While I tend to agree with your premise that the linked article seems to be reasoning to the extreme off the basis of a very small code snippet, I think the core critique the author wants to make stands:

AI agents alone, unbounded, currently cannot provide huge value.

> try asking cursor for potential refactors or patterns that could be useful for a given text.

You, the developer, will be selecting this text.

> try giving them an abstract jira ticket or asking what it things about certain naming, with enough context

You still selected a JIRA ticket and provided context.

> ask any engineer that saves time with everything from test scaffolding to run-and-forget scripts.

Yes that is true, but again, what you are providing as a counterfactual are very bounded, aka easy contexts.

In any case, the industry (both the LLM providers as well as tooling builders and devs) is clearly going into the direction of constantly etching out small imoprovements by refining which context is deemed relevant for a given problem and most efficient ways to feed it to LLMs.

And let's not kid ourselves, Microsoft, OpenAI, hell Anthropic all have 2027-2029 plans where these things will be significantly more powerful.