Throwback to when we first started vibe coding

everyone all up in here about agents writing code when there are bigger wins "qa it"

a quick recording of how I approach dealing with layout shifts

Very few AI products have true product market fit If you look at your usage or talk to your friends, you'll see that there are only a couple of AI products actually being used It's confusing because you see all these crazy revenue numbers and rounds that are being raised and you assume that these products must be blowing up This is happening because we are in a very unusual period where consumers and businesses are very motivated to try anything AI related, and that includes enterprises signing contracts for them But people are just trying these products out, if these don't stick then their users and customers will just churn It's also hard to stay relevant when you are still trying to find product market fit, there's so much noise and an onslaught of new companies entering your space You can see companies struggling to deal with this, they are under constant pressure to launch new features or products Which unfortunately just makes the problem worse because you are likely to ship more slop just to keep up with the market, compounding the problem of a lack of product market fit

Elder Gong COOKED with this one.

This is literally the prompt I use, it's not fancy: /goal Reduce memory by at least 1% on {repo} without (1) changing our build configuration or allocators, (2) reducing runtime performance (unless the tradeoff is clearly favorable, i.e, 2% memory for a smaller performance hit). The existing optimizations in branches like charlie/consolidate-ast-id-map or charlie/intern or are not valid candidates. Avoid spending lots of time running release benchmarks to measure runtime performance. Just try to keep performance in mind. If you theorize that a chance should be performance neutral, and that it reduces memory to meet the goal, then we'll open a draft PR to run benchmarks in CI.

Phones, watches, doorbells, cars, factories and energy grids are increasingly becoming connected, all collecting and communicating information to be interpreted, analyzed and acted upon. Noting this trend, Elder Gerrit W. Gong (@GerritWGong)  of the Quorum of the Twelve Apostles will discuss how to safely navigate artificial intelligence in a 60-minute gospel workshop video titled “Faith, Dignity and Human Flourishing: Hearing God’s Voice in an Age of Artificial Intelligence,” available on Sunday, June 7, 2026. Learn more on Church Newsroom. newsroom.churchofjesuschrist…

If you want to know what giveaway LLM design is, this is it: thin colored borders, gradients, glow effects, too many different font sizes, small fonts too small, inconsistent padding and alignment (especially vertical). Not a dunk on @zeeg he’s being transparent about it. And he’s a good AI driver and good developer in general. But using this moment to show people how obvious this is.

Deploying a Hermes Agent with Fly, Modal, OpenRouter, & Cloudflare 02:43 Managed vs VPS 06:08 Architecture 15:14 Setup 22:23 Deployment 28:00 Access / OIDC 39:57 Hermes and Open WebUI 52:07 Cloudflare 01:01:35 Validation 01:07:32 Recap Awesome tool - s/o @NousResearch !

here's my pi session for those asking how i get to this point pi.dev/session/#5ddc8747b98a…

Submitting an order for several more Rust-based JS package managers

there's no catch; SAM3 is open source and really good one of the things it does really well is object tracking, even in crazy complex scenes like basketball probably my favorite computer vision model ever

x.com/i/status/1996001582211… - ofc

I've been coding for 40 years. Here are the top 5 things I wish I knew when I started. 1. 90% of the job is debugging and fixing, not creating new code. Which is still fun if you're good at it. I used to think programming was mostly writing fresh, clever stuff. In reality, most of your time is spent in other people's (or your own past self's) messy code, chasing down why something that "should" work doesn't. Get really good at debugging early. Learn assembly reading, call stacks, and kernel debuggers. It pays off hugely. The best engineers I saw were absolute magicians at this. 2. Manage complexity from day one (ie: don't write slop and "fix it later" if it goes somewhere). Very early on, I'd hammer out code and refactor afterward. Big mistake. Now I start with clean, skeletal structure (minimalism first) and flesh it out carefully, with AI or not. Messy code compounds and becomes unfixable. Upfront discipline on architecture, naming, and simplicity saves enormous pain later, especially in large systems like Windows. 3. Tools and processes matter more than you think We suffered with basic diff/manual deltas instead of modern source control like Git. Branching, testing, and good tooling would have made porting and collaboration way smoother. Invest in your environment, automation, and reproducible builds early. Good tools amplify your output; bad ones (or none) drag everything down. 4. Understand the problem and existing code deeply before writing Don't jump straight to coding. Map out the problem, study what's already there (you'll inherit a lot), and plan. Low-level knowledge (hardware quirks, alignment issues on different architectures like MIPS/Alpha) was crucial. Also: assert early and often. It forces clarity. 5. People, politics, and "the right tool for the job" beat pure tech arguments. Brilliant engineers still argue endlessly. Sometimes it's about ego, not merit. Learn to spot the difference and "steer" the conversation rather than "winning" it. Bonus from experience: Side projects like Task Manager (started at home because I wanted the tool) can become your biggest hits. Ship small, useful things often. If you're just starting, focus on fundamentals, patterns over syntax, and building resilience for the long haul. It's going to be a wild ride, but the fundamentals still matter.

More and more people are asking me about testing resources so let's put everything I've written in one post. Bookmark, share, and, most importantly, please read these. The True Purpose of Testing epicweb.dev/the-true-purpose… Developers often overlook the fundamentals and rush into writing tests without properly understanding what a test is and what is its function. No test is inherently useful just because it exists. Read this one to learn what makes it useful. The Golden Rule of Assertions epicweb.dev/the-golden-rule-… There's a lot of debate over what makes a good test. In this one, I'm defining a short and objective way to grade a test's quality no matter the language or the tested system. This is, without a tinge of exaggeration, a game-changer in how you approach your tests. Anatomy of a Test epicweb.dev/anatomy-of-a-tes… Let's talk about the building blocks that make up any automated test. From JavaScript to Go and Rust—these blocks power tests everywhere. Know your blocks. Implicit Assertions epicweb.dev/implicit-asserti… Did you know there's a way to express expectations in tests without writing "expect"? Those are called implicit assertions and they are tremendously powerful because they help you express more by writing less. Inverse Assertions epicweb.dev/inverse-assertio… Sometimes you need to assert that something did not happen. That can be tricky, especially if that something is asynchronous. The last thing you want are false positives. What you actually want is inverse assertions. Making Use of Code Coverage epicweb.dev/making-use-of-co… Code coverage has been an ongoing debate in the engineering circles. Is 100% code coverage in tests good? Bad? When should you strive for it? Why do people say it's harmful? I'm answering all those questions in this one and giving you practical tips on when to use (and not to use) code coverage. Good Code, Testable Code. epicweb.dev/good-code-testab… You've gathered by now that some code is easier to test than the other. But why? Let's take a look at the characteristic of code's testability, what defines it, what is its relationship with complexity, and how to make your code more testable. What is a Test Boundary? epicweb.dev/what-is-a-test-b… Automated tests rarely involve your entire system (yes, even the end-to-end ones have exceptions). There's often a place where you draw the line. The boundary. Learn what it is and how to use test boundaries efficiently to focus on the exact behaviors you want to test. Be S.M.A.R.T. About Flaky Tests epicweb.dev/be-smart-about-f… Flakiness is the scourge of reliability. If you've written a test before, you likely had experience with flakiness. But what is it at its core and what causes it? And how should you deal with flakiness? Writing Tests That Fail epicweb.dev/writing-tests-th… You write tests for them to fail. We all enjoy a green CI, but the true value of tests is when they fail. What matters is when and how they fail.

There has been no greater blessing in my life and no greater purpose driver than being a father 10 out of 10 would recommend

pnpm supercut "by the way" --bucket @ThePrimeagen --tile --limit 150

My sitemogging website was on the front page of Hackernews for a while last Friday... Of course it was built on Cloudflare. How much do you think it cost me to run thousands of Workers AI Browser Run sessions?!

"Agents can now create Cloudflare accounts, buy domains, and deploy" Here's how it works in 4 minutes.