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Ivan Santos
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You can’t be perfect, no one needs you to be perfect anyway, it’s too expensive to try to be perfect, and everyone is really happier at the end of the day if you accept those facts. - Implementing Service Level Objectives (Alex Hidalgo)
objectives implementing happier
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15 September
Creator of Homebrew, the macOS package manager, and a Swift developer.
Products for devs are quite dead. SaaS for devs is dead. There are exceptions, though I think you have to extrapolate on variables that are not raw software. I have ideas and am implementing them. Mostly in private because building in public also can no longer be capitalized upon. Seemingly. Quoting @alex_holovach my WHOOP subscription expired so i had codex reverse engineer it and build my own app - telemetry goes to my prometheus server - grafana and the app visualize it - hermes monitors metrics and plans workouts next wanna build my own Zwift and Strava the era of personal software is here SaaS Related
13 September
AI research engineer working on large language models. He writes the Ahead of AI newsletter and is the author of Build a Large Language Model (From Scratch).
Reasoning from scratch round 3: This time, I cover generating a verifier for... a) ...evaluation (base model versus any future model improvement) b) ...the reinforcement learning with verifiable rewards (RLVR) training later on 00:00 Introduction 01:21 Four approaches to LLM evaluation 07:20 Verifiers and reinforcement learning with verifiable rewards 10:52 Notebook setup and dependencies 13:43 Section 3.1 Building a math verifier 18:57 Section 3.2 Loading a pre-trained model to generate text 24:34 Generating and displaying model answers 29:23 Section 3.3 Implementing a wrapper for easier tex… LLMs Related
9 September
Co-creator of Django and creator of Datasette; writes daily at simonwillison.net.
"Deterministic code checks the result" sounds like they might be implementing a variant of the DeepMind CaMeL paper simonwillison.net
Quoting @dps One threat we’re particularly focused on is prompt injection, and we handle it in layers. The model is trained to recognize and resist it. The harness marks anything coming from an untrusted source. Deterministic code checks the result. And an ensemble of classifiers runs where the agent can't reac… Google Related
3 September
Creator of Flask and Jinja. Writes about software at lucumr.pocoo.org.
31 August
Mac and iOS developer at the Iconfactory, where he has worked on apps including Twitterrific and Tot. He writes about development at furbo.org.
10 August
Swedish designer and programmer. Designed early Spotify, worked at Facebook and Figma, and created the Inter typeface.
Is there a service where I can rent access to Linux desktop machines with actual displays? We're implementing the Playbit runtime for Linux and it's surprisingly difficult to test various desktop configurations. We need a real GPU with a display connected, for testing dawn/webgpu, vsync, display sleep, etc. We use Modal and AWS, neither have had machines that I've been able to test with properly. Ideally there's a way to test a variety of systems (like ubuntu, arch, alpine etc) × GPUs (nvidia, amd, intel) × window managers. Linux Related
Software engineer at PlanetScale and creator of the vim-go plugin. Writes at arslan.io about Go, tooling, industrial design and books.
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Nobody writes the code anymore. Instead you're basically planning, debating, implementing and reviewing with Agents.
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3 April
Computer scientist and director of the MIT Digital Currency Initiative; her research covers distributed systems, databases and digital currency.
My take on Bitcoin and quantum computing: https://t.co/bq2HdAsnXQ tl;dr: I think the risk is high enough to warrant prioritizing designing, implementing, and evaluating post-quantum signature schemes and consensus upgrades in Bitcoin now. Related
24 February
Programmer; wrote Redis and hping, and blogs about C, systems programming and working alone.
11 September 2025
Machine learning engineer and consultant focused on RAG and retrieval systems. He writes about applied AI engineering at jxnl.co and is the author of the instructor library.
6 September 2025
AI research engineer working on large language models. He writes the Ahead of AI newsletter and is the author of Build a Large Language Model (From Scratch).
22 July 2024
Co-founder of Superlogical, started in 2026 to build server-side terminal infrastructure; creator of Ghostty. Co-founded HashiCorp and created Vagrant and Terraform before that.
19 December 2023
Writer on learning and skill acquisition; author of Ultralearning and Get Better at Anything, known for the MIT Challenge and the Year Without English.
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I recently reviewed Beck's book, which is written as a practical guide for therapists implementing CBT.
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scotthyoung.com
30 October 2023
Professor of economics at George Mason University and Bartley J. Madden Chair at the Mercatus Center. Co-writes the blog Marginal Revolution and co-authors the textbook Modern Principles of Economics with Tyler Cowen.
30 May 2023
Programmer and entrepreneur; co-founded GitHub and created Jekyll, Gravatar and the Semantic Versioning spec.
Their words
While we love GraphQL for many use cases, implementing a secure and performant GraphQL API can be tricky and there is a definite cost to requiring it during early prototyping of your app.
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tom.preston-werner.com
1 May 2023
Designer and engineer; formerly principal research engineer at GitHub Next; writes at wattenberger.com.
30 August 2016
Emeritus Professor of Statistics at the University of Cambridge, former president of the Royal Statistical Society, and author of The Art of Statistics.
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Nobody here wrote their own korrents. They are compiled from public
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