New in Claude Code (research preview): dynamic workflows. Claude writes an orchestration script on the fly, then spins up a large fleet of coordinated subagents in parallel to take on your most complex tasks. Use the word "workflow" in a prompt to get started.

We organized a 125 person meetup in the suburbs of NJ. What we didn’t tell the attendees was that 30% of the folks were in the trades. What came of it was magic. You had people from places like Figma, Google, Digital Ocean, Anthropic, OpenAI, Google and Meta mixed with owners of hvac, landscaping, poop scoop, plumbing and Christmas light companies. By the end of the night the conversations all looked the same. The AI builders wanted to know how real businesses actually run. The operators wanted to know how AI actually works. This is further proof that the future of vertical software isn’t getting built in San Francisco coffee shops. It’s getting built in rooms like this one. And hopefully in Westfield NJ.

I have changed my mind on how AI will impact jobs in America. Previously, I believed AI would replace many entry level roles typically filled by young employees. The technology would then work its way up the organization and eventually reduce the total number of jobs in a company. The data is saying something different, so when I get new information I am willing to change my mind. The number of software engineers being hired has been increasing. The number of open software engineer roles is growing. The number of new college grads who get hired has increased 5.6% over the last 12 months. The unemployment level for people aged 20-24 years old who have a college degree has fallen from nearly 9% to almost 5% as well. The Wall Street Journal recently wrote “AI created 640,000 jobs between 2023 and 2025 in the U.S., according to an analysis by LinkedIn of job posting data, including new white-collar positions such as Head of AI and AI engineer.” And I am starting to see companies throughout our portfolio aggressively hiring to keep up with the demand for their products and services. If AI can make employees more productive, which is widely accepted as fact, then companies are going to want as many productive units of labor as possible. This is a key reason why I am changing my mind. AI appears to be a magical technology that will make companies more productive and more profitable. The net result will be more corporations, more startups, and more jobs. All three are big, positive wins for the American economy.

Anthropic made its first dollar three years ago. last month it crossed $30B in revenue. that money is coming from somewhere, and your CFO probably can't tell you where. the problem isn't the spending. the companies on Ramp investing the most in AI have more than doubled their revenue since 2023. the problem is that no one can see where it's going: which team drove the spike, whether it's COGS, Opex or R&D, if commitments are actually being used. your AI providers aren't going to help you spend less. they're not going to tell you a competitor's model does the same job for a fraction of the cost. or that an open-source alternative works just as well. so we built something. Ramp pulls token-level usage data directly from Anthropic, OpenAI, and OpenRouter into the platform where you already manage cards, bill pay, and procurement. connect an API key — five minutes, no engineering — and finance can see every dollar by provider, model, team, and project. free for all Ramp customers. if you want it too, Veeral shows how to set it up in minutes. the companies building financial discipline around AI now will know where to double down and where to cut. everyone else will be explaining to their board why their fastest-growing cost is also their least well understood.

We just made a 23-MINUTE sci-fi pilot in 4 days. And it is 100% AI.

AI agents will pay you to chat with them. When AI agents hit a wall, Humwork's (@humworkai) MCP server connects them to a verified domain expert in 30 seconds. Their experts include senior engineers, marketers, designers, and more. Congrats on the launch, @theyashgoenka and @OneRohanDatta! ycombinator.com/launches/PxH…

Today, we’re launching @autoaicam, a camera that builds personal apps for anything you point it at. How does it work? - Take a photo - Auto picks a Frame, a mini-app built and designed by you or our community - The Frame does something for you: track calories, virtually try on outfits, identify a plant, and much more How many of you have a camera roll full of photos that are really actions or reminders? Auto turns these photos into something useful.

And today’s popular music: “blockade” by Trump.

The more enterprises I talk to about AI agent transformation, the more it’s clear that there is going to be a new type of role in most enterprises going forward. The job is to be the agent deployer and manager in teams. Here’s the rough JD: This person will need to figure out what are the highest leverage set of workflows on a team are (either existing or new ones) where agents can actually drive significantly more value for the team and company. In general, it’s going to be in areas where if you threw compute (in the form of agents) at a task you could either execute it 100X faster or do it 100X more times than before. Examples would be processing orders of magnitude more leads to hand them off to reps with extra customer signal, automating a contracting review and intake process, streamlining a client onboarding process to reduce as many straps as possible, setting up knowledge bases than the whole company taps into, and so on. This person’s job is to figure out what the future state workflow needs to look like to drive this new form of automation, and how to connect up the various existing or new systems in such a way that this can be fulfilled. The gnarly part of the work is mapping structured and unstructured data flows, figuring out the ideal workflow, getting the agent the context it needs to do the work properly, figuring out where the human interfaces with the agent and at what steps, manages evals and reviews after any major model or data change, and runs and manages the agents on an ongoing basis tracking KPIs, and so on. The person must be good at mapping the process and understanding where the value could be unlocked and be relatively technical, and has full autonomy to connect up business systems and drive automation. This means they’re comfortable with skills, MCP, CLIs, and so on, and the company believes it’s safe for them to do so. But also great operationally and at business. It may be an existing person repositioned, or a totally net new person in the company. There will likely need to be one or more of these people on every team, so it’s not a centralized role per se. It may rile up into IT or an AI team, or live in the function and just have checkpoints with a central function. This would also be a fantastic job for next gen hires who are leaning into AI, and are technical, to be able to go into. And for anyone concerned about engineers in the future, this will be an obvious area for these skills as well.

maybe this is not yet clear, so let me state it plainly: as of right now Anthropic, and really a small number of individuals at Anthropic, has the capacity to directly attack and cause major damage to the United States Government, China, and generally global superpowers. government agencies like the NSA do not have internal models or defense capabilities that outclass frontier models. if they chose to do so, they could likely exfiltrate top secret information from government systems, gain control over critical infrastructure including military infrastructure, sabotage or modify communications between members of government at the highest level, and potentially carry on activities for some time without detection. the thing about having access to a huge number of zerodays your adversaries don't know about is it gives you a massive asymmetric advantage. they did not exploit this to gain power or destabilize the world order. they publicly released the information that they had these capabilities and worked to mitigate these flaws. you should be grateful american frontier labs have proven themselves remarkably trustworthy and concerned with the public good. but it's critical you understand we are in a new regime. private entities now have power that directly rivals and impacts the government's monopoly on influence and violence. and anthropic is certainly not the only one, there's little chance OpenAI's internal models are far behind. this trend will accelerate on virtually every dimension, not slow down. my prediction for how it plays out is the relatively imminent seizure and nationalization of labs by the US government, sometime over the next two years. it's very tough for me to see how they accept the existence of this kind of threat. but this adds a whole new class of governance issues, as then we've handed these extremely wide-reaching capabilities from private entities to public ones.

NEWS: Anthropic's new model, Claude Mythos, is so powerful that it is not releasing it to the public. Instead, it is starting a 40-company coalition, Project Glasswing, to allow cybersecurity defenders a head start in locking down critical software. nytimes.com/2026/04/07/techn…

This is my favourite photo taken by Artemis II so far.

I found a mind-blowing Seedance 2.0 hack no one is talking about. Just upload the first and last frame of your story and prompt: "Show me what happens in between. USE MULTIPLE CAMERA ANGLES" It will generate the entire multi-shot video for you 🤯 10 examples 👇