Dan Grover

This has been on my mind for a while now so I'm going to rant on product design for a sec: what @AnthropicAI needs, most of all, is a Cowork onboarding process. We have an intelligent, natural-language assistant as the core product and we’re still using tooltips and popups to explain how the app works? Please. Be serious. When you first download Cowork you should be presented with a blank canvas and just the words “Hello”. Big letters. Whole screen. Greetings from the latent space. After a second, a bar appears for you to type a response (though you are strongly encouraged to use voice). Claude then explains that it will be your virtual coworker, secretary, and thought partner. Its job is to make your life easier, automating the stuff you like the least to give you more time to do the high impact work. Introduce Claude's personality. Claude then warns that in order to get this right, it will need to conduct 1-2 hours of deep, back-and-forth interviewing with you so it can best understand your job, your tools, your organization, and your goals. Don’t have time right now for that? Okay, let’s book time on your calendar. I can send you an invite! Better yet, connect me to your email/calendar system right now so I can create the event directly. I’ll walk you through how to do that. When you do find time, Claude interviews you in great detail, following a pre-built guide (perhaps with branching flows depending on the job function). What is your job? What are your responsibilities? How do you work? What projects are you currently working on?What are your biggest pain points? Where can Claude provide the most leverage? Claude then recommends integrations, plugins, and skills, and walks you through the set up of each one. Next, Claude also makes a Growth Plan: a list of skills that it should build/customize with you in the future to distill your particular ways of working and habits. I honestly wouldn't even start with the default skills. They're generic and long, and frankly, I don't want Claude following directions that I haven't read or discussed. Maybe use them to demonstrate an example if the user asks, but otherwise it's unnecessary overhead. The only exception is for guardrail instructions (i.e., "don't use placeholder values for sensitivity tables"). Those can be imported. Then, when you ask Claude to do a task that is related to a skill on the Growth Plan, it flags this, and asks for coaching on how you want it to perform this task. This becomes it's own interview flow where Claude asks some basic questions, asks for and helps find examples, and workshops the approach. The final output is a customized, personalized skill. These interview flows are then the sorts of thing the Cowork team should ship in the backend. So instead of a generic financial analysis skill, it's a "financial analysis skill-building interview guide" detailing what Claude needs to ask the user about in order to build a robust, personalized financial modeling skill (e.g., "ask what sort of cell and number formats they use"). Finally, only after you've agreed on the Growth Plan (which is just a cross-session list of action items, not the final custom skills themselves), Claude then suggests one activity to work on to get started. And boom, you're off to the races. Claude should also schedule weekly feedback reviews on your calendar where the two of you assess what it did for you this week, where it performed poorly, where it can actually do more than what you're asking it to do right now, and how to improve generally. The team already announced some of this today (plugin/skill customization, etc.), but imo it really needs to be a cohesive, E2E, multi-session, iterative flow. The user shouldn't have to navigate lists of plugins and skills to get the most out of the robot; the robot should help the user customize itself.

Investors are betting billions of dollars that robotics will experience a Giant Leap. Meaning: robots are not useful today, but throw enough GPUs, models, data, and PhDs at the problem, and you’ll cross some threshold on the other side of which you will meet robots that can walk into any room and do whatever they’re told. The Giant Leap view is sexy. It holds the promise of a totally unbounded market – labor today is a ~$25 trillion market, constrained by the cost and unreliability of humans; if robots become cheap, general, and autonomous, the argument goes that you get Jevons Paradox for labor - available to whichever team of geniuses in a garage produces the big breakthrough first. This is the type of innovation that Silicon Valley loves. Brilliant minds love opportunities where success is just a brilliant idea away. My friend @evanbeard is betting that progress will happen by climbing the gradient of variability. That robotics will progress towards general usefulness in small steps. The logic is clear: - Robotics is bottlenecked on data. - The best data is the data your robots collect actually doing things. - The best strategy, then, even if it's not the sexiest, is to get paid to collect that data, learn, and iterate. This is where the vast majority of value lies, and the real path to our abundant robotic future. For the first co-written essay in not boring world, Evan and I write about the robots.