Are they doing the same thing? Are they trying to achieve the same goals, but fail because one is lacking some skill?
One person may be someone who needs a very basic thing like creating a script to batch-rename his files, another one may be trying to do a massive refactoring.
And while the former succeeds, the latter fails. Is it only because someone doesn't know how to use agentic AI, or because agentic AI is simply lacking?
* strictness of the result - a personal blog entry vs a complex migration to reform a production database of a large, critical system
* team constraints - style guides, peer review, linting, test requirements, TDD, etc
* language, frameworks - quick node-js app vs a java monolyth e.g.
* legacy - a 12+ year Django app vs a greenfield rust microservice
* context - complex, historical, nonsensical business constraints and flows vs a simple crud action
* example body - a simple crud TODO in PHP or JS, done a million times vs a event-sourced, hexagonal architecrtured, cryptographical signing system for govt data.
Bad with regex or things involving recursion.
Also bad at integration between modules. I have not tried to solve this yet, by giving documentation of both the modules.
Also model used impacted. To understand java code it was great.
I first ask it to generate the detailed prompt by giving a high level prompt. Then use the detailed prompt to execute the task.
Java code size Upto 20k loc is fine. Other wise context becomes big. So you have to do module by module.
I believe to have a discussion maybe someone has to take an open source code example and then say it doesn't work. Other people can then discuss and decide.
Overall happy with gpt5 and claude code.
Edit:updated bad at integration
You should first draft the interface and roll out coverage with automated tests, and then prompt your way into filling in the implementation. If you just post a vague prompt on how you want multiple modules workinh together, odds are the output might not met implicit constraints.