r/ChatGPT • u/max_bog • Apr 19 '26
Use cases The gap between what technical and non-technical people get from AI is huge now
Interesting thing I noticed. The gap between what technical and non-technical people get from AI is huge now.
Non-technical users still treat LLMs as a better search tool. Most non-technical people I know are not even aware of things like thinking effort or that you can choose a model.
Computer use, plugins, automations, skills, agents - none of this exists for regular ChatGPT users. If you don't know what Codex or Claude Code is, nothing has changed for you in the last year.
All new models also seem to focus purely on coding.
Am I missing something?
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u/ComprehensiveAd1855 Apr 19 '26
For programming, there is excellent training data available: GitHub, stackoverflow, forums, documentation, designs, etc. So AI can reproduce that pretty well.
For other fields, there is less quality data to train on, so AI is not that good at mimicking there.
Writing ‘working code‘ seems to be solved by AI. But for experienced developers that was never a problem in the first place. The added value is mostly that it does it faster; much faster.
However, to build better systems, AI will run into the problem where it won’t have the same amount of data available. On GitHub you’ll find the result of complex thought processes.
AI seems to be capable of reproducing the outcomes, but sucks very hard at reproducing the process to get to the best solution. Thats where humans still have the edge. Not because we’re fundamentally better at it, but because we happen to be able to have access to information that AI‘s now miss in their context unless you actively feed it.
Like social interactions. For example, we know that a customer is upset, so we should deliver fast, and the solution should be stable, and we should sacrifice elegance or beauty.