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Agentic AI systems violate the implicit assumptions of database design

arpitbhayani.me

11–20 of 115 posts

Re: Agentic AI systems violate the implicit assumptions of database design

#11
I totally agree on investing in a sane data model upfront. So many production systems have schemas that only made sense to the engineer that created them. I would be delighted if I can read a schema and understand what a column means without having to dig through a bunch of migration PRs.

I recently encountered `is_as BOOL` in an important table. After way too much invested time we found out it meant "is active service".

Re: Agentic AI systems violate the implicit assumptions of database design

#12
post #2

Giving LLM agents direct, autonomous access to a real production databases with write access seems insane to me. NO ONE, agent or human, should have direct write access to production databases outside of emergency break glass scenarios. This is why we have stored routines and API layers to pre-define what writes are allowed. The facts that agents CAN autonomously write to a database does not imply that they should. F…

How does that even work in compliance-relevant scenarios where the audit trail shows some LLM messed with the data? Who, if anyone, is on the hook?

Re: Agentic AI systems violate the implicit assumptions of database design

#13
post #4
post #2

Giving LLM agents direct, autonomous access to a real production databases with write access seems insane to me. NO ONE, agent or human, should have direct write access to production databases outside of emergency break glass scenarios. This is why we have stored routines and API layers to pre-define what writes are allowed. The facts that agents CAN autonomously write to a database does not imply that they should. F…

LLM agents are unlocking demand and supply for applications that wouldn't have been possible before due to time constraints though. There's a growing demand for single user or smaller scoped apps where giving LLM agents direct access means velocity. The failure/rollback model is much easier with these as long as we have good backup hygiene.

1) Can you explain what demand and supply mean in this context?

2) In regards to having good backup hygiene, who is we?

Re: Agentic AI systems violate the implicit assumptions of database design

#14
post #4
post #2

Giving LLM agents direct, autonomous access to a real production databases with write access seems insane to me. NO ONE, agent or human, should have direct write access to production databases outside of emergency break glass scenarios. This is why we have stored routines and API layers to pre-define what writes are allowed. The facts that agents CAN autonomously write to a database does not imply that they should. F…

LLM agents are unlocking demand and supply for applications that wouldn't have been possible before due to time constraints though. There's a growing demand for single user or smaller scoped apps where giving LLM agents direct access means velocity. The failure/rollback model is much easier with these as long as we have good backup hygiene.

But are those users allowed to see all the data in the databawe by the law? Some privacy laws require that personal information must be hidden from employees unless they have a narrow and specific business reason to view it. Blanket full access to a database may be illegal for that reason.

Re: Agentic AI systems violate the implicit assumptions of database design

#15

There are two broad types of databases: operational and analytical. Operational databases store transactions and support day-to-day application workflows. For analysis, data is often copied into separate analytical databases (data warehouses), which are structured for efficient querying and large-scale data processing. These systems are designed to handle complex, random queries and heavy workloads. LLM agents are th…

> LLM agents are the best way to analyze data stored in these databases

Why, and how?

Re: Agentic AI systems violate the implicit assumptions of database design

#16
post #7
post #4

Earlier quoted context omitted.

LLM agents are unlocking demand and supply for applications that wouldn't have been possible before due to time constraints though. There's a growing demand for single user or smaller scoped apps where giving LLM agents direct access means velocity. The failure/rollback model is much easier with these as long as we have good backup hygiene.

This makes no sense whatsoever. It's not news that if you just give all developers at a company write access to the production databases, owner permissions on all resources, etc. that velocity can be increased. But at what cost? The reason we don't do that in most cases is that "move fast and break things" only makes sense for trivial, non-critical applications that don't have any real importance, like Facebook.

I think the argument would be mostly about the companies where such trivialities like proper auth were given up to maximum possible extent. I'm sure even some bigger ones are only gnashing their teeth over implementing security measures that are required by law and not seeing much point to it.

Re: Agentic AI systems violate the implicit assumptions of database design

#17
post #10

Giving an LLM write access is insane but I gave LLM’s read-only access to our database and it’s been a huge productivity win. Executives who wouldn’t take the time to build a report are happy to ask an AI agent to do so.

How do you validate that the reports are correct? What if an executive makes a wrong business decision because the LLM wrote a wrong SQL query?

The same way we've always done it - glance at it and see if the numbers look like they're within an order of magnitude of what looks reasonable.

Re: Agentic AI systems violate the implicit assumptions of database design

#18
post #7
post #4

Earlier quoted context omitted.

LLM agents are unlocking demand and supply for applications that wouldn't have been possible before due to time constraints though. There's a growing demand for single user or smaller scoped apps where giving LLM agents direct access means velocity. The failure/rollback model is much easier with these as long as we have good backup hygiene.

This makes no sense whatsoever. It's not news that if you just give all developers at a company write access to the production databases, owner permissions on all resources, etc. that velocity can be increased. But at what cost? The reason we don't do that in most cases is that "move fast and break things" only makes sense for trivial, non-critical applications that don't have any real importance, like Facebook.

This comment is savage and I’m here for it.

Re: Agentic AI systems violate the implicit assumptions of database design

#19

Giving an LLM write access is insane but I gave LLM’s read-only access to our database and it’s been a huge productivity win. Executives who wouldn’t take the time to build a report are happy to ask an AI agent to do so.

I would hope that you're running this on a replica so that the massive table scan doesn't choke writes to the main db. Even then it's possible to bring the replica down and depending on the technology still create a problem (WAL backup for instance)

Another way to bring prod down even with read is depending on your atomicity settings, try starting a transaction and don’t commit or abort it, just leave it dangling. That’s a cute one

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