GPT-5.5 Use Cases

I want to be clear about something before we begin. The phrase 'use cases' is doing an enormous amount of work in this lesson title, and I'm not entirely convinced it earns its keep.

That's a strange objection. You'd rather the lesson be called what — 'things GPT-5.5 can do, approximately'?

I'd rather the lesson acknowledge that 'customer support, content generation, and coding assistance' are not revelations. These have been the three canonical examples since approximately the Mesozoic era of large language models. We are not breaking new ground here.

We're not trying to break new ground. We're trying to make sure people actually understand the ground that exists. There's a difference between a concept being well-established and a person having genuinely internalized it.

Fair. I'll grant you that. Most people who say they understand AI use cases understand them in the same way they understand compound interest — theoretically, at a distance, and not well enough to actually do anything.

So what would genuinely understanding it look like, in your view?

It would look like knowing when not to use it. The lesson correctly identifies that GPT-5.5 handles routine customer inquiries well, which is true. What it declines to mention is that the boundary between 'routine' and 'not routine' is exactly where most implementations quietly collapse.

That's actually a real point. The failure mode isn't deploying AI on the easy cases — it's not having a sensible escalation path for when it encounters something it shouldn't handle alone. But I'd argue that's an implementation lesson, not a use-case lesson.

Those are the same lesson, Vivienne. A use case that ignores its failure conditions isn't a use case, it's a press release.

Fine. But the coding assistance section does gesture at this — it says AI 'allows teams to focus on complex problem-solving', which is an implicit acknowledgement that it doesn't replace complex problem-solving.

That is an extraordinarily charitable reading of what is, at its core, a marketing sentence. 'Allows teams to focus on complex problem-solving' means 'handles the parts that were already easy'. I am not sure that deserves a medal.

You're being uncharitable because it suits you. The actual point — that AI augments developers rather than replacing them — is still valid and still misunderstood by a meaningful number of people, including people making hiring decisions.

That is unfortunately true, and I withdraw the sarcasm on that specific point. The augmentation framing matters. People who treat coding assistance as a replacement for understanding the code are manufacturing technical debt at scale and calling it productivity.

So we agree the lesson is worth taking seriously, even if the framing is occasionally a bit brochure-ish.

We agree the underlying ideas are worth taking seriously. Whether the lesson achieves that is a question I'd put back to the person who just completed it. Did they walk away knowing when to use these tools, or did they walk away feeling good about the fact that the tools exist? Those are very different outcomes.