Absolute madness. Why would anyone pay any premium for a BMW from now on when they become the product with force pushed ads after dropping $50K+ (or more) on a new car Suddenly any car looks more tempting than BMW. It will be hard to recover from this. Who greenlit this?

I have trouble reconciling how 1) Spotify used to have a very strong eng culture, huge on quality. 2) Their products are extremely buggy, unreliable, and getting worse esp this year. It got so bad I had to offboard from their video podcasts product, just did not work. Here:

Kent Beck is such a good reminder that it takes genuine humility + that desire to learn (even thru grunt work) and get better every day to become a standout professional I don’t think AI changes this fwiw

Amusing observation: Many of us devs are becoming as opinionated and knowledgeable about SOTA models (and their coding performance) like we used to be about programming languages and the tips-and-tricks to be more productive with them Meanwhile we don't really talk about programming languages all that much...

Customs work: they disincentive buying anything from outside the customs area, or sending from outside. Bought something online that was shipped from outside the EU. Went away for ~2 weeks, and now my stuff is returned because I did not pay customs (notif came over snail mail)

The industry’s progress on agentic capabilities is pretty incredible, esp the last few months. Cloud coding agents are starting to become more common and capable, and local ones are already v powerful. What do they not see at Meta that eg I do?

I’m starting to realize just how important it is to understand context sizes, context rot, context compression & similar behaviors to understand why these models often fall short Eg why it is that you give it a large block of stuff and the model “forgets” about parts of it etc

Yes this is all happening. But to put a positive spin on all of this: There Will Be More Cleanup Work and Guess Who Will Do It? (No, AI will not do this kind of cleanup - though there will be startups promising their AI will do this but they won’t do it as well as xp’d devs)

I talked with a few folks inside Anthropic and I am starting to understand what @karpathy is saying (and what lots of people are misunderstanding) It's not about Slack, but about a cloud AI, hooked up to ALL internal company systems, that "just works." THIS is the breakthrough

Google has already removed my original article from its search index. The one that I am the only copyright holder of! So I wrote a new one lol . Will the anonymous entity (who I cannot tell who is!) try to remove this as well? And does Google let this?

WTH Pollen (the events tech company that did not pay salaries of staff for months, founded by Callum Negus-Fancey) is filing a copyright claim to remove this article from Google: Go to hell. This my article, and there's zero copyright claim to be made on it

Talked with a few folks inside of AI labs (OpenAI, Anthropic) about what they think of the future of software engineering. The “closer” to shipping production code engineers are, the less they believe software engineering will be “solved” fully by AI. The opposite true as well

Why is the creator of OpenCode pretty skeptical about AI productivity gains, and the hype around AI? A very conversation @thdxr (and lots of truth bombs:) Timestamps: 00:00 Intro 07:03 Dax’s path into tech 09:04 Early startup experience 13:16 Getting involved with open source 16:13 OpenCode 23:17 Anthropic banning OpenCode 30:34 From terminal to GUI 32:34 OpenCode’s business model 36:33 Why inference is profitable 39:11 GPU bottlenecks 40:54 AI hype 45:50 AI spending 48:47 Dax’s memo 55:41 Dax’s skepticism of predictions 58:58 Engineering culture at OpenCode 1:02:38 How building works at OpenCode 1:05:36 Taste and quality 1:11:32 Dax’s work setup 1:12:35 The role of engineers and EMs 1:15:50 Advice for engineers 1:18:12 Book recommendation Brought to you by: • @AntithesisHQ – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages • @WorkOS – everything you need to make your app enterprise ready • @turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable Three interesting thoughts from Dax: 1. No AI-native coding agent company is “winning” by being better with AI. Dax says that none of OpenCode’s competitors are crushing them, and that nobody is using AI so well that others cannot compete. 2. Most software engineers profit from AI as time gained, not increased output — unless you change incentives! Dax says the natural way for software engineers to “cash out” their AI tooling gains is with time savings, by doing the same work as before, but faster. Until compensation and motivation structures change, most teams should expect output to stay flat while engineers go home earlier. There’s nothing wrong with this, but AI vendors sell a different outcome to CFOs: increased output. 3. AI code generation mutes the “guilt” of doing the wrong thing, but this builds up tech debt. Pre-AI, writing a hack felt bad, the second time it felt really bad, and by the third time you’d often just refactor in order to fix up the code. Now, the agent hides the hack, which skews devs’ judgment and results in less tech debt being cleaned up.

Kind of amusing that my almost exactly 1-year-old interview with Shopify's Head of Engineering @fnthawar is presented as the most cutting-edge content you can watch today. Tells you how some companies are just so ahead of the game - the indusry takes months/years to catch up!

I got a notification that some pages on one of my side projects is no longer indexed by Google b/c of some issue. It’s the first time I decided: “nah, won’t fix it.” Because “appearing on Google” is increasingly irrelevant as Google becomes an AI aggregator, hiding pages anyway

Starting to REALLY see how reaching potential customers is becoming a massive pain point for software startups - esp w AI! I get so much more messages about software that founders built rapidly that they think will solve some important problem (usually eg AI+context/trust/security). But how will anyone know about it? It was fast to build, but getting the world to know about it / care about it is increasingly hard/expensive/time-consuming. And the irony is: the "easier" it is to build, the more the only differentiation is marketing/advertising! (Because the easier it is to build, the more teams build something similar in parallel, and racing to win the market becomes key!)