AI Session Reviews: Remember the Middle as Well as the Ending

The conversation ends well. After several confused attempts, the AI assistant finally produces the outline you wanted and closes with an encouraging message. You leave feeling pleased. Later, someone asks whether the session was useful, and the successful finish becomes the answer.

That answer may capture something real while leaving out something important. How long did the confusion last? What work remained? Was the ending a sign of a productive process, or a welcome recovery after an unnecessarily difficult one?

For creators and business owners, reviewing AI use means making room for both the remembered impression and the experience that unfolded. A pleasant ending deserves to count. It should not have to carry the entire evaluation.

Remembering an experience is a form of judgement

In research published in July 1993, Barbara Fredrickson and Daniel Kahneman examined retrospective evaluations of pleasant and aversive film clips. Their experiments compared responses during experiences with later overall judgements. Duration had a relatively small influence on retrospective evaluations, and its influence was further reduced when judgements were made from memory.

The researchers described evaluations in terms of selected snapshots rather than a simple accumulation of every moment. This does not mean people cannot remember duration, or that time never matters. It concerns how experiences were evaluated in those experiments.

A March 2000 paper by Charles Schreiber and Kahneman studied unpleasant sounds with varying loudness and duration. One experiment found a preference for episodes extended by a less aversive ending. The result illustrates how changing the final part can affect preference without making the episode shorter.

Neither paper tested AI conversations. Applying the ideas here is an editorial inference: when evaluating an extended interaction, it is worth checking whether a memorable moment is representing more of the session than it should.

A fictional outline session

Imagine Nneka using an AI assistant to plan a short workshop. For the first part of the session, the proposed structure repeatedly ignores her audience. She clarifies the brief, edits several suggestions and eventually receives a useful outline.

These events are hypothetical, not an account of a real user or a measured product test. Suppose she describes the session afterwards as excellent because the final outline feels right. That description tells us about her overall impression. It does not establish how efficiently the useful outline was reached.

Now imagine a different session that helps her make steady progress, followed by an awkward final reply. She might leave irritated even though much of the work was useful. The irritation need not be dismissed, but the last reply should not erase the completed work.

Both examples invite a fuller account. What happened at the beginning, during the main work and at the end? Which difficulties were resolved, and which were merely left behind when the conversation stopped?

Separate feeling, process and result

A practical review could use three distinct questions. How did the interaction feel? What did the process require? What usable result did it produce? These questions can have different answers.

For Nneka, the ending may have felt encouraging. The process may have required repeated corrections. The result may still be a good first outline that needs checking against the workshop brief. None of those observations cancels the others.

This distinction also protects positive experiences from an overly narrow efficiency test. A conversation could help someone explore an idea they care about even when it produces no finished document. The intended purpose needs to be stated before judging whether the time was worthwhile.

That connects with MaryChuks.com’s discussion of deciding what counts as a good day: the measure should reflect what the person values and intended to do, rather than whichever outcome is easiest to count.

Make a short record while the details are available

For a work session like the fictional example, I would suggest a brief note containing:

• The purpose at the start: what help did I want?
• One useful moment from the main work, not only the ending.
• One difficulty, including whether it was resolved.
• The time spent, if time matters to this task.
• The result and any checking or follow-up still required.
• My overall impression of the interaction.

This is a proposed reflection method, not a validated psychological scale. It is intended to make the review inspectable. You can keep it simple enough that recording it does not become a larger task than the work itself.

If the purpose is to compare tools, use the same questions across comparable tasks. If the purpose is personal reflection, the note may be more descriptive. Avoid turning an informal impression into a precise-looking score that suggests more certainty than the observations support.

Let AI organise the account without supplying missing memories

An assistant could help format notes that you have already written. A bounded request would be to group the observations under purpose, process, result and impression, while keeping uncertainties visible.

If all you provide is that the ending felt good, the assistant does not have evidence that the middle went well. Ask it to leave that part unspecified. A plausible narrative about steady progress would still be invented if your notes did not establish it.

Likewise, a transcript may show repeated revisions but not how you felt while making them. Some revisions may have been satisfying exploration; others may have been frustrating repair. Your account and the visible conversation supply different kinds of information.

The useful review therefore retains attribution: these are my reported feelings; these are actions visible in the record; these are interpretations that remain tentative.

Improve the experience rather than polish the verdict

For someone designing an AI service, a thoughtful closing message can be appropriate. But the practical response to a difficult session should include examining the difficulty itself. Did the system miss a clear constraint? Did it require unnecessary repetition? Was the handover usable?

An improved ending and an improved process are different changes. If a team evaluates only the final satisfaction response, it should be cautious about claiming that the whole interaction became easier.

For Nneka, the most useful conclusion might be that the final outline was worth keeping, while the initial brief needs a clearer audience statement next time. Another session might suggest that the tool is a poor fit. The review should leave room for either result.

A remembered impression is part of the evidence about an experience. Putting it beside a short account of the session gives it context. The ending can then be appreciated for what it contributed, while the rest of the interaction remains available for learning.

Sources

• Fredrickson and Kahneman, Duration neglect in retrospective evaluations of affective episodes — Journal of Personality and Social Psychology, July 1993.
• Schreiber and Kahneman, Determinants of the remembered utility of aversive sounds — Journal of Experimental Psychology: General, March 2000; DOI: 10.1037/0096-3445.129.1.27.