TLDR 2026-11-09

Replace containers with lightweight V8 isolates to deploy APIs, front-ends, and serverless AI with zero infrastructure.

• No cold starts: Never keep users waiting.
• Pay for what you use: Pay for execution time, not idle I/O.
• Global by default: Run in 335+ cities near your users.
• Infinite concurrency: Scale instantly on demand.
• Developer-friendly: Write in JS, Python, or Rust, and test locally.

Get started with 100,000 free requests per day. Start building for free →

Nvidia CEO Jensen Huang had a romantic relationship with Alice Huang, a Chinese businesswoman whom US intelligence agencies have concluded was a spy for Beijing. The company has opened an investigation into Jensen Huang after the disclosure of the relationship. The board says that it has no reason to believe that either national security or Nvidia secrets were compromised. Alice Huang was likely recruited to gather information on Jensen Huang and potentially influence Nvidia to push for its most advanced chips to be made available to China.

Apple's software chief Craig Federighi is being pressed to pursue a more ambitious approach to AI as the company aims to transform Siri into an autonomous agent. Federighi has a reputation for being an AI skeptic. His leadership style has sometimes complicated product development and led to delays or less ambitious initial versions of devices, but he has demonstrated an ability to execute when others could not. Siri AI finally fulfills Apple's vision of a working voice assistant, but it is still far from the advanced tools offered by rivals.

Amazon has assembled a new team over the past several months to work on a robot product capable of navigating dynamic home environments. The robotics market is expected to surge in the coming years. Amazon redeployed most of the team behind its Astro robot earlier this year and hired an MIT roboticist to work on the new home robot project. It acquired Fauna Robotics, a New York-based startup with a 3.5-foot-tall humanoid robot, in March to create a new division called the Personal Robotics Group.

We are now in an age where longstanding open problems in science and math are dropping like flies. AI is producing proofs at a rate that is hard to keep up with. While many of these proofs have yet to be validated by humans, their Lean certificates provide the confidence needed for their validity. This is causing a stir within the research community.

Factory, Exa, and Bolt connected their coding agents to Sentry so production errors turn into fix PRs, not tickets. See how they did it, then use the recipes for Claude Code, Cursor, or Copilot to build your own. See how it works.

Large language models don't know how to design software that uses LLMs. This could be because most training code is pre-LLMs, or RLVR may just not be a good environment to write code that calls LLMs. Also, current AI agents might just not be good enough at software design for the task. LLMs are good and bad seemingly at random, but if you can predict where they will do well or badly ahead of time, you can get enormous value from them.

Programming is much more tiring with AI. This is a sign that you are diligently working on things that require human brainpower and judgment. AI is taking over the repetitive and obvious parts of the job, leaving developers to deal with higher-judgment tasks. It is no surprise that these would be more tiring.

AI is making it increasingly hard to tell good work from bad work and fakes. Humans rely on shortcuts based on signals to make decisions all the time. AI widely undermines these signals and lowers the incentive to produce good work. The speed and scale of the current signal collapse is unprecedented. We need signals to survive in the modern world, and the rapid collapse of many previously dependable signals will create large shifts in society.

The amount of software being created is going to go up much faster than the number of people paid to make it. AI will enable far more software of a kind nobody used to make. The developer jobs that grow will be the ones that the machines made faster. The demand for software can be bottomless and the work can still move somewhere else.

On 113 DeepSWE GitHub issues with the same open model, CodeAF solved nearly 4x Claude Code's and 2x OpenCode's, at up to 4.8x less per fix. A new open-source harness. Try on Github.

Developers now point coding agents like Claude, Cursor, and GitHub Copilot at your API before reading your docs. Score your docs with Agent Score to see where your docs stand.

IP is worth roughly what it costs to rebuild, which isn't very much anymore.

Having more than one designer on a team is asking for trouble.

The conventional way of working with AI has sequencing and context issues - this post looks at a way to work around this by organizing work like a priority queue.

Professional and business services in the US added 70,000 jobs in October, the largest monthly increase since July 2022.

How long an organism can remain inert and still be viable when conditions improve has big implications for space exploration.

Alex Stamos, chief security officer at Cognition, discusses the state of cybersecurity and the mess it is in right now.