As @eastdakota pointed out this week, humans are now the minority of internet users. This has radical implications that I don't think anyone has fully digested yet: 1) Tokens are cheaper than eyeballs. Meaning, ATTENTION IS NO LONGER SCARCE. AI agents are first class users of the internet means that the whole economic model underpinning the internet is at stake. 2) Last fall @sama said that "Margins are going to go dramatically down on most goods and services." I think everyone nodded their head at that but didn't actually grok the long-tail implications of his statement. Any physical good, food, clothes, trips, whatever, all that touches the internet will have their margin eaten by tokens. Maybe that all goes towards consumer surplus, maybe it all goes towards Nvidia, but that money certainly isn't going to the digital SMB. 3) What is scarce is not taste. Taste is a nice idea that I believe in, but it has to be paired with high value, non-AI reproducible SKUs, because otherwise people will just replicate it for the cost of tokens. For example, I have readers who have made an "Evan Armstrong" skill on claude code that they ask for advice on their business strategy problems. I also talked with @blauyourmind about @trydrip and @carrawu about Index from @p0 about their respective products trying to make this situation tenable for content providers. Their services charge AI agents a token tax everytime they reference a piece of content. I think these are good, noble ideas that I want to succeed. But startups selling content or software should view them as beer run money, not as long-term defensible assets that create enterprise value. Anyways I'm buzzing, this is a radically different internet and is a problem I'm going to be chewing on for awhile. Reach out if you have thoughts or are building something.

Microsoft discovered that Anthropic's Claude Code GitHub Action could expose CI/CD workflow secrets when AI agents process untrusted content, including issue bodies, pull request descriptions, and comments. msft.it/6017vdfUc Following our disclosure, Anthropic mitigated this issue in Claude Code version 2.1.128 by blocking access to sensitive /proc files. Read the blog for details from our research, along with practical guidance for reducing prompt injection, over-permissive tooling, and secret exposure risks in agentic CI/CD workflows.

We're ready for tomorrow. Are you? The Agentic Finance Summit program covers the full agentic stack: payment rail selection, agent identity and trust, enterprise spend controls, autonomous capital allocation, and the standards being built around agent-initiated transactions. Focused on how these systems get built in production. June 3, New York · Full agenda: agenticfinance.xyz/agenda

UPDATED: the Agentic Finance Landscape for Q2 2026. Our most in-depth report yet. Agentic finance is a household name now. Since our Q1 report, Robinhood, Visa, Mastercard, Stripe, and many other reputable names have acknowledged that agents are the future of finance. Not all agents will make it into that future. That's why our team spent the last 3 months testing agents, filtering out hundreds of slopbots, and identifying only the most legitimate projects shaping this emerging sector. Presenting the latest cohort of the AgentFi Landscape 🧵

One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organization to help customize solutions, such as building and tuning agentic workflows that suit the client’s particular needs. I’ve heard from people who are wondering anew about the FDE career path since OpenAI and Anthropic started building new teams to place FDEs within client organizations. The rise of FDEs for AI workloads is one way AI is creating new jobs (and why the jobpolcalypse narrative of upcoming job market collapse is false -- there will be many AI and non-AI jobs). However, I believe there will be far more AI Engineer jobs than FDEs, as I explain below. The FDE role was pioneered about two decades ago by Palantir, which sent engineers to government locations to work on secure, air-gapped networks. In addition to having good technical skills, FDEs need communication skills and sometimes business skills. For example, they may need to speak with clients to understand their needs, formulate a strategy to prioritize projects, explain complex technology, and respectfully push back if a client asks for something unrealistic. They’re enjoying a resurgence because of the amount of work involved in taking an off-the-shelf LLM and building it into a custom agentic workflow that fits particular business needs. However, I believe the number of AI Engineer jobs will be far larger. A company might accept a few FDEs to be embedded within its organization. But most companies will want far more of their own employees working on their projects. While my organizations do hire FDEs, we hire far more AI Engineers! Also, a common client concern is that it is hard to find vendor-neutral FDEs — they are, after all, there to deeply integrate a particular vendor’s product into a company. In this moment when it’s hard to predict which AI service will be the best one in a year’s time, optionality (the ability to pick whatever vendor turns out to fit best in the future) is very valuable. In contrast, letting FDEs tightly bind a company’s processes significantly reduces optionality. Right now, I see surging demand for AI Engineers who can build software applications using AI software components (like LLM prompting, agentic frameworks, evals, etc.) and effectively use AI coding agents (like Claude Code, Codex, Antigravity CLI, and OpenCode). As the AI Engineer role matures, I expect it to fragment into more specialized roles, like the generic Software Engineer role from decades ago fragmented into frontend, backend, mobile, data engineering, devops, and so on. What will be the future, specialized AI engineering roles? I don’t know. Perhaps there will be AI FDEs, LLMOps Engineers, Evals Engineers, AI Data Engineers, Harness Engineers, and other roles we don’t have names for yet. But for now, I see a lot of AI engineers who are generalists create a lot of value. Skilled AI Engineers are in very high demand! As our field continues to mature over the coming decade, I look forward to new specializations within AI Engineering that create even more job opportunities. [Original text: The Batch newsletter]