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Apple will blow everyone out of the water.

Instagram is dead. In the next 3 - 5 years, every single image in social media will be generated by AI. And here is the kicker: It will be impossible to tell fake from reality. I wrote a few lines of Python code to show you how screwed we are:

AI will not replace you. A person using AI will.

Passive aggressive reminder that US’ tipping culture is out of control.

11 ways ChatGPT saves me hours of work every day, and why you'll never outcompete those who use AI effectively. A list for those who write code: 1 of 16

This is the best laptop in the world. Period. M4, 32 GB RAM, 1TB SSD, 18 hours of battery life, 13 inches, 2.7 lbs. $1,699 with the student discount. No competition.

Scrum is a cancer. I've been writing software for 25 years, and nothing renders a software team useless like Scrum does. Some anecdotes: 1. They tried to convince me that Poker is a planning tool, not a game. 2. If you want to be more efficient, you must add process, not

My new soon-to-be Linux laptop right before I start assembling it.

This is embarrassing. 🍿

“We will not accept money to influence the answers we give you” — Google, 1998.

I just met a person who can't tell Python from C++. He has never written a single line of code in his life, yet he feels he can build anything he wants. He told me point-blank: "I challenge you to tell me something I can't build using AI." I tried to explain, but I couldn't find the right words. The most fascinating aspect of vibe-coding is how it has convinced so many people to believe they are better and more capable than they really are.

Quick reminder: I'm charging $1,000/hour to fix your vibe-coded mess.

I just gave ChatGPT 200+ lines of JavaScript code and asked it to translate the code into Python. The code parses text using regular expressions. It was complex. 2 minutes later and I had Python code that worked flawlessly. This thing just saved me a couple of days of work.

GPT-4 is getting worse over time, not better. Many people have reported noticing a significant degradation in the quality of the model responses, but so far, it was all anecdotal. But now we know. At least one study shows how the June version of GPT-4 is objectively worse than the version released in March on a few tasks. The team evaluated the models using a dataset of 500 problems where the models had to figure out whether a given integer was prime. In March, GPT-4 answered correctly 488 of these questions. In June, it only got 12 correct answers. From 97.6% success rate down to 2.4%! But it gets worse! The team used Chain-of-Thought to help the model reason: "Is 17077 a prime number? Think step by step." Chain-of-Thought is a popular technique that significantly improves answers. Unfortunately, the latest version of GPT-4 did not generate intermediate steps and instead answered incorrectly with a simple "No." Code generation has also gotten worse. The team built a dataset with 50 easy problems from LeetCode and measured how many GPT-4 answers ran without any changes. The March version succeeded in 52% of the problems, but this dropped to a pale 10% using the model from June. Why is this happening? We assume that OpenAI pushes changes continuously, but we don't know how the process works and how they evaluate whether the models are improving or regressing. Rumors suggest they are using several smaller and specialized GPT-4 models that act similarly to a large model but are less expensive to run. When a user asks a question, the system decides which model to send the query to. Cheaper and faster, but could this new approach be the problem behind the degradation in quality? In my opinion, this is a red flag for anyone building applications that rely on GPT-4. Having the behavior of an LLM change over time is not acceptable. Have you noticed any issues when using GPT-4 and ChatGPT lately? Do you think these problems are overblown?

My European friends (software engineers) make a fraction of what my American friends make. The disparity in salary is huge (as high as 2x, 3x, and even 4x.) And if you think that “hEalTh inSuRanCe aNd pAid lEaVe” makes up for this, you are just coping.

Apple will blow everyone out of the water.

Instagram is dead. In the next 3 - 5 years, every single image in social media will be generated by AI. And here is the kicker: It will be impossible to tell fake from reality. I wrote a few lines of Python code to show you how screwed we are:

Scrum is a cancer. I've been writing software for 25 years, and nothing renders a software team useless like Scrum does. Some anecdotes: 1. They tried to convince me that Poker is a planning tool, not a game. 2. If you want to be more efficient, you must add process, not

This is the best laptop in the world. Period. M4, 32 GB RAM, 1TB SSD, 18 hours of battery life, 13 inches, 2.7 lbs. $1,699 with the student discount. No competition.

I just met a person who can't tell Python from C++. He has never written a single line of code in his life, yet he feels he can build anything he wants. He told me point-blank: "I challenge you to tell me something I can't build using AI." I tried to explain, but I couldn't find the right words. The most fascinating aspect of vibe-coding is how it has convinced so many people to believe they are better and more capable than they really are.

Passive aggressive reminder that US’ tipping culture is out of control.

My European friends (software engineers) make a fraction of what my American friends make. The disparity in salary is huge (as high as 2x, 3x, and even 4x.) And if you think that “hEalTh inSuRanCe aNd pAid lEaVe” makes up for this, you are just coping.

I fired somebody cheating. He was working two jobs. The guy had a great interview with me. He was sharp, and I was happy to hire him. Two weeks later, I started noticing the red flags. He joined our meetings but never turned his camera on. He would always ask to repeat the

I was talking to a guy who vibe-coded a saas, trying to explain to him what a huge mess the code is. I thought I had him. He looked at me completely confused. “So?” He said. That’s when it hit me: Vibe-coders don’t give a shit about code. They don’t understand it, they don’t touch it, they will never have to deal with it. They care about bringing their ideas to life and nothing else. They are 100% unburden by what many of us consider a showstopper. There’s an important lesson here.

I have many friends in the U.S. and Europe. We all work in tech. High-paying jobs. All of my US friends can afford a vacation in Europe once a year. No sweat. None of my European friends can. Doing it once is a stretch. Once per year is out of the question. Anecdotical

If you aren't using GitHub Copilot to write code, can you tell me why?

I'm officially done reading AI-generated code. It's been two weeks since I looked at any of it. I think the IDE is officially on its way to the graveyard. The job is no longer about "writing code," so we need new tools that better reflect this new reality. While reviewing the code, I realized my only complaints were stylistic, and I wasn't finding any obvious bugs anymore. The more code I generated, the harder it became to keep track of every line. I found that my time is better spent designing ways to verify that the overall system works than looking at the code. State-of-the-art coding agents are better at writing code than I'd ever be, and I'm going to stop pretending otherwise. I still think these coding agents can't go too far without an experienced human guiding them, but we're past the point where we need to check every line of code.

GPT-4 is getting worse over time, not better. Many people have reported noticing a significant degradation in the quality of the model responses, but so far, it was all anecdotal. But now we know. At least one study shows how the June version of GPT-4 is objectively worse than the version released in March on a few tasks. The team evaluated the models using a dataset of 500 problems where the models had to figure out whether a given integer was prime. In March, GPT-4 answered correctly 488 of these questions. In June, it only got 12 correct answers. From 97.6% success rate down to 2.4%! But it gets worse! The team used Chain-of-Thought to help the model reason: "Is 17077 a prime number? Think step by step." Chain-of-Thought is a popular technique that significantly improves answers. Unfortunately, the latest version of GPT-4 did not generate intermediate steps and instead answered incorrectly with a simple "No." Code generation has also gotten worse. The team built a dataset with 50 easy problems from LeetCode and measured how many GPT-4 answers ran without any changes. The March version succeeded in 52% of the problems, but this dropped to a pale 10% using the model from June. Why is this happening? We assume that OpenAI pushes changes continuously, but we don't know how the process works and how they evaluate whether the models are improving or regressing. Rumors suggest they are using several smaller and specialized GPT-4 models that act similarly to a large model but are less expensive to run. When a user asks a question, the system decides which model to send the query to. Cheaper and faster, but could this new approach be the problem behind the degradation in quality? In my opinion, this is a red flag for anyone building applications that rely on GPT-4. Having the behavior of an LLM change over time is not acceptable. Have you noticed any issues when using GPT-4 and ChatGPT lately? Do you think these problems are overblown?

AI will not replace you. A person using AI will.

It's crazy to me how nobody knows how to build a laptop that matches the quality of an Apple MacBook Pro. Everything I've seen is a downgrade hardware-wise.