentic workflows it's already showing up as looped improvement cycles bounded by diminishing returns. Each iteration is effectively a round, and each agent's output in that round is a potentially faulty proposal the next round refines. Painful in cost yes, but manageable. If models continue to improve at current rates, I think it's reasonable to assume the number of cycles will decrease.
The more interesting objection is that "agent misinterprets prompt" isn't really byzantine. The 3f+1 bound assumes independent faults, but LLM agents share weights, training data, and priors. When a prompt is ambiguous they don't drift in random directions, they drift the same way together. That isn't majority vote failing loudly, it's consensus succeeding on a shared bias, which is arguably worse.
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