[AnEro]

I think that MIT study of 95% of internal AI projects failing has scared off a lot of corporations from risking time in it. I think they also see they are hitting a limit of profitable intelligence from their services. (with the growth in inelegance the past 6–8 months being more realistic, not the unbelievable like in the past few years)

I think everyone is starting to see this as a middle man problem to solve, look at ERP systems for instance when they popped up it had some growing pains as an industry. (or even early windows/microsoft 'developers, developers, developers' target audience)

I OpenAI see it will take a lot of third party devs to take what OpenAI has and run with it. So they want to build a good developer and start up network to make sure that there are a good, solid ecosystem of options corporations and people can use AI wise.

[Workaccount2]

The MIT study found 90% of workers were regularly using LLMs.

The gap was that workers were using their own implementation instead of the company's implementation.

[keeda]

The MIT study as released also does not really provide any support for the 95% failure rate claim. Until we have more details, we really don't know where that number came from:

https://www.linkedin.com/feed/update/urn:li:activity:7365026...

[AnEro]

Yea from what I understand 'Chats' and AI coding are something they already have market domination/are a leader on and are a good/okay product. It's the other use cases they haven't delievered on in terms of other companies using them as a platform to deliver AI apps, which I would imagine would have been a huge vertical in their pitches to investors and internal plans.

These third-party apps get huge token usage with agenentic patterns. So losing out on them and being forced to make more internal products to tune to specific use cases is not something they want to biuld out or explore