https://t.co/kxkbc79LTn

Anthropic literally dropped the Prompt Guide to 10x your Claude Opus/Sonnet 4.5 10 best practices you should know. Bookmark this. 👇

Just updated the Big LLM Architecture Comparison article... ...it grew quite a bit since the initial version in July 2025, more than doubled! https://t.co/oEt8XzNxik

Chroma is hiring! Help build the Apache 2.0 distributed database written in Rust powering search for frontier labs, Fortune 500, and many of your favorite startups. (25k github stars, 9M monthly downloads) The team is small and you will have an immense impact. DM me!

"How to become an effective senior software engineer": The T-Shape - my latest free video: https://t.co/GwNVY0wrWA

"Mount Mayhem at Netflix: Scaling Containers on Modern CPUs". Ultimately, the best solution combined hardware awareness with software improvements. by @NetflixEng https://t.co/SuJenizsIV

API Pagination Techniques 1. Offset-Based Pagination → Definition ✓ Uses offset and limit parameters to fetch specific slices of data. → Example GET /products?offset=20&limit=10 → Pros ✓ Simple and widely supported ✓ Easy to implement and understand → Cons ✓ Slow

AWS finally talked about the Oct. 20th outage and holy shit, @QuinnyPig was right the whole time AWS uses DNS (route53) as a database, creating a txt record to indicate which node holds the lock while it updates the public DNS records for the entire region Total Corey Victory

Interview with a Former $GOOGL employee on the cloud economics and $GOOGL TPUs: 1. When it comes to the GPU economics for a cloud/hyperscaler provider, he mentions that the margins aren't as good as with the non-GPU compute. He also discusses Kubernetes and the services built on

Ready for tomorrow’s lecture: 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗼𝗻 𝗚𝗣𝗨𝘀

How modern database systems can leverage the Linux io_uring interface for efficient, low-overhead I/O https://t.co/gONgy5YBfS @m4ttze @melhindiCS @Tobias__Ziegler @viktor_leis @cbinnig

Writing a CUDA kernel requires a shift in mental model. Instead of one fast processor, you manage thousands of tiny threads. Here is the code and the logic explained for Matrix Multiplication.

First large-scale study of AI agents actually running in production. The hype says agents are transforming everything. The data tells a different story. Researchers surveyed 306 practitioners and conducted 20 in-depth case studies across 26 domains. What they found challenges

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Agree with @istoica05 that AI-driven research systems should free humans from the inner experimentation loop so we can focus on what really matters: choosing the right problems, designing robust evaluation frameworks, and interpreting results. We may soon reach a point where

New blog post. In the era of LLMs, what does learning look like? What happens when are overconfident in our understanding due to AI sycophancy? Is it even useful to use LLMs for education without outsourcing our thinking? https://t.co/X8i3qj7Jn0

earlier this year, i asked jensen how he designed nvidia's org chart 'the org looks like a computing stack' most founders treat org charts as HR paperwork. jensen treats them as architecture. there is a reason nvidia has one of the highest market caps per employee

What comes after Transformers? Neural Memory and Test-Time Training! @GoogleResearch presented 2 new papers during NeurIPS with an architecture that actively learns and update their own parameters during inference, acting as a "long-term neural memory" rather than a static

After leading the creation of CUDA C++, Vinod Grover @vinodg (Sr. Distinguished Engineer, @NVIDIA) now focuses on the compiler techniques that make modern AI training and inference possible. Come listen to his invited talk, titled: "The Essence of CUDA and AI for GPUs"!

Build Your Own Key-Value Storage Engine—Week 3: Durability with Write-Ahead Logging (Written in collaboration with @ScyllaDB) This week, we explore how to make data durable with the use of a WAL. https://t.co/1zXSqJadGK