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dfabulich 2 hours ago [-]
I watched Dr. Hipp's keynote. Here's my summary for folks who don't want to sit through it. (This is hand written, not LLM-generated.)
Dr. Hipp suggests a definition of "AI" in which SQL planners are AI, defining AI as "any computing system that performs tasks typically associated with human reasoning, problem-solving, and decision-making." (He then explains briefly how SQL planners are runtime code generators. If you're not familiar with how SQL planners work, the keynote is pretty short and worth a watch.)
He then makes a recommendation to developers who are afraid that AI will take their jobs. He points out that SQL planners kinda take away part of the job of a developer, but really just changed the nature of the job.
He makes his point with a slide:
> Q: How can you avoid being replaced by AI?
> A: Solve more problems than you create.
He concludes with a recommendation against having LLMs generate your SQL entirely. He recommends writing it yourself in order to understand it better and engage both the part of your brain that process human language and the part of your brain that processes formal languages like SQL. (He gives an example of trying to ask a coworker for help, but solving the problem by explaining it to the coworker, and how valuable that experience is.)
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For my part, I'm not sure I agree with calling a SQL planner "AI" in 2026 (I think that obscures more than it reveals), but the advice to solve more problems than you create will always be wise.
abetusk 18 minutes ago [-]
The SQL planner is most definitely "AI", we're just so used to it that it's become trite to say so. I'm having trouble tracking down the version I heard about, but this essentially the "AI effect": "Every time we figure out how to do one of these tings, it ceases to be called AI and just becomes useful software" [0].
Part of the reason I'm dismissive of the current pushback against AI is that people have such a vague definition of it that it starts becoming all inclusive to subsume things like SQL, the Shazam algorithm, etc. Personally, I think it's a good reminder that SQL has quite a bit of intelligence in it. After all, SQL was one of the first mass successes of a declarative based engine.
Put another way, in some abstract sense, one of the differences between SQL query planning and an LLM is one of scale and compute. I wouldn't be surprised that, at some point in the future, we'll see LLM simulation in SQL(ite) akin to how people use different systems to run Doom.
I liked his note about how before SQL a lot of people were employed as COBOL programmers to painstakingly write systems that fetched and joined data by hand.
angry_octet 2 hours ago [-]
I suggested something similar in an internal chat, i.e. using AI as a tool to help specify, debug and improve your code, rather than delegating all coding to it, and I think the collective response was essentially 'ok grandpa'.
I think we have to expect the majority of SQL queries will soon be machine generated and machine tuned. The planner in database engines will use LLMs. There will be LLM chats to help you specify what query you want to make, and it will work out which tables etc via question and answer.
nemomarx 2 hours ago [-]
is that faster than just knowing what tables you want to run it on? I can see it for agentic but having to chat back and forth every time sounds frustratingly slow for my tastes
a1o 4 minutes ago [-]
Azure DataBricks has something called Genius where you put the tables and views you want to interact with and can talk to it so it constructs a query based on the data you specified. It often does not work completely for me, it either doesn’t get it, or get things 90% there and I need to jump in, decipher the query it came up with and then figure how to change it to what I need. So not sure if the data I am playing with is just too complex/too big, but it’s not working exactly great for me.
Every keynote, panel, and workshop from this year's Cesium DevCon is now free to watch, no signup. I work in DevRel at Cesium so wanted to flag it here since I don't think it's made the rounds yet.
Highlight for me: Richard Hipp (SQLite's creator) keynoted the opening session, marking 15 years of Cesium as an open source geospatial project. There's also a talk on building a lunar camera digital twin for an actual spacecraft instrument, and a session on Barcelona's underground infrastructure twin, if you want a sense of the range.
Dr. Hipp suggests a definition of "AI" in which SQL planners are AI, defining AI as "any computing system that performs tasks typically associated with human reasoning, problem-solving, and decision-making." (He then explains briefly how SQL planners are runtime code generators. If you're not familiar with how SQL planners work, the keynote is pretty short and worth a watch.)
He then makes a recommendation to developers who are afraid that AI will take their jobs. He points out that SQL planners kinda take away part of the job of a developer, but really just changed the nature of the job.
He makes his point with a slide:
> Q: How can you avoid being replaced by AI?
> A: Solve more problems than you create.
He concludes with a recommendation against having LLMs generate your SQL entirely. He recommends writing it yourself in order to understand it better and engage both the part of your brain that process human language and the part of your brain that processes formal languages like SQL. (He gives an example of trying to ask a coworker for help, but solving the problem by explaining it to the coworker, and how valuable that experience is.)
---
For my part, I'm not sure I agree with calling a SQL planner "AI" in 2026 (I think that obscures more than it reveals), but the advice to solve more problems than you create will always be wise.
Part of the reason I'm dismissive of the current pushback against AI is that people have such a vague definition of it that it starts becoming all inclusive to subsume things like SQL, the Shazam algorithm, etc. Personally, I think it's a good reminder that SQL has quite a bit of intelligence in it. After all, SQL was one of the first mass successes of a declarative based engine.
Put another way, in some abstract sense, one of the differences between SQL query planning and an LLM is one of scale and compute. I wouldn't be surprised that, at some point in the future, we'll see LLM simulation in SQL(ite) akin to how people use different systems to run Doom.
[0] https://en.wikipedia.org/wiki/AI_effect
I think we have to expect the majority of SQL queries will soon be machine generated and machine tuned. The planner in database engines will use LLMs. There will be LLM chats to help you specify what query you want to make, and it will work out which tables etc via question and answer.
Highlight for me: Richard Hipp (SQLite's creator) keynoted the opening session, marking 15 years of Cesium as an open source geospatial project. There's also a talk on building a lunar camera digital twin for an actual spacecraft instrument, and a session on Barcelona's underground infrastructure twin, if you want a sense of the range.
Happy to answer questions about any of it.