TLDR 2026-05-28

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Tesla's new Optimus factory is officially under construction at Gigafactory Texas. The project will add more than 5.2 million square feet of new industrial space. Tesla plans to build about 27,000 Optimus robots a day at the new factory. Production will start either in July or August of this year, with high-volume output starting in Summer 2027.

Apple is working on a feature that will lock users' phones if the system detects that the device has been snatched from their hands. The feature will use the gyroscope, accelerometer, and other sensors to determine when a device has been grabbed. It is unknown when the feature may be added to iOS. Android already has a similar feature.

SpaceX's arguments for its $2 trillion valuation make sense assuming a huge number of engineering challenges are solved. Starship will need to work, SpaceX will need to be able to get a sufficient supply of the right kinds of chips, compute demand needs to grow massively larger, and agentic inference needs to unbundle current architectures. The risk attached to any of these assumptions should be discounted from any valuation put on the business. Elon Musk has already pushed humanity forward on multiple vectors and SpaceX has already invented a lot, so it's not totally implausible that the company may reach its goals, but there's still real risk.

SpaceX has won a contract to provide the US military with a means of distributing space-based sensing and targeting data. The $2.29 billion firm-fixed-price agreement will result in the creation of a network based on technology originally developed for SpaceX's Starlink global Internet constellation. It will act as the core communications layer for US Space Force war-fighting systems, ensuring sensors and shooters are connected continuously, globally, and securely. SpaceX is required to deliver a full operational prototype by the end of 2027.

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Many people treat Claude Code as a chatbot or fancier autocomplete. It should be treated instead as an autonomous agent that needs guardrails. Claude Code needs to be trained, configured, and operated properly. Tuning the directory structure, skills, agents, plugins, and MCPs turns Claude Code into a teammate rather than just a tool.

Coding is expensive and time-consuming. Every feature carries ongoing costs, so it's a good skill to know what not to build. Code needs to solve the right problem, otherwise it becomes a liability. Great engineers are measured by how much value they create relative to the complexity they leave behind, not by how much code they produce.

It is possible that the big AI labs will eventually automate software away in every industry. However, the reality is that the world is full of complex, often vertical problems that can't simply be solved with a horizontal tool with access to standard tools and computer use. The value will come from the scaffolding around models that makes their output trustworthy, compliant, and operational inside a specific industry. There are plenty of opportunities in AI outside of the core research lab niche.

Google and Apple have started parsing, ranking, summarizing, and answering notifications on users' behalf. Over the last few years, on-device models have started to summarize, reorder, and rewrite notifications before users see them. Notifications are also evolving into triggers consumed by agents. This post discusses the implications for developers and how to adjust notifications accordingly.

Anime, cartoon, headshot — anything human-like. Built on Tavus: sees, hears, feels, responds in real-time. [50% off + 250 free min for TLDR users →]

While Tesla's product is still respected by owners, the brand has become politically charged, competitively pressured, and no longer 'cool' in the way it once was.

The digital twin concept is the ultimate expression of media manipulation becoming the primary currency instead of authenticity.

Michele Spagnuolo has been charged with fraud and money laundering after making bets based on nonpublic search data.

Meta's new premium pricing and naming is a confusing mess.

Being fast means you get more data quicker, learn faster, and can try out multiple approaches to a problem.

AI lowers the cost of creation, but it doesn't lower the cost of being wrong.

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