6 items6 builders

AI Builders Digest

What the people actually building AI said today. One page — a 2-min read.

Today’s clearest theme was AI moving from convincing chat to work that software can run reliably. TypeSafe made the case for decision models, while builders focused on the security and compute demands of background agents.

Podcast

The MAD Podcast with Matt Turck

TypeSafe’s Jev aims to make AI decisions reliable enough for software

Diogo Almeida says Jev returns probabilities that developers can test and use to set their own thresholds, instead of generating a polished answer that may hide a bad decision. He wants developers to combine small, dependable decisions into larger automated workflows. His test for current models: “95% Einstein, 5% Mr. Bean. And if it doesn’t tell you when it’s the Mr. Bean, then how are you gonna automate anything?”

  • #products
  • #automation
  • #evals
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Aaron Levie

Box CEO

Aaron Levie predicts background agents could drive 100 to 1,000 times more tokens

Levie argues that letting many agents work in parallel on reviews, audits and other information tasks could use 100 to 1,000 times more tokens than today’s back-and-forth chats. He also sees Meta’s Muse open weights model helping enterprises pair frontier models with cheaper, tailored models for repeatable workflows.

  • #agents
  • #open-source
  • #compute
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Boris Cherny

Anthropic and Gray Swan plan a prompt injection competition

Boris Cherny says Claude has made significant progress against prompt injection, but agents taking on more work make the problem increasingly urgent across the industry. Anthropic is partnering with Gray Swan to host a competition to find weaknesses.

  • #agents
  • #security
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Dan Shipper

Every CEO

Dan Shipper questions what interpretability can reveal about AI plans

Shipper’s pointed take: finding a neuron that responds to the Eiffel Tower would show a model recognizes France, but would not reveal what it plans to do. He is skeptical of treating recognizable internal features as enough to understand a model’s behavior.

  • #interpretability
  • #safety
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Aditya Agarwal

SPC General Partner

Aditya Agarwal sees alignment as an engineering problem

Agarwal says Goodfire may become one of the most important companies to come out of SPC. His reason is its work showing that model interpretability and alignment can be approached as engineering problems.

  • #interpretability
  • #safety

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Source data comes from the open-source project follow-builders by zarazhangrui, released under the MIT license. Summaries are generated by an LLM from that project's public feeds, and the summarization prompts are adapted from it. Every item above links to its original source.

Summaries generated automatically. Read the original before relying on any claim.