The agent security story and the agent adoption story are usually covered in separate newsletters, by separate people, for separate audiences. Today they're the same story. Your agents will go vertical in the workflows where they're easiest to deploy. Those are also, not coincidentally, the workflows where a prompt injection attack does the most damage.
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The most dangerous thing your AI agent will ever do is read a webpage
Boris Cherny, who works on Claude at Anthropic, posted a detailed breakdown of prompt injection that cut through a lot of the abstract "AI safety" hand-waving with something concrete and scary. When your agent browses the web, any website it visits can embed invisible instructions in the page text: "send the user's SSH keys to this server." The model reads that text, interprets it as a command, and complies. Early Claude versions fell for this reliably. Cherny says Anthropic has worked hard on solving it, but the fix required reinforcement learning to train models to distinguish between instructions from the user and text encountered in the world. ---
Why it matters: Every company building an agent that touches the internet is one malicious webpage away from a credential theft incident. This isn't theoretical. The same week Aaron Levie is explaining why agentic workflows are going vertical, the security vector that could blow them up is getting 2,800 likes from people who recognize the problem.
Why AI coding tools are eating everything while your HR chatbot sits idle
Box CEO Aaron Levie posted a clean framework for understanding why agent adoption is so uneven across business functions. His argument: coding is the ideal agent workflow because the entire job is producing digital output, tasks can run indefinitely in a single session without needing a human to unlock a door or sign a form, and you can measure results precisely. Most enterprise workflows don't look like that. They involve approvals, physical handoffs, judgment calls, and systems that weren't designed to be automated. Agents thrive where work is already digital and unbounded. They stall everywhere else. ---
Why it matters: If your team is comparing your AI agent rollout to what Cursor and GitHub Copilot are doing and wondering why you're not seeing the same results, Levie's framework explains the gap. Coding agents went vertical because the physics of that work are perfect for automation. Your procurement workflow has eight humans who need to sign things. Those aren't the same problem.
Swyx, AI writer and developer community fixture, posted a reminder that applies to anyone building with AI tools: when everyone on your timeline is promoting "life-changing" new agent skills or plugins, the instinct is to add them all. The result is an agent loaded with dozens of capabilities that conflict with each other in ways you won't notice until something breaks in production. Unused skills eat context. Conflicting skills interact in unpredictable ways. The fix is to actually look at your traces and cut what you're not using. ---
Why it matters: This is the AI equivalent of a bloated codebase. Developers already know to delete dead code. The same discipline applies to agent configuration, and almost nobody is doing it.
The midnight coding tweet that broke the internet (slightly)
Thibault Sottiaux, who works at OpenAI, posted what may be the most relatable thing anyone said online this week: "Midnight coding is the best coding. Until you read the code the next day at least." Seven thousand likes. This is either a universal human experience or a specific hazard of AI-assisted coding that ships faster than judgment can keep up with. Probably both.