481
A bubble that knows it's a bubble
Railway Mania, dot-com, AI. Technology bubbles follow a pattern older than any of them. What's different this time is that everyone knows the script.
New
The latest blog posts to take off on Hacker News. 1,227 posts.
482
Making games in Go: 3 months without LLMs vs. 3 days with LLMs
After 15 years as a software engineer, I realized I had never actually built and published a game.
483
Writing with LLM is not a shame
Do we have to disclaim how we use AI ?
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DeepWiki: Understand Any Codebase
How I use DeepWiki to speed up real coding work
486
How to build a coding agent
It's not that hard to build a coding agent. 300 lines of code running in a loop with LLM tokens. You just keep throwing tokens at the loop, and then you've got yourself an agent.
487
Evaluating LLMs for my personal use case
My life is not a math Olympiad
488
AGI is an engineering problem, not a model training problem
LLM models are plateauing, but true AGI isn't about scaling the next breakthrough model—it's about engineering the right context, memory, and workflow systems. AGI is fundamentally a systems engineering problem, not a model training problem.
489
What makes Claude Code so damn good
Claude Code is the most delightful AI agent/workflow I have used so far. Not only does it make targeted edits or vibe coding throwaway tools less annoying, ...
490
Writing Speed-of-Light Flash Attention for 5090 in CUDA C++
In this post, I will walk through how I learned to implement Flash Attention for 5090 in CUDA C++. The main objective is to learn writing attention in CUDA C++, since many features are not available in Triton, such as MXFP8 / NVFP4 MMA for sm120. I also feel this is a natural next step after learning about matmul…
491
My experience creating software with LLM coding agents – Part 2 (Tips)
moved to https://blog.efitz.net/posts/my-experience-creating-software-with-llm-coding-agents-part-2-tips/
492
Sprinkling self-doubt on ChatGPT
I replaced my ChatGPT personalization settings with this prompt a few weeks ago and promptly forgot about it: Be extraordinarily skeptical of your own…
493
A guide to Gen AI / LLM vibecoding for expert programmers
I get it, you’re too good to vibe code. You’re a senior developer who has been doing this for 20 years and knows the system like the back of your hand. Or maybe you’re the star individual contributor who is the only person who can ever figure out how to solve the hard problems. Or maybe you’re the professor who…
494
Being “Confidently Wrong” is holding AI back
The failure mode that stalls “AI for data” efforts or "AI on my APIs" efforts isn’t psychedelic hallucination—it’s confident inaccuracy: plausible answers that are wrong in subtle and costly ways.
495
In the long run, LLMs make us dumber
The comfort we get when offloading our cognitive load to LLMs is bad for us. Cognitive load should exist, and if we reduce it too much – if we stop thinking – we can actually unlearn how to think. Kids who always choose the easy route and copy their homework from other students eventually find […]
496
Building AI products in the probabilistic era
AI turns products from deterministic functions into probabilistic systems. That requires expanding old playbooks (SLOs, funnels, siloed finance), and reasoning in terms of trajectories, Minimum Viable Intelligence thresholds, and data as company operating system.
497
The unbearable slowness of AI coding
I’ve been coding entirely with Claude Code for the past two months. At first it was exhilarating. I was speeding through tasks. I was committing like mad.
498
Unmasking the Privacy Risks of Apple Intelligence
We reveal AppleStorm, our investigation into how Apple AI’s eco-system quietly transmits messages (WhatsApp, iMessage) sent via Siri to Apple servers, even when it isn’t needed to complete the task.
499
Measuring the environmental impact of AI inference
A methodology for measuring the energy, emissions, and water impact of Gemini prompts shines a light on the environmental impact of AI inference.
500
Weaponizing image scaling against production AI systems
In this blog post, we’ll detail how attackers can exploit image scaling on Gemini CLI, Vertex AI Studio, Gemini’s web and API interfaces, Google Assistant, Genspark, and other production AI systems. We’ll also explain how to mitigate and defend against these attacks, and we’ll introduce Anamorpher, our open-source…
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Vibe coding creates a bus factor of zero
"AI first" leaves humans nowhere. Learn about the Bus Factor and how the launch of ChatGPT has changed the landscape on knowledge sharing.
502
How to Think About GPUs
We love TPUs at Google, but GPUs are great too. This chapter takes a deep dive into the world of GPUs – how each chip works, how they're networked together, and what that means for LLMs, especially compared to TPUs. While there are a multitude of GPU architectures from NVIDIA, AMD, Intel, and others, here we will…
503
The lottery ticket hypothesis: why neural networks work
The lottery ticket hypothesis explains why massive neural networks succeed despite centuries of theory predicting they should fail
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Who Invented Backpropagation?
Its modern version (the reverse mode of automatic differentiation) was first published in 1970 by Seppo Linnainmaa
505
LLMs and coding agents are a security nightmare
Things are about to get wild
506
MCP doesn't need tools, it needs code
Exploration into providing MCPs with the most powerful of all tools: code.
507
When did AI take over Hacker News?
One in three top 10 Hacker News posts in August 2025 were AI-related. Can we pinpoint when this trend started?
508
AI doesn't lighten the burden of mastery
<no value>
509
Who does your assistant serve?
ChatGPT and its consequences have been a disaster for the human race.
510
Derivatives, Gradients, Jacobians and Hessians
This article explains how these four things fit together and shows some examples of what they are used for. Derivatives Derivatives are the most fundamental concept in calculus. If you have a funct…