The Post-AI Internet Doesn't Look Great – Jordan Goodman Jordan Goodman Home Blog Portfolio Consulting The Post-AI Internet Doesn't Look Great 02 Sep, 2026 Since the explosion of usage in generative AI, much of the internet is pretty much unusable. Search engines inject AI responses, when I actually want the answer from the source directly. Social media platforms are being bombarded with slop posts from bots. For that reason, I have deactivated most of my accounts, especially X. The barrier to generate content is trending toward 0, causing noise to drown out the signal. For the reasons above, my relationship with the internet has changed into something a bit more peaceful - posting and interacting here on my website, subscribing to rss feeds and substack bloggers that have in-depth content, and being super picky about what youtube channels I subscribe to. I hope the internet becomes usable again. ✉︎ jordan@jordangoodman.xyz · Subscribe via RSS Powered by Bear ʕ•ᴥ•ʔ
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GitHub - lajosdeme/mole: A deep-research agent with an enforced budget, verified quotes, and a privacy boundary for local data. · GitHub Skip to content Navigation Menu Sign in Appearance settings Platform AI CODE CREATION GitHub Copilot Write better code with AI GitHub Copilot app Direct agents from issue to merge MCP Registry Integrate external tools DEVELOPER WORKFLOWS Actions Automate any workflow Codespaces Instant dev environments Issues Plan and track work Code Review Manage code changes Code Quality Enforce quality at merge APPLICATION SECURITY GitHub Advanced Security Find and fix vulnerabilities
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Well, Astra is here, kind of. It's being rolled out to some special companies and organizations, but the rest of us peasants who will get it shortly. Very likely it'll be Very likely it'll start rolling out within in the next 24 hours. Most people will receive it, it sounds like, over the next few days. And this model, Astra, aka GPT-6, it might be AGI. Greg Brockman kind of hinted at the fact that we might be there. And certainly when you look at some of these results, it does seem like we might be. GPT-6 Astra got a 99.9 on the ARC AGI-3. The previous OpenAI model, Claude Opus 5 got 30.2%. So, it was a little bit frustrating sitting there waiting for it to get released, then getting the PR, all the the news rolling out, basically saying that it's out, but not for you. No Astra for you. Also, the news reported the ARC AGI-3 numbers as 98.6 instead of 99.9. And of course, we know this is the first critical model under the OpenAI Preparedness Framework, specifically for its cyberattack capabilities. The SRE bench is a cybersecurity benchmark. Notice the previous best was a 69, right? So, one in three failures, roughly, versus now it's at 99. So, one in a hundred, that's quite a big
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The Pulse: We need to talk about migrations with AI - The Pragmatic Engineer Menu Close Home Newsletter Podcast Sponsors Ethics statement Now My Books Early trends Investing Contact me About RSS Feed bluesky twitter youtube linkedin Subscribe Home Newsletter Podcast Sponsors Ethics statement Now My Books Early trends Investing Contact me About RSS Feed bluesky twitter youtube linkedin Menu The Pulse: We need to talk about migrations with AI Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover Big Tech and startups through the lens of senior engineers and engineering leaders. Today, we cover one out of four topics from last week’s The Pulse issue. Full subscribers received the article below seven days ago. If you’ve been forwarded this email, you can subscribe here . OpenAI put an impressive-sounding case study about how they helped Asana save $5.9M with a single migration. From OpenAI (emphasis mine.) “Asana cleared 5 years of engineering work in 2 weeks with Codex . Using OpenAI Codex, Asana replaced an outdated testing system in two weeks for about $12K. For this project, Codex helped Asana’s engineers remove Enzyme, an outdat
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All right, we got to talk about this. And I'm going to be real with you, I'm a very mad about this whole thing. I'll tell you why in just a second. This is a Jacob Coxon. He quit Anthropic because he said neither OpenAI nor Anthropic know what they're doing. They're gambling with our lives and AI could kill us all by the end of the decade. He didn't quite say that, but it's strongly implied. Today Anthropic posted this about various failures of alignment in their Claude models. This is actually what I was recording a video about today. And we'll get to that in the end because there's a lot of interesting stuff in here. But here's a couple of points. This post here and everything that's happening around it, it's not organic. Every time you hit refresh, the number goes up in a certain interval. This isn't happening through organic reach. So far, at least 22 politicians responded directly to the tweet with calls for legislation to regulate AI. Two governors, seven senators, 13 representatives. A large well-known account in kind of like the the trading space, Zerohedge, is saying that this person was only there 6 weeks. Now we have some Anthropic employees kind of vouching for him sayi
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Friend recommendation is inherently graph-structured: the relevance of a potential connection depends on multi-hop social context rather than user attributes alone. However, deploying message-passing GNNs on a production-scale social graph with hundreds of millions of users and tens of billions of edges requires addressing numerous modeling and systems challenges. We present a scalable end-to-end GNN ranking system for production social graphs, focusing on two design choices that are critical in this setting: multi-hash ID embeddings and temporal neighbor sampling. Multi-hash embeddings are common for high-cardinality features, but industrial GNN systems typically either ignore trainable IDs or accept full embedding tables, exceeding 200 GB for our graph. We integrate multi-hash as the primary node representation, reducing the ID-embedding table size by more than 98 percent while preserving ranking quality. Temporal neighbor sampling is well understood in principle, but existing implementations scan full adjacency lists, which is a non-starter for users with tens of thousands of friends. We implement timestamp-sorted CSR storage with binary search, reducing the per-node temporal sa
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Quick impressions: A week of using Codex more than Claude | All about coding All about coding Ruby and Rails technical content written by Lucian Ghinda home posts archive about llms.txt Quick impressions: A week of using Codex more than Claude Aug 21st, 2026 · Markdown version #codex #claude-code #coding-agents #developer-tools #ai Some quick and very personal impressions from using Codex more than Claude this week (I will do a full analysis during the weekend hopefully). (1) While I tried this year to keep Claude and Codex on par, having the same set of plugins/skills and so on, Claude had more skills, as I created skills out of some sessions and not all of them were ported to Codex. Fix for this is simple: Point Codex at the Claude skills folder and ask it to transform them for Claude (2) When I was in a rush (like debugging something that felt urgent), I still opened Claude as somehow I felt more at home with it. I am not saying it was better, but it was familiar, and when debugging, using tools that I know is important. (3) Changes created by Codex had fewer comments in Ruby/Ruby on Rails code. I liked that a lot, and I will soon share some experiments I ran on this. (4) The ou
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[2608.10863] Time to Move on: Querying without Nulls and Bags Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Databases arXiv:2608.10863 (cs) [Submitted on 11 Aug 2026] Title: Time to Move on: Querying without Nulls and Bags Authors: Molham Aref , Leonid Libkin , Wim Martens View a PDF of the paper titled Time to Move on: Querying without Nulls and Bags, by Molham Aref and Leonid Libkin and Wim Martens View PDF Abstract: SQL is the database community's success story in terms of language design. The key reason for its success is its declarativeness: it gives rise to optimizability, reducing the programmer's burden significantly. However, given the evolving complexity of problems to solve with query languages, our community needs to re-think some of the fundamental early query language design decisions. Our experience in having worked on the design of Rel (a language for end-to-end relational programming) tells us that it is possible to design, implement, and successfully deploy a language based on fully normalized relations. Such relations avoid what Codd called corrupted relations and what we commonly refer to
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Power 2026 by Neel Somani - Electricity Pricing in the Age of AI INDEX 01 Preface: Motivation All About Power Plants 02 Fundamentals of Commodities Pricing 03 The Power Plant 04 To Build A Power Plant 05 Case Study: Homer City 06 Meeting the Growing Demand How To Trade Power 07 Power Markets in the US 08 Case Study: Alberta 09 The Production Cost Model 10 Practical Approximations 11 Types of Power Trades #1 on Apple Books · Top Free · CALCULATING... Power 2026 Electricity Pricing in the Age of AI Neel Somani CHAPTER 01 Preface: Motivation AI demand is exploding. But while there's been plenty of discussion on the GPU and memory supply chains, the real constraint to expanding AI capacity is power. Data centers already account for ~5% of US power consumption [1] . With data center power demand doubling every two years [2] , demand would in theory outpace total US power generation by the mid-2030s. Building a data center requires thoughtful planning around permitting, surrounding infrastructure, and anticipated power prices. In many cases, the variable cost of power determines whether or not a data center is viable at all. I'm a former quant researcher at a major hedge fund who covered