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World desk2 min

You Cannot Make the Agent Fast Enough. Move the Wait Instead.

If an AI call cannot be fast enough to hide, run it before the user needs its result. Michael Hairetis’s learning-app example shows the trade-off and the reliability conditions.
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When an AI-generated result cannot arrive quickly enough to hide its latency, schedule the work before the user needs it. In a learning app built by Michael Hairetis for his two children, generating the next question during the current one still sometimes left a spinner between questions. His redesign prepared complete lessons ahead of time, so opening one was a database read rather than a new agent call.

Why generating the next item on demand still caused a wait

Hairetis describes building a small learning app for his two children on agent infrastructure he also used for other platforms. In an unattended orchestration job, a slow call was less visible; in the app, a child waiting between questions made the delay immediate.

The first design made one question per agent call and prefetched the next question while the child worked. That moved some of the generation into otherwise useful time, but it did not guarantee the next question would be ready. If prefetching was still underway when the child finished, the app showed a spinner.

Move generation ahead of the interaction

The revised design planned three lessons at once and generated each lesson completely in one call before the child saw it. Hairetis reports that the first lesson took “a minute or two”; later lessons could be built in the background while the child worked on the first. The initial wait remained, but it happened before the active sequence rather than between its questions.

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Once a lesson was complete, opening it became a database read. Hairetis reports measuring that operation at six milliseconds in his own app. This is an author-reported implementation measurement, not an independent benchmark or a general guarantee about database reads or agent systems.

What makes this pattern work

Prepare usable work, not a promise of future work

A pre-generated lesson needs to be genuinely complete enough for the user to start. If it is only a plan containing placeholders, the app still has to call the agent during the session, putting the wait back in the user’s path.

Let background work survive interruption

Background generation must be durable across server restarts. Hairetis warns that an in-flight asynchronous task can die silently, leaving a lesson marked “building” without a result. A production design therefore needs a way to persist work state and detect, retry, or otherwise recover interrupted generation instead of treating a launched task as a completed one.

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When to move the wait—and when not to

This approach trades an up-front wait for fewer interruptions during use; it does not make generation itself faster. It fits best when there is a predictable next interaction, the user can wait before beginning or keep using the current item while preparation runs, and the output can be completed in advance.

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For a design decision, compare the alternatives by asking where the wait lands, what the user can do while work runs, whether the prepared output is actually complete, and how interrupted background work is detected and recovered. If the user needs to shape the result step by step, or the next task cannot be predicted, pre-generating a complete unit may not remove the important wait.

Hairetis’s account is a concrete design example, not evidence that all users prefer an up-front delay or that this architecture improves performance in every app. Its useful insight is narrower: when a call cannot be made invisible, changing when it runs can make the user-facing interaction feel immediate.

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