> research aided by my agent Also not good enough.

As an example: Yesterday i asked Claude and ChatGPT to design a circuitry that monitors pulses form S0 power meter interface. It designed a circuit that didn't have any external power to the circuit. When asked it said "ah yes, let me add that" and proceeded to confuse itself and add stuff that are not needed, but are explained and sounds reasonable if you don't know anything. After numerous attempts it didn't produce any working design.

So how can you verify that the therapist agent you've built will work with something as complex as humans, when it can't even do basic circuitry with known laws of physics and spec & data sheets of no more than 10 components?

And the thing when it comes to therapy is, a real therapist doesn't have to be prompted and can auto adjust to you without your explicit say so. They're not overly affirming, can stop you from doing things and say no to you. LLMs are the opposite of that.

Also, as a lay person how do i know the right prompts for to work correctly?

Don't get me wrong, i would love for AI to be on par or better than a real life therapist, but we're not there yet, and i would advise everyone against using AI for therapy.

And there's a lot of enterprises that use that and pay a lot of money for it! The business side problem i can see is : how do you convince MS focused companies to use your product instead of SharePoint? Could your product be built on top of it?

Can you for example also enhance gSuite?

Thank you for open sourcing this, so others may learn from you or build upon your work!

[0] https://pubmed.ncbi.nlm.nih.gov/32418073/

The cloud counterpart had 600+ mongodb databases split amongst 3 Mongo clusters.

The integration team took usually 2 weeks to setup the on premises software, and the cloud stuff took about a minute. The entire setup for the cloud was a single form that the integration team filled in with data.

The point I'm trying to make, is that if your customers require separate infra, they can wait a bisuness day to be setup. Meanwhile they can play on a sandbox environment.

It's also doable in fully automated fashion, but you will have to have strong identity and payment verifications, to avoid DoS, and in those cases usually contracts fly around.

That's for the b2b side.

For b2c, usually you rely on a single db and filter by column ID or similar, which can easily be abstracted away.

I dot see the value proposition here. Let's take couple of examples

If I need to have my totally separate infra for each tenant I'm going to go for terraform

If I need separate database on the same db infra, I'm Goin to either have a db initialization script that creates a usable db or clones a template database already present

So why do I need your sdk? To avoid a call to postgres to execute a script or a terraform script?

How does that work with the need for prefilled data?

Maybe I'm missing something, but I do not understand this service.