lol. wish it was. fwiw i was pretty much bearish on AI for years because I did go deep into this shit since i got access to GPT 3. but since astra i have been quite bullish.
98% of people think AI means what gemini tells them when they do a google search.
of that 2% who go beyond... maybe 20% of those are using AI to code.
most SWE still think "using AI" to code means the copilot pane they open on the side in VSC. they get sloppy code output and think "ai sucks!"
so of that 20%, maybe 5% have actually explored what an "agentic" workflow even means. they might use skills, set up their code base so AI almost NEVER makes a mistake. maybe 1-5% of that 5% actually went deeper, and those are the people who built tools like Cursor or Harvey or whatever other "agentic" companies.
you are still thinking about the old world where you obsess and define data models and bike shed over data integrity, all the while you have a "temporary" table with 3 attributes that gets 2 million queries per second that's now holding up a bunch of other shit that's also glued together.
> I could not think of a worse technology to use for an ETL pipeline than throwing LLMs at it and asking it to vibe out the correctness of the data every time it runs.
like i said, if you are still having quality issues in 2026, that's a skill gap.
also, agents now continually improve the process.
for a business, the only thing that matters is transaction log. for 99% of businesses, swe are a cost.
again this is like baby steps on the journey. we are still only 3 years into this technology being opened up to masses.
i'm sure people thought computers were dumb, or that cars are stupid because the first cars were moving slow af. "we have horses, why do we need to build out roads to get anywhere"
but you're free to feel smart doing 20/20 hindsight on things 100+ years from the future