Average is all you need

But nobody bothered to check if it was correct. It might seem correct, but I've been burned by queries exactly like these many, many times. What can often happen is that you end up with multiplied rows, and the answer isn't "let's just add a DISTINCT somewhere".

The answer is to look at the base table and the joins. You're joining customers to two (implied) one-to-many tables, charges and email_events. If there are multiple charges rows per customer, or an email can match multiple email_events rows, it can lead to a Cartesian multiplication of the rows since any combination of matches from the base table to the joined tables will be included.

If that's the case, the transactions and revenue values are likely to be inflated, and therefore the pretty pictures you passed along to your boss are wrong.

Further reading, and a terrific resource:

https://kb.databasedesignbook.com/posts/sql-joins/#understan...

I think this is important, because if his hypothesis is right, then LLMs behave differently here: They really are average in all dimensions. They are the pilots the Air Force thought they had before Daniels made the study.

So if he is right, we'd be changing from a mostly-non-average to a mostly-average society, which would really be a massive change - and probably not a good one IMO.

[1] https://noblestatman.com/uploads/6/6/7/3/66731677/cockpit.fl...

Why didn’t the boss ask the AI for the charts to begin with?

Everyone’s income is going to be below average, because they got fired.

You might say it "still less work" and that's true, perhaps, only for the first few times. After a while you _learn_ how to do it, and understand how to _think_ with the language of your data. With LLMs, you never get this benefit, and also loose your ability to judge the LLM's output properly.

But again, that might be enough on your case, or, you simply don't _know_.

When it comes to bs dashboard where "average is all you need", maybe the "better than average" result would be asking yourself if it's even worth doing in the first place?

Do you know enough about JOINs and how they work to be able to break those big queries down and figure out whether they are doing exactly what you're asking for in English?

> ninety percent of everything is crud

https://en.wikipedia.org/wiki/Sturgeon%27s_law

Yes, thinking about your data and how to check it is so annoying. Much better to do something average, see if the result puts you in a good light, and share that insight into your company's working with ~~everyone on the internet~~ your boss.

Rarely have I seen "we help you create meaningless slop more easily" advertised so explicitly. Or is this also average?

It makes me wonder if Hacker News has a silent majority of people who would actually use AI in this way without wanting to admit it, and a vocal minority of people who wouldn't.

where it gets interesting is when you have a custom system that your LLM surely never saw (custom ERP) that has 50 sometime cryptic tables, unclear look up tables and unexplained flags.

something no text2sql solution solved for us.

we built a second mcp that lets the agent look up business logic (generated from source code) and then does better queries. that i think is something i never read in a blog post about a text2sql solution.

And there is a lot of that type of work to do if you're trying to grow a business. But, something in there should be trying to be exceptional or else you have no moat. Claude will probably not be able to breeze through that part with the same amount of ease...

It's a post claiming average AI is useful... by a for-profit "data platform with a CLI that LLM agents can use directly". What are they going to do? Criticize the whole industry they are selling to?

Not all context is documented, and some context has to even be changed because it doesn't make sense.

I find AI very useful, but I think a lot of this AI SQL products are misleading.

Why is that a good thing? Claude didn't ask any obvious follow up questions, like what determined whether a user got an email or not? It is using the ab test terminology in Step 3 without any kind of confirmation that this is, you know, a valid test.

if anything it makes the world more dangerous

a reckoning is coming

the top decile will be janitors for the rest

A car that starts 50% of the time ?

A plane that stops on 50% of the flights ?

A pacemaker that beats only 50% of the time ?

David Goodenought said that average is enough ..

Pass.

    This is not only average. This is actual magic.

    So let's be real: the SQL is average. The joins are average. The chart is average. And that took us less than 5 minutes and that was amazing, that is the entire point.

    You did not need a data engineer to model your HubSpot data, or a meeting to agree on whether it should be last-click or first-click or linear or time-decay or whatever.

    You needed a query, written fast, on data you already own. Your LLM wrote it. You confirmed it made sense. Your manager got a link.


    Honestly, average is clearly magic; prove me wrong.

It is like nails on a chalkboard.