模型强还不够：从 Gemini 4 与 Sonnet 5.5 看能力、成本和产品体验

A voluntary safety accord can create a channel for cooperation, but its credibility depends on concrete internal controls and independent auditing rather than ceremonial agreement alone.

An AI portal that searches government information is not yet an integrated service agent, because executing transactions requires agency interfaces, identity controls, and reliable handling of sensitive data.

Investigations under existing consumer-protection rules may address agent failures, while the existence of an inquiry does not establish wrongdoing or resolve questions about enforcement credibility.

Gemini 4 Argon's reported benchmark gains suggest renewed competitiveness, but restricted access prevents most users from determining whether those gains transfer to their own workloads.

A frontier model does not by itself supply a competitive coding harness or personal agent, so product execution can remain a bottleneck even after benchmark performance improves.

Sonnet 5.5 can deliver strong capability, yet extensive reasoning and token consumption may make a particular high-effort run more expensive than an Opus alternative despite apparently attractive nominal pricing.

A model's best role may be tactical implementation within a larger agent workflow, rather than serving as the default choice for every strategic and execution task.

Muse's rapid adoption suggests that accessible user experience matters, while reports of capability limits leave open whether convenience can compensate for a weaker underlying model over time.

An agent intended to manage work across familiar products can still create friction when its permissions and data access do not match the responsibilities users expect it to handle.

A service-specific agent can simplify ordering by connecting identity, preferences, payment, and fulfillment, while keeping third-party access open preserves flexibility in an unsettled distribution market.