whoami4041

6 ms·

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by whoami4041 3mo ago
I've been in the data engineering space for over a decade. As the workload for our team started to scale faster than our staff and context switching thrashed my focus, PRs took a backseat. Releases, pipelines, and reports downstream st
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by whoami4041 3mo ago
Funny story to build on this. I spent a couple of days last week building a Powershell script for database refreshes (backups + restores). The process was iterative (typical), and AI helped me solve all the problems we've ran into hist
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by whoami4041 3mo ago
IMO we have been conditioned to believe that everything is "all or nothing" which is a mistake. AI-assistance provides undeniable leverage IF, and only if, you know what you want. I think the market, in general, is still finding w
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by whoami4041 3mo ago
I actually hold both extremes inside of me simultaneously. The speed at which you can ship when you have a strong vision of the end product and the architecture is extraordinary (the part of me that loves AI-assistance). The journey itself,
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by whoami4041 7mo ago
Shameless plug here for Lexega—a deterministic policy enforcement layer for SQL in CI/CD :) https://lexega.com There are bridges here that the industry has yet to figure out. There is absolutely a place for LLMs in these wo
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by whoami4041 7mo ago
I totally agree. However, none of them are infallible and never will be. They're nondeterministic by nature. There is an interesting psychological nuance that I've noticed even in myself that comes with AI assistance in coding, an
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by whoami4041 7mo ago
The key to my point is in the word "generating". Meaning human input/judgement by actually typing more SQL than the LLM produces. The model's reasoning and code generation pipelines are typically 2 separate code paths, s
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by whoami4041 7mo ago
Very interesting work here, no doubt. It's a measured approach to using an LLM with SQL rather than trying to make it responsible for everything end-to-end.
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by whoami4041 7mo ago
"LLMs are good at SQL" is quite the assertion. My experience with LLM generated SQL in OLTP and OLAP platforms has been a mixed bag. IMO analytics/SQL will always be a space that needs a significant weight of human input and
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by whoami4041 7mo ago
That's a pretty lofty valuation for a company that has yet to demonstrate code generation anywhere near Anthropic's models if they're leaning into the engineering angle.
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by whoami4041 7mo ago
Playground is not mobile friendly. Lexega is a pre-execution analysis and policy enforcement engine for SQL in CI/CD and agent runtimes
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by whoami4041 7mo ago
Lexega is a pre-execution analysis and policy enforcement engine for SQL in CI/CD and agent runtimes
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by whoami4041 7mo ago
Looping back here - trial licenses can now be obtained instantly through the free trial form on the website with just an email. No outreach needed on your part. Here for support if you decide to try it.
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by whoami4041 7mo ago
Would love to help out! Shoot me an email at trial@lexega.com for a 30-day free trial license.
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by whoami4041 7mo ago
I appreciate that! It's a culmination of years of my own pain in the engineering space and a solution anticipating the flood of AI-generated SQL coming for our databases.
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by whoami4041 7mo ago
Yeah, it's one of those things that is hard to catch unless you've been bit by it before and know to look for it. Analytics teams at scale are at a much higher risk of this sneaking in, which is where automatic blocking with Lexeg
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by whoami4041 7mo ago
That's exactly the use case I built agent runtime mode for: AI agents generating SQL need a policy layer between intention and execution. The rules engine is designed to be extensible for precisely that reason and can be enhanced with
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by whoami4041 7mo ago
Great question! sqlfluff catches real things like "= NULL" bugs, implicit cross joins, unused CTEs, and SELECT *. It's a genuinely useful code quality tool. The dialect coverage of sqlfluff is also extensive. Lexega's di
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Lexega Turns SQL into Signals(lexega.com)
21 points by whoami4041 7mo ago|14 comments