Posted by petesergeant 4 days ago
About 25% of the sentences are rewrites from Claude for clarity and accuracy. Claude was also heavily involved in how the article is laid out, and challenged me to add several transitional pieces I wouldn’t have added otherwise. In all, I found it very helpful for writing this article, and strongly recommend using it for improving articles.
It’s just a tool that does well with language. You have to be smart about using it for that. And most people are. That’s why tools, MCPs, etc. are so big nowadays.
Is there some website where I can read more on what AI can do, instead of what it cannot do?
Its unlikely that they would change their approach, so the world and LLM creators would have to adapt.
https://phys.org/news/2025-03-atheists-secular-countries-int...
>The "Knobe effect" is the phenomenon where people tend to judge that a bad side effect is brought about intentionally, whereas a good side effect is judged not to be brought about intentionally.
(Note that DeepSeek got "good enough" with "only" FP8)
Have a conversation with a nontech person who achieves quite a bit with LLMs. Why would they give it up and spend a huge amount of time to learn programming so they can do it the "right" way, when they have a good enough solution now?
So:
- Humans make mistakes all the time and we happily pay for those by the hour as long as the mistakes stay within an acceptable threshold.
- Models/agents will get cheaper as diminishing returns in quality of results get more common. Hardware to run them will get cheaper and less power hungry as it increases in commodity.
- In all cases, It Depends.
If I ask a human tester to test the UI and API of my app (which will take them hours) the documented tests and expected results are the same as if I asked an AI to do it, the cost may be the same or less of an AI to do it but I can ask the AI to do it again for every change, or every week etc. Have genuinely started to test this way.
That humans make mistakes all the time is the reason we encode business logic in code and automate systems. An “if” statement is always going to be faster, more reliable, and have better observability than a human or LLM-based reasoning agent.
We don't, however, continue to pay for the same person who keeps making the same mistakes and doesn't learn from them. Which is what happens with LLMs.