This entire post about when and how to slow down in the age of AI by James Stanier is full of great stuff, including this:

If the decisions that precede execution are flawed, AI will faithfully implement those flaws in a way that looks like fully featured code. Looks can often be deceiving, especially with powerful and confident models. It will generate thousands of lines of code based on a misunderstood requirement. It will happily build an elegant solution to the wrong problem.

The illusion of speed is that you’re making progress when you’re actually digging yourself into a deeper hole.

The answer isn’t to abandon speed, but to deploy it deliberately. We should only unleash AI’s pace when we’re confident it’s pointed in the right direction.

And this:

Given that AI is speeding things up so much, if you haven’t already been challenged on why something’s taking so long, you certainly will be soon.

“Can’t you just use AI?” is a new form of velocity pressure, and it’s particularly insidious because it conflates the appearance of productivity with actual throughput. Yes, AI can generate code in seconds. But generating code and solving the right problem are not the same thing.

An astute observation from M.G. Siegler on AI’s notable lack of taste, especially with something as complex as personal travel preferences:

From here we quickly enter a maze of a hundred little preferences that are altered by thousands of real-world variables. If the powers that be thought the game of Go was a good, complex task to prove out AI, wait until it gets a load of trying to book travel for a family with children.

For all these stories about AI creating 500,000 lines of code and 90% of an app in 10 minutes, where are the follow up posts about the meaningful, measurable outcomes it created?

Like what actual business problem was solved? How well did it integrate with your existing product and strategy? How many new paying customers did you land because of it? What profit did it generate? What was the customer support experience for it like? Did customers actually like it? Did customers actually use it? How did it materially impact your business or revenue? How maintainable was the code base over time? 🦗

This is the tech bro bullshit worldview we’re up against. Unreal.

Was using Claude Code and it got confused as to when to use curly quotes in code (eg, literally never) and it broke a bunch of stuff. Maybe the AI hype bros can chill a bit with the “I BUILT THIS APP IN 15 MINUTES TO 90% DONE” stories?

I know it’s not serious but I’m still proud of my 0%.

Some of the smartest, most thoughtful people I know in tech are extremely skeptical of AI. That is, as they say in our business, a smell.

These aren’t the loud, bombastic, attention seeking jerks you see everywhere on socials. They’re just good folks who have proven time and time again to have strong ethics, thoughtful judgement, deep expertise, a strong sense of community, and a kindness toward humans. I’ve seen them build up open source communities and people alike.

So when the people you respect the most are deeply skeptical of something, that’s worth sitting with. Especially when the subject matter is something that has a non-zero chance of imploding.

We literally can’t go a week without a mass layoff, this time by Epic. I’m getting real fucking tired of asking old colleagues and friends “Hey, saw the news about the layoffs, you OK?”

At the risk of sounding corny, as a grizzled (but experienced) old dude, I can tell you with great confidence that your values – what you believe way down deep – is the best thing to help you navigate your career choices. Over the long run it’s what’ll make you successful.

Definitions of success may vary wildly and it’s easier said than done, but if you can consistently align your values with your work, you’re already mostly there.

There are people in 2026 talking about how many lines of code they shipped with a straight face. Well, I think they’re people at least. 😑

Just read an AI hype post saying their vibe coding got them 90% complete on a project. Woo hoo! The “only” things they had to engage an engineer to finish off: authentication, API keys lockdown, VPN protection, and a full security audit.

Funny how all these over the top “AI is changing everything!” posts are largely from people running AI startups. Totally not suspicious at all and very believable.

Still mulling over the Block layoffs, and one thing that caught my eye was how many folks who were let go were there for easily 6, 8, even 10 years or more. People who gave literally a decade of their life, jettisoned in an instant.

In addition to the cruelty of it, there’s is NO WAY that you lose that much institutional knowledge and keep rolling along anywhere close to full operational efficiency, maybe not even 50%. There is a 0.0% chance that your fancy AI tools have that kind of context. And they certainly don’t have the collective centuries of technical, product, or design judgement of those people.

Such a failure of leadership and management at every level.

Then I took that context map - I have never written a line of Terraform in my life - and spent 40 minutes with an Al to generate roughly 80% of the correct answer.

This is the state of the AI brain worming that’s happening right now. Guess we shouldn’t be shocked that mindless AI slop code would result in a mindless AI slop post about it, too.

I’m well past just muting folks with AI slop takes (“3 engineers can outperform 8 with just AI, here’s how!”). Full blast ridiculing and blocking now. ✌️

Emily Gorcenski on Bluesky:

“But guess what—they all require you to still be a good software developer. Engineering has always been about tradeoffs and judgment and I have seen nothing that indicates that this will change.”

“You hear all these stories of people vibe coding a SaaS alternative in a weekend. That’s great for N_users=1. That’s not the hard part.”

This, this, this, this. 💯

Meta (META.O), opens new tab is planning sweeping layoffs ​that could affect 20% or more of the company, three sources familiar with the matter told Reuters, as ‌Meta seeks to offset costly artificial intelligence infrastructure bets and prepare for greater efficiency brought about by AI-assisted workers.

For the heartless tech bro I saw write “I’m not mad about the [Block] layoffs” who works in Meta’s AI group, may I introduce you to my friend karma?

You Can’t Prompt Your Way to Judgment by Dr. Claire Knight is full of thoughtful nuggets on AI, like these:

But most of the software world isn’t Stripe. Some companies still have six-month release cycles. Some are still in the middle of their cloud migration. Panic-adopting AI in those environments doesn’t produce 4x productivity. It produces faster slop.

AI amplifies your existing engineering culture.

Experience debt is what accumulates when you’ve never been through a catastrophic release, never owned a 3am system failure, never made an architectural decision that seemed brilliant and then cost you eighteen months of pain to undo. It’s the absence of pattern recognition that only comes from proximity to failure."

Knowing what to enforce, what to leave flexible, what will break under load and what won’t. You cannot build that from a standing start. It accumulates through years of getting it wrong."

John Miller on LinkedIn writes:

You can run 20 parallel codex threads. You can orchestrate 15 agents. You can have them all working together.

Okay.

But are you actually serving your customer better? Or are you serving your feed, your boss, your board… or your ego?

A productivity story is not a product strategy. I think we’re missing the plot here.

Customers don’t care how impressive your internal workflow is. They pay for the value you’re building for them.

Nailed it.

Kind of hilarious to see a company make a big deal about how rigorous they are about hiring, but also have the same role open for literally a year in a market flooded with candidates. That’s not rigor, that’s just being bad at hiring.

This conversation on AI with Anil Dash is so good. I don’t know how anyone could argue with what he’s saying — measured, realistic, and well reasoned throughout. Y’all need to give it a listen.

This post by Naoko Takeda on their experience with the Block layoff (not being laid off but leaving anyway) is hardcore. I cannot express how much respect I have for people who have a strong ethical compass and act decisively. 👏

If there were a Mismanagement Hall of Fame, Jack Dorsey would be a first ballot inductee.

Instant block for anyone who even remotely attempts to piggyback on the Square/Cash App layoffs to advertise their product. Absolute vultures. 🚮