Tech

Forward-deployed engineers are the AI industry’s latest talent obsession

A new study estimates only 2,000 U.S. engineers have the expertise to deliver meaningful AI ROI, as enterprises race to hire forward-deployed engineers to implement AI at scale.

With a stateless makeover, new MCP spec targets enterprise scale

Plus, a new policy for the AI protocol ensures features aren’t removed suddenly.

Scale AI has a new CEO: the current COO of Google Cloud.

Francis deSouza will begin as CEO on August 10, taking over from the interim CEO who has been leading the company since Alexandr Wang, its founder and former CEO, joined Meta in June 2025. Joe Osborne, a spokesperson for Scale AI, said the company’s new focus on building AI applications for enterprises and governments, rather than solely data labeling, has it projecting more than $1 billion in 2026 revenue.

Lilian Weng, co-founder of Thinking Machines Lab, has returned to OpenAI.

Weng had left OpenAI along with a handful of other employees to co-found the competing AI startup, which was helmed by Mira Murati, OpenAI’s former CTO. Weng recently shared a note that after being “absent for a month” to focus on her health leading up to Thinking Machines Lab’s first model release, Inkling, she was making the decision to leave behind “consistent stress and workload” to pursue “a scoped role in a more predictable place.” She is reportedly already back at OpenAI.

Scale AI hires former Google Cloud COO Francis deSouza as new CEO

deSouza replaces Alexandr Wang, who left for Meta last year.

TechCrunch Disrupt 2026’s biggest stage features leaders from Amazon, Replit, Tether, with much more to come

The Disrupt Stage is where many of the biggest conversations in technology happen, with a legacy that stretches back for more than a decade.

Instagram and Facebook will likely require a redesign after EU rules they’re ‘addictive’

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Meta and YouTube found negligent in landmark social media addiction case

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How to spot AI writing

A GHOST WRITER is haunting the English language. The linguistic spectre can turn its hand to prose, poetry, journalese and corporate jargon. It is frightfully versatile: you can get it to mimic Shakespeare’s sonnets or a schlocky beach read; Ernest Hemingway’s taut prose or the office-printer manual. It is frightfully fast, churning out thousands of words a minute. (Hemingway rarely produced as many in a day, and required much more booze.) Wordsmiths are spooked.

AI is getting better at writing. Humans must get better at editing

WRITING IS HARD. For Franz Kafka, putting words on the page was a process of “unending torments”. George Orwell said it felt like “a long bout of some painful illness”. Hunter S. Thompson, a journalist, saw it as the opposite of sex: “only good when it’s over”. Now AI has come to the rescue. Large language models (LLMs) eagerly offer reams of text without any pain or torment. Bots can spew out emails (excellently), longer prose (passably) and poetry (poorly). To them, writer’s block is a 500-sheet pack of paper: any user of an LLM can produce as many words in a day as Kafka did in his life.

Cartoon: Who benefits from AI?

A lighter take on the news

Dili raises $21.7 million to bring AI compliance to the infrastructure boom

The Series A was led by Khosla Ventures, with participation from Allianz, Rebel Fund, Brick and Mortar Ventures’ Darren Bechtel, and Y Combinator’s Garry Tan.