Gusarich's thoughts

What LLM to use today? Many major releases occurred in the past weeks. The current frontier consists of models that a couple of months ago were only rumors. And they are great. OpenAI has GPT-5.1 and GPT-5.1-Codex-Max; Anthropic has Opus 4.5; Google has…

Things got too easy with AI AI provides incredible value to me and to many other people in our daily lives and work. It's now possible to do more, better, and faster than ever. But I realized that the progression of AI capabilities outpaced the progression of my goals. I recently started thinking in retrospect about what I was doing and what I was thinking about in the past months, and it feels like I didn't really face any hard challenges in many months. I can't remember the last time I was …

I gave Codex its own Mac Mini I was playing around with Codex CLI a lot over the holidays, and apart from making it run 30 instances of itself as "subagents" (actually just doing codex exec runs in background terminals) I also decided to buy a fresh Mac Mini and give it to Codex. I quickly implemented a pretty simple setup, that consists of a Codex caller that controls Codex process and that forces it to run in an endless loop, and a Telegram bot through which I interact with the agent. The s…

A detailed write-up covering all optimizations and the development process will be published soon

Happy new year 🕺

A new blog post with my predictions on AI progress in 2026. https://gusarich.com/blog/ai-in-2026/

TON Vanity Meet the new blazingly fast vanity address generator for TON smart contracts! The previous state-of-the-art solution was released 3 years ago and hasn't improved much since. We at TON Studio decided to develop a completely new solution from scratch, following the usage patterns the previous solution introduced. Optimizations in both the smart contract and the kernel lead to extreme generation speedups. In realistic usage scenarios on an RTX 4090, the generator finds suffix patterns…

My personal opinion based on experience: * GPT-5.1 has the best instruction following, strong agentic capabilities, and very good skills in math, coding, and problem solving. * GPT-5.1-Codex-Max has worse general capabilities than GPT-5.1, but is noticeably better for large and complex coding tasks. * Opus 4.5 has the best implicit intent understanding, very good instruction following and agentic capabilities, but lacks depth in its reasoning that is required for complex problem solving. * Gemin…

What LLM to use today? Many major releases occurred in the past weeks. The current frontier consists of models that a couple of months ago were only rumors. And they are great. OpenAI has GPT-5.1 and GPT-5.1-Codex-Max; Anthropic has Opus 4.5; Google has Gemini 3 Pro. I'm often working with code, and therefore I need a good coding model. I look at coding benchmarks, like SWE-bench, but scores there differ by just a couple of percent. Are there just no leaders for coding right now? It's just th…

AI would discover a lot of new science.

There is nothing out-of-distribution AI turned out to be very simple if you think about it. You just make a model that works with something generic, and feed as much training data as you can into it. The generic data I mean here is text. People had writing for thousands of years and the whole world is built on it — we write, we speak, we read, and we listen our entire lives. It's so deep in our brains that it's hard to think of something that cannot be described in text. Some AI pessimists lov…

There is no singularity When mentioning singularity, people often think of some "point" in time when AI progress starts to speed up exponentially very quickly with no human control and it all kind of converges to infinity and we don't know what will happen the second after. And I myself had a similar picture in my head too, until recently. I was thinking that predicting anything after 2027 is impossible because of this "singularity" that I thought would happen in that period. I decided that I …

Writing with AI If you scroll up through my Telegram channel, or open my first blog posts, you will easily notice how they were completely written with AI. Those very obvious patterns that are very easy to spot, like "this isn't just X, it's Y". I was mostly writing drafts myself, but using AI to "finish the paragraph", and also to completely rewrite the whole draft in the end for the purpose of fixing grammar errors and "improving writing". I'm now ashamed of that. A lot of time has passed an…

Channel photo updated

This February I made a prediction that AI would surpass top human performers in competitive programming by the end of the summer. For context, at that point, the best models we had were o1, Sonnet 3.6, and Gemini 2.0. They couldn't reliably solve even simple tasks, and the only hint we had was the late-December preview of o3 (which eventually turned out to be a different version from what we got in April). This "o3-preview", when benchmarked on Codeforces contests, ranked in the 99.8th percenti…

Why did many people have a bad first impression of GPT-5? Actually, the reason behind that is absurdly stupid. OpenAI fucked up with UX. That's it. The model is actually good; all variants of it are. But OpenAI rushed the release for some reason, and their goal of making the UX better made it worse for a lot of users. The key detail here was the model router that they added to ChatGPT so that users don't have to manually choose a model, and it can just choose the appropriate one on its own. Fo…

My impression of GPT-5 This was an extremely anticipated release. Literally the whole AI bubble waited for it and watched closely. It's been 2 years since GPT-4, and people expected something extraordinary. Me too. I raised my expectations for GPT-5 in the past few months - hoping that it would basically be "o4" but under a new name. And I expected a capability jump similar to the jump from o1 to o3. I was also watching the whole rollout extremely closely and had tried out GPT-5 before the of…

https://www.youtube.com/live/0Uu_VJeVVfo?si=_01lfBGSyzd_7hoA

The Complexity Threshold of AI We see dozens of new LLMs heavily tuned for software engineering tasks, and they're becoming very good at it, very quickly. As models evolved, I started using them more and more for writing code, eventually reaching a point where I almost completely stopped writing code myself. The last time I wrote code manually (or rather, with AI-assisted tab completions) was around four months ago. However, once tasks become larger and more complex, these models quickly become…

✍️ New Blog Post: "Billions of Tokens Later: Scaling LLM Fuzzing in Practice" I've spent months running LLM-powered fuzzing at production scale—processing billions of tokens, discovering practical scaling laws, and developing effective deduplication strategies. Here’s what I learned along the way: https://gusarich.com/blog/billions-of-tokens-later/