When AWS announced AgentCore in July, the company made an unusual claim: agent sessions that run for up to eight hours—"the longest in the industry" for asynchronous workloads. Not eight minutes. Eight hours of continuous, autonomous execution.

The technical documentation describes the architecture in detail:

• Dedicated microVMs that persist across multiple invocations
• Health check systems that monitor background processes
• Session isolation that prevents cross-tenant contamination

AWS built sophisticated infrastructure to support workflows that span an entire business day.

Then you look for the use cases.

The general availability announcement in October lists early customers—Sony, Thomson Reuters, National Australia Bank. But nowhere in the documentation, blog posts, or customer testimonials does anyone describe an actual eight-hour workflow. The marketing materials mention "complex asynchronous workloads" and "extended problem-solving sessions" without showing what those look like in practice.

Meanwhile, Google, Microsoft, and OpenAI don't prominently advertise runtime duration limits at all. Their documentation focuses on rate limits and throughput. Session length isn't yet a competitive factor that shapes buying decisions.

This gap reveals where agent adoption actually is. The infrastructure exists for fully autonomous, multi-hour workflows. Most organizations are still learning to trust agents with 15-minute tasks.

Consider what an eight-hour workflow actually requires:

• Success criteria precise enough that an agent can execute without human judgment for an entire workday
• Monitoring systems that can detect drift or errors hours into execution
• Organizational confidence that the output will be trustworthy enough to act on
• Workflows where eight hours of autonomous execution creates more value than eight hours of human-supervised work

Those workflows exist in theory—reconciling massive datasets across fragmented sources, conducting exhaustive competitive analysis across thousands of properties, processing complex compliance checks at scale. The market hasn't publicly demonstrated them yet because the organizational infrastructure to support them is still being built.

AWS built the runtime capability. Enterprises are still developing the operational maturity to use it. You can provision an eight-hour session, but can you define what should happen during those eight hours? Can you monitor it? Can you trust the output enough to act on it without verification?

Vendors building ahead of market readiness is how infrastructure markets work. The capability becomes available before the use cases crystallize. Early adopters experiment quietly. Eventually, someone figures out how to operationalize what was previously just technically possible, and the market shifts.

The signal isn't that AWS built something unnecessary. The signal is timing. When organizations develop enough confidence in agent reliability to let software work unsupervised for a full business day, the infrastructure will be waiting. AWS is betting that moment arrives sooner than the current silence around eight-hour use cases suggests.

Runtime limits matter less than organizational readiness. Can your team define, monitor, and trust a workflow that should run unsupervised for eight hours? For most teams, not yet. Building that operational maturity happens through successfully automating shorter workflows first, developing trust through repeated success, and learning what reliable agent execution actually looks like at scale.

The eight-hour runtime will matter when enterprises are ready for it. Right now, it's infrastructure waiting for adoption to catch up.