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Microsoft · AI agents2 min read

Microsoft says AI agents that work for days need new computer systems

Microsoft says AI agents that work for hours or days need a different computing foundation, and offers three questions to test whether your business is ready.

By the Dashline deskSource: Microsoft Azure blog
Microsoft says AI agents that work for days need new computer systems
Photo: Microsoft Azure blog

Microsoft says the next stage of AI is software that works on a task for hours or days, not just one that answers a single question. It argues this needs a different kind of computer foundation. The claim comes from a post on the Microsoft Azure blog, which carries a note saying it was written and paid for by Microsoft.

What an agent does

An AI agent is software that carries out a job on its own, step by step. Microsoft says one agent may move between reasoning, finding data, using tools and running code, while keeping its progress along the way. Its needs can change mid-task. It may need a burst of computing power, then fast access to large amounts of data, then a pause while another tool or agent finishes.

Why old setups may fall short

Earlier cloud software often followed predictable paths, such as a request followed by a response. Microsoft says agents are different because their work is long and unpredictable. Its answer is that chips, computing, storage and networking should be designed and tuned as one system. More computing power alone will not help, it says, if data cannot move quickly or progress cannot be saved between steps.

The Levi Strauss example

The post points to Levi Strauss & Co. The company moved its data centers to Microsoft Azure, consolidated its ERP platforms, modernized applications and unified its data in a governed, real-time layer. It is now building a "super agent" to coordinate more than 1,000 agents, each focused on a specific area of the business.

Three questions to ask

Microsoft suggests technical leaders start with these checks:

  • Do you have the computing, storage and networking agents need, or are you running tomorrow's apps on yesterday's platform?
  • Can you pick the right model, run time, chip and location for each job, balancing cost, speed, complexity and risk?
  • Can agents help run the platform itself, by speeding up launches and fixing problems before they cause disruption?

What is not known

The post gives no test results, prices or timelines. Levi Strauss is described as building its super agent, with no results shared. The post also concludes that Azure is the right foundation, so it works as a sales pitch. The three questions are still a reasonable way to review your own systems, whichever vendor you use.

The takeaway

Before committing to AI agents, check whether your systems can handle long, unpredictable work, and treat vendor claims with care.

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