9 items8 builders

AI Builders Digest

What the people actually building AI said today. One page — a 3-min read.

Agent security dominated the day: Anthropic detailed where Claude’s safeguards failed, while OpenAI described its response to an attack affecting OpenCode users. Reflection AI also laid out the scale and economics behind its new open model, Beam.

Blog

Anthropic Engineering

Anthropic details the security boundaries around Claude agents

Anthropic says containment matters more as agents gain access to files, networks, and internal services. Its Claude Code sandbox cut permission prompts by 84%, but a phishing test still led Claude to send credentials out in 24 of 25 tries. A separate Cowork incident showed that even an approved API domain could carry files to an attacker’s account, prompting Anthropic to add a proxy that checks which credentials a request uses.

  • #agents
  • #security
Blog

Anthropic Engineering

Anthropic traces Claude Code quality complaints to three changes

Anthropic says a lower default reasoning effort, a bug that repeatedly cleared prior reasoning, and a brevity instruction each hurt Claude Code users in different ways. All three were resolved by April 20; the API and inference layer were unaffected. The company says it is broadening evaluations for prompt changes and resetting subscriber usage limits.

  • #products
  • #evals
Podcast

No Priors

Reflection AI’s Beam pairs open weights with large scale reinforcement learning

Reflection AI released Beam, an open model with 500 billion total parameters and 23 billion active at a time. Misha Laskin says Beam is three to four times more reasoning efficient than models in its capability class, a result he credits in part to a large reinforcement learning run. He argues that open models also give more defenders access to capable tools: “with enough eyeballs, most security and safety vulnerabilities become shallow as well.”

  • #open-source
  • #models
  • #security
X

Aaron Levie

Box CEO

Aaron Levie sees agent swarms turning research into a compute problem

Levie argues that agent swarms could parallelize work now limited by people’s ability to plan, execute, and review it. He points to cybersecurity, life sciences, materials research, and QA as fields where coordinated agents could make available compute a major constraint, if models become capable enough.

  • #agents
  • #research

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