I appreciate the overall sentiment of the post, but I can't say I would choose anything like the implementation the author is suggesting. My takeaway is to avoid relying too heavily on LLMs both in terms of the scope tasks given to them as well as relying too heavily on any specific LLM. I think this is correct for many reasons. Firstly, you probably don't want to compete directly with ChatGPT, even if you are using…
Don't build AI products the way everyone else is doing it
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Re: Don't build AI products the way everyone else is doing it
#22One simple example are e-mail clients. Somebody asks for a decision or clarification. The AI could extract those questions and just offer some radio buttons, like:
Accept suggested appointment times: [Friday 10:00] [Monday 11:30] [suggest other]
George whats to know if you are able to present the draft: [yes] [no]
I think Zendesk (ticketing software for customer support) already has some AI available. A lot of support requests are probably already answered (mostly) automatic.Human resources could use AI to screen job applications and let an AI resarch additional information about the applicant on the internet, and then create standardized database entries (which may be very flawed).
I think those kind of applications are the interesting ones. Not another ChatGPT extension/plugin.
Re: Don't build AI products the way everyone else is doing it
#23Earlier quoted context omitted.
> I am about 80% of the way through integrating with the OAI assistant API. I've been there. Turns out, the last 20% takes x10 the time and effort compared to these first 80%.
Sounds like a normal development project then.
Re: Don't build AI products the way everyone else is doing it
#24Great tips. I tried to do this with SVG icons in https://unstock.ai before a lot of people started creating text-to-vector solutions. You also have to keep evolving!
Re: Don't build AI products the way everyone else is doing it
#25> The solution: create your own toolchain No thanks. I have an actual job & customer needs to tend to. I am about 80% of the way through integrating with the OAI assistant API. The real secret is to already have a viable business that AI can subsequently improve . Making AI the business is a joke of a model to me. You'd have an easier time pitching javascript frameworks in our shop. Our current application of AI is a…
Re: Don't build AI products the way everyone else is doing it
#26With the pace of AI, that (large) investment into a custom toolchain could be obsolete in a year. It feels like ChatGPT is going to gobble up all AI applications. Data will be the only differentiator.
There's not even a good way to benchmark language models at the moment.
Re: Don't build AI products the way everyone else is doing it
#27Earlier quoted context omitted.
> I am about 80% of the way through integrating with the OAI assistant API. I've been there. Turns out, the last 20% takes x10 the time and effort compared to these first 80%.
Sounds like a normal development project then.
Re: Don't build AI products the way everyone else is doing it
#28This is a thought-provoking post and I agree with the "avoid using AI as long as possible" point. AI is best used for things that can only be accomplished with AI--if there's any way to build the feature or solve the problem without it, then yeah, do that instead. Since everyone now has more or less equal access to the best models available, the best products will necessarily be defined by everything they do that's n…
Re: Don't build AI products the way everyone else is doing it
#29> When passing an entire design specification into an LLM and receiving a new representation token by token, generating a response would take several minutes, making it impractical. Woe is me, it takes minutes to go from user-designed mockup to real, high-quality code? Unacceptable, I tell you! But seriously, if there are speed improvements that you can make and are on the multiple-orders-of-magnitude then I do get i…
I use it for exactly this use-case, converting mockups to code, but you need short feedback loops.
It will get things wrong. There'll be things it misunderstood, or small tweaks you realise you need after it's done its first job. Or maybe it misunderstood part of your design, or just needs extra prompting (ALL CAPS for emphasis, for example).
Even after multiple iterations it will extremely rarely be perfect, which is fine, because once it has a decent readable solution, you can obviously take ownership of it for yourself.
Where minutes might be fine would be in a "handoff" workflow, where designers do design and then handoff to devs. 10 minutes in between of AI processing to get something for the dev to start on would be acceptable, and the dev could then take that first attempt and using GPT4 refine it a bit. But I don't really like handoff teams anyway..
Re: Don't build AI products the way everyone else is doing it
#30> The solution: create your own toolchain No thanks. I have an actual job & customer needs to tend to. I am about 80% of the way through integrating with the OAI assistant API. The real secret is to already have a viable business that AI can subsequently improve . Making AI the business is a joke of a model to me. You'd have an easier time pitching javascript frameworks in our shop. Our current application of AI is a…