Indeed. I lived there for 4-5 years and left right before they started tearing down Fry Street. At that time I could see Bill Callahan at Rubber Gloves for 5 dollars, then head to the square and get my fill. Leave my car and walk home. Wake up and do it again, but instead see The Black Angels in someones house. Saw many great shows at Dan's Silverleaf and saw a number of terrible art exhibitions from the students. I had moved to the east coast by the time they burned down the Flying Tomato and it seemed like a fitting end given what I saw of the place the last time I had visited in early 2007.

I'm very fond of that place at that time. I used to commute straight into the metroplex and back out to Denton. I'd get home and park my car and have most everything a dude in his early 20s needed in walking distance.

I drank a bunch of these PBR owned zombie brands over the last 20 years, Black Label, Schlitz, Old Milwaukee, Lone Star, etc [1] and I've always wondered when I'm drinking one if it's the same flavor as one from previous years or even if the flavor is consistent across regions (assuming PBR was just slapping labels on contracted brewing).

[1] https://www.beeradvocate.com/beer/profile/447/

And this could easily apply to every change we made by hand before AI, it was just a tedious process to layer these things into code when we were just fixing bugs and whatnot. In an AI writes all the code world adding this kind of stuff as table stakes for a changeset is zero cost, effort wise.

This I think is the unexplored aspect of what's happening right now. Guardrails around "good enough" systems is where the future value lies. In the future code will never be as good as when the artisans were writing it, but if you have an automated process to validate/verify mediocre code (and kick it back to AI for refinement when it fails) before it's fully productionized, then you have a pathway to scaling agentic coding.

I'd note here that the long arc of software engineering has been commodifying the discipline into tooling. Ask any unix greybeard how shitty modern abstractions are and they'll give you all you can stomach and yet the wheel turns despite their treasured insights.

What I think will happen is AI will write code and it will do the best it can to mitigate mistakes prior to rollout, but once rollout time occurs, rollout will be incremental and it will self monitor by defining success conditions at rollout time. The nature of the code will mitigate "catastrophe" to a small group at worst, but most likely initial rollout will just run new versions of the code in a simulated context (language design could benefit from this) and analyze potential outcomes without affecting current functionality.

But when the code goes live... it will be slowly scope changes progressively (think feature/experiment flags) and if it fails in the initial cohort, it will redirect. If success is positive, it will increase the rollout cohort.

This is a normal software engineering practice today, but it's labor and process intensive when driven by humans. But in a world where humans are less involved, this process is scalable.

Eventually this will be automated as well. Discipline, rigor and correctness are not strictly human tasks.

I suspect this institutional flexibility is actually a natural consequence of the gendered nature of the role.