There is a world of difference of having tens of millions of dollars and paying hundreds of dollars a month for AI subscriptions vs someone making 100k / year doing the same.

For the DHH's of the world that's not even something to think about, but for most people who are working (even in tech), now we're talking 2-8%+ of your income depending how much you use AI. Just to have the "luxury" of being able to experiment with it. I use air quotes on luxury because I personally find a lot of AI results to be quite bad, but then again, I'm not spending hundreds of dollars a month on the premium models.

Here is the description for the Rails World 2026 Opening Keynote:

"Opening Keynote highlighting what's new in Rails, what's coming next, and where Rails is headed in the future."

DHH literally did not cover that. Not even close!

The first response in the conference chat described it as the "worst opening keynote possible to setup the Rails World conference." While someone soon disagreed with that, another guy later said he felt it undermined the later talks, and someone else said the Laracon conference had more about what the framework is doing in the AI age. He barely mentioned Rails. I get how he was excited about his experiments but I certainly wish he had focused more on what Rails is doing for this new era.

The fact that you get so much out of the box that just works and you don’t have to do much beyond configure it reduces a ton of headaches.

Absolutely would rather be using Go instead of Ruby but for apps of a certain kind and size, the omakase approach of Rails still wins out.

I mean I haven’t touched Ruby in years but if you’ve got tokens to burn, who cares? Compute is pretty cheap these days and Ruby is usually fast enough for web stuff, and as far as I can tell 2nd hand the robots write it just fine.

And I say this as someone building a strongly typed programming language that compiles to native code.

Those who travelled to a soon to be dead web frameworks conference might appreciate the heads up.

Those who refuse to accept or believe it might be salty.

Is the idea that they'll switch to doing "product owner" roles overseeing agents? I don't see that employing the same number of people or paying as well as engineering used to.

To be honest I expect that that role to suit different people to those that used to be engineers.

If this feels gloomy to some people, it's because it is.

- A layperson can now build one a solo developer can do

- A solo dev can now build what an agency of web development can do

- An agency of web development can now build native apps similar to what large corporation can do

- Large corporation can now tackle even more ambitious projects

Which makes sense given what got automated. This is with the current tech, people still exploring the full potential, but if that turns out to be the case then I'd argue the software market will grow substantially and we are just having an adjustment period.

He explicitly said he still loves ruby as a language and thinks Rails is well suited for a future with AI coding.

It's interesting how this stuff gets spun on social media by people who don't watch the content.

That sounds like layoffs lol.

I have a hard time believing that, considering his hobby of racing cars and commissioning one-off hypercars. Unless it's that his business could never afford that dev team after DHH takes his salary.

Any specific examples? I am/was out of the loop on this and had to Google "DHH politics" to know what people are talking about.

The one for me is spotting the Baader-Meinhof effect, of which this is an unfortunately strong example.

I'm always pleased when working with a dev who has Rails experience even if they've since moved stack, as often they have picked up and learned the value of these good behaviours. Perhaps it's as much a community thing as a framework thing, or combination of both.

Agentic development definitely still has room to improve, but I suspect that there is some future framework (maybe even language) designed to help minimise these types of mistakes.

When designing systems, you want the important details to be right. Especially with authentication and authorization.

From an architecture level, you can know which classes are important to review and which ones are not.

There's a difference between everything being vibe-coded where you don't look at the code and don't understand anything and using your agent like a very fast pair programmer.

It looks like Antirez did the latter. From https://antirez.com/news/164:

> In the first month I just wrote the specification document...Thanks to AI, the specification evolved a lot, via back and forth of feedback, intellectual challenges about what was the best design, what was the right compromise, what was too engineered and what not.

> You know what was the biggest realization of all that? For high quality system programming tasks you have to still be fully involved

Judgement will be required even moreso now. There will be critical parts of the system where it's important that engineers know them well. But there's a lot of work around the core that isn't that critical to know in detail. For these types of things, I've found it's just important to understand the gist to make sure things aren't going off the rails. But for the core pieces, it's important to understand the details of what's happening.

I agree that we have to keep understanding our code and we have to understand the systems we build.

I think the deeper issue is that AI can generate so much code that reading it simply doesn't scale.

Even if AI were to produce perfectly written code that didn't have any bugs that human review needed to catch, it would still be too much code to read in order to understand everything. The machine can write much faster than I can read.

Extending this argument further, it also becomes impossible to onboard young people to codebases if we maintain an expectation that reading all the lower level source code is how they come up to speed. I don't think this was ever an actual expectation in the industry, although we may have short-handed it that way in conversation.

So IMHO we need to come up with higher level visualizations and other ways to compress the knowledge that we used to get out of reading source code. We basically need to create new higher level projections off of our semantic understanding of the project.

That said, I think this only applies to apps that can be replaced by vibe coded garbage. Anything with a network effect, or anything that requires deep domain knowledge is much safer

Are you changing your own oil? The cost of oil alone usually ends up being around 3 DIY changes vs one at the dealer ship. The mobile 1 synthetic I like is currently $92 for a 3-pack of 5qt containers. Which is enough for 3 oil changes with some left over to almost do a 4th. Dealership currently wants $84+tax for change w/free tire rotation. It's cheaper but certainly not "do it forever", and living in an apartment often means risking getting a warning from the landlord for doing auto maintenance in the parking lot since its against the stated rules in the lease.

Drain plug is in a stupid location that I don't often feel like dealing with. I do change the oil myself in all my other machines with much more pleasant for oil change designs, though. So I guess what you are saying is that AI isn't ergonomic enough yet, but will that hold true much longer?

As of now, but we are talking in a perspective.

Yeah, I'm sure you are doing ~4 years worth of work per day. Get real Jesus Christ.