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Andrew Ng says bottleneck in AI startups isn't coding – it's product management

(www.businessinsider.com)
120 points cl42 | 1 comments | 27 Aug 25 19:43 UTC | HN request time: 0s | source
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betaby ◴[30 Aug 25 15:04 UTC] No.45075275[source]▶
If AI is that good, can someone code a good XML library with AI? The spec is available.

If AI is that good, there should be an explosion of Open Source projects of good quality.

Neither of those is happening.

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megaloblasto ◴[30 Aug 25 15:10 UTC] No.45075333[source]▶
Many people are seeing huge gains in coding productivity with AI. If you're not one of those people it might be useful to evaluate why you aren't experiencing any benefits, instead of claiming that there are none.
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zkry ◴[30 Aug 25 16:07 UTC] No.45075757[source]▶
I don't think this line of reasoning holds. The only thing people should look at are peer reviewed studies, lots of them ideally, and with no conflict of interest. Who's getting productivity gains? What kinds of work are they doing? What doesn't work so well? All of these questions should be investigated by studies. People feeling productivity gains doesn't imply the gains exist.

Otherwise it sounds like "many people have had their lives changed by {insert philosophical/religious movement}, so if you're not finding it true you should look into what's wrong with you."

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1. jaggederest ◴[30 Aug 25 16:24 UTC] No.45075864{3}[source]▶
> The only thing people should look at are peer reviewed studies, lots of them ideally, and with no conflict of interest.

"Ignore your own direct experience, only research papers matter" is certainly a take.

The beautiful thing about the current generation of tools is that they are so incredibly cheap relative to historical tools intended to improve engineering productivity. You can't just run out and pick up CASE tools for less than ~$CAR to ~$HOUSE. A pro subscription to whichever AI tool you want to try is $20.

Ignore research, try them, if you have success, use them. There's no dogma here. Just empiricism.