One common issue with personalization in all LLMs is how distracting memory seems to be for the models. A single question from 2 months ago about some topic can keep coming up as some kind of a deep interest of mine with undue mentions in perpetuity. Some kind of trying too hard. [Translated from EN to English]
@karpathy
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PyPI Security Incident: 425K Downloads Exposure Timeline
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In particular this clarifies the timeline more: 1.82.7 was published 10:39 UTC, PyPI quarantine approx 13:38, so this was up ~3 hours. At 3.4M downloads/day this might be approx ~425K downloads, a lot of that could be non-latest/locked versions so maybe 20K – 80K range exposure.
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LiteLLM PyPI Supply Chain Attack Steals Credentials and API Keys
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Software horror: litellm PyPI supply chain attack. Simple `pip install litellm` was enough to exfiltrate SSH keys, AWS/GCP/Azure creds, Kubernetes configs, git credentials, env vars (all your API keys), shell history, crypto wallets, SSL private keys, CI/CD secrets, database passwords. LiteLLM itself has 97 million downloads per month which is already terrible, but much worse, the contagion spreads to any project that depends on litellm. For example, if you did `pip install dspy` (which depended on litellm>=1.64.0), you'd also be pwnd. Same for any other large project that depended on litellm. Afaict the poisoned version was up for only less than ~1 hour. The attack had a bug which led to its discovery – Callum McMahon was using an MCP plugin inside Cursor that pulled in litellm as a transitive dependency. When litellm 1.82.8 installed, their machine ran out of RAM and crashed. So if the attacker didn't vibe code this attack it could have been undetected for many days or weeks. Supply chain attacks like this are basically the scariest thing imaginable in modern software. Every time you install any depedency you could be pulling in a poisoned package anywhere deep inside its entire depedency tree. This is especially risky with large projects that might have lots and lots of dependencies. The credentials that do get stolen in each attack can then be used to take over more accounts and compromise more packages. Classical software engineering would have you believe that dependencies are good (we're building pyramids from bricks), but imo this has to be re-evaluated, and it's why I've been so growingly averse to them, preferring to use LLMs to "yoink" functionality when it's simple enough and possible. Daniel Hnyk (@hnykda) LiteLLM HAS BEEN COMPROMISED, DO NOT UPDATE. We just discovered that LiteLLM pypi release 1.82.8. It has been compromised, it contains litellm_init.pth with base64 encoded instructions to send all the credentials it can find to remote server + self-replicate. link below — https://nitter.net/hnykda/status/2036414330267193815#m
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Context and Specification Engineering Beyond Prompting Techniques
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Yes I think in one part of the video I think I still used the word prompt but it's not really about "prompting", it's about context and spec engineering, and then all of the other harness things – tools, workflows, etc.
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AI Agents Generate Poor Code Quality and Ignore Instructions
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I'm not very happy with the code quality and I think agents bloat abstractions, have poor code aesthetics, are very prone to copy pasting code blocks and it's a mess, but at this point I stopped fighting it too hard and just moved on. The agents do not listen to my instructions
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AI as Teammate: Building Partnership with Intelligent Assistants
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Great questions! Starting backwards with (3), I'd hope AIs can feel like Rocky from Project Hail Mary (it's top of mind having seen it yesterday), like a partner and a teammate. As one small example that stuck with me recently, when Claude found the Sonos system on my LAN, it
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Karpathy on No Priors Pod: AI Engineering, AutoResearch, and Future Skills
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Thank you Sarah, my pleasure to come on the pod! And happy to do some more Q&A in the replies. https://t.co/uIeUtFxDkm
— Andrej Karpathy (@karpathy) 21 mars 2026Thank you Sarah, my pleasure to come on the pod! And happy to do some more Q&A in the replies. sarah guo (@saranormous) Caught up with @karpathy for a new @NoPriorsPod: on the phase shift in engineering, AI psychosis, claws, AutoResearch, the opportunity for a SETI-at-Home like movement in AI, the model landscape, and second order effects 02:55 – What Capability Limits Remain? 06:15 – What Mastery of Coding Agents Looks Like 11:16 – Second Order Effects of Coding Agents 15:51 – Why AutoResearch 22:45 – Relevant Skills in the AI Era 28:25 – Model Speciation 32:30 – Collaboration Surfaces for Humans and AI 37:28 – Analysis of Jobs Market Data 48:25 – Open vs. Closed Source Models 53:51 – Autonomous Robotics and Atoms 1:00:59 – MicroGPT and Agentic Education 1:05:40 – End Thoughts — https://nitter.net/saranormous/status/2035080458304987603#m
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Dobby AI Controls Home Automation via WhatsApp
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Yeah I have 4 blog posts that I didn’t finish yet this is one of them. Dobby runs my entire house over WhatsApp. Lights, shades, pool/spa, sonos, security HVAC etc
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Jensen Huang and the Prescience of Deep Learning in 2015
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The signature is alluding to NVIDIA GTC 2015, where Jensen excitedly told an audience of, at the time, mostly gamers and scientific computing professionals that Deep Learning is The Next Big Thing, citing among other examples my PhD thesis (one of the first image captioning systems that coupled image recognition ConvNet to an autoregressive RNN language model, trained end to end). This was back when most people were still unaware and somewhat skeptical but of course – Jensen was 1000% correct, highly prescient and locked in very early. [Translated from EN to English]
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Karpathy receives first DGX Station GB300 from NVIDIA
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Thank you Jensen and NVIDIA! She’s a real beauty! I was told I’d be getting a secret gift, with a hint that it requires 20 amps. (So I knew it had to be good). She’ll make for a beautiful, spacious home for my Dobby the House Elf claw, among lots of other tinkering, thank you!! NVIDIA AI Developer (@NVIDIAAIDev) 🙌 Andrej Karpathy’s lab has received the first DGX Station GB300 — a Dell Pro Max with GB300. 💚 We can't wait to see what you’ll create @karpathy! 🔗 blogs.nvidia.com/blog/gtc-20… @DellTech — https://nitter.net/NVIDIAAIDev/status/2034291235041554871#m