James Hull

here's what will really happen.

Rush knows what he’s talking about. I’d love to see thousands of industrial supply chain entrepreneurs stepping up, building all the parts and pieces we need to fully reindustrialize. How can we get them the support they need?

Another week on the road meeting with a couple dozen IT and AI leaders from large enterprises across banking, media, retail, healthcare, consulting, tech, and sports, to discuss agents in the enterprise. Some quick takeaways: * Clear that we’re moving from chat era of AI to agents that use tools, process data, and start to execute real work in the enterprise. Complementing this, enterprises are often evolving from “let a thousand flowers bloom” approach to adoption to targeted automation efforts applied to specific areas of work and workflow. * Change management still will remain one of the biggest topics for enterprises. Most workflows aren’t setup to just drop agents directly in, and enterprises will need a ton of help to drive these efforts (both internally and from partners). One company has a head of AI in every business unit that roles up to a central team, just to keep all the functions coordinated. * Tokenmaxxing! Most companies operate with very strict OpEx budgets get locked in for the year ahead, so they’re going through very real trade-off discussions right now on how to budget for tokens. One company recently had an idea for a “shark tank” style way of pitching for compute budget. Others are trying to figure out how to ration compute to the best use-cases internally through some hierarchy of needs (my words not theirs). * Fixing fragmented and legacy systems remain a huge priority right now. Most enterprises are dealing with decades of either on-prem systems or systems they moved to the cloud but that still haven’t been modernized in any meaningful way. This means agents can’t easily tap into these data sources in a unified way yet, so companies are focused on how they modernize these. * Most companies are *not* talking about replacing jobs due to agents. The major use-cases for agents are things that the company wasn’t able to do before or couldn’t prioritize. Software upgrades, automating back office processes that were constraining other workflows, processing large amounts of documents to get new business or client insights, and so on. More emphasis on ways to make money vs. cut costs. * Headless software dominated my conversations. Enterprises need to be able to ensure all of their software works across any set of agents they choose. They will kick out vendors that don’t make this technically or economically easy. * Clear sense that it can be hard to standardize on anything right now given how fast things are moving. Blessing and a curse of the innovation curve right now - no one wants to get stuck in a paradigm that locks them into the wrong architecture. One other result of this is that companies realize they’re in a multi-agent world, which means that interoperability becomes paramount across systems. * Unanimous sense that everyone is working more than ever before. AI is not causing anyone to do less work right now, and similar to Silicon Valley people feel their teams are the busiest they’ve ever been. One final meta observation not called out explicitly. It seems that despite Silicon Valley’s sense that AI has made hard things easy, the most powerful ways to use agents is more “technical” than prior eras of software. Skills, MCP, CLIs, etc. may be simple concepts for tech, but in the real world these are all esoteric concepts that will require technical people to help bring to life in the enterprise. This both means diffusion will take real work and time, but also everyone’s estimation of engineering jobs is totally off. Engineers may not be “writing” software, but they will certainly be the ones to setup and operate the systems that actually automate most work in the enterprise.

Rush knows what he’s talking about. I’d love to see thousands of industrial supply chain entrepreneurs stepping up, building all the parts and pieces we need to fully reindustrialize. How can we get them the support they need?

New Article, possibly my last for a while. I've spent two years figuring out how to make a two-person law firm compete with teams twenty times its size using AI. This is the closest I'll come to explaining how. Also explains why I can type “plz fix” and get back work product that reads like I spent three hours on it, when really I spent three hundred hours building the system that did.

Today we're launching local scheduled tasks in Claude Code desktop. Create a schedule for tasks that you want to run regularly. They'll run as long as your computer is awake.

It’s been a month since China’s BOBA-POCALYPSE, when Alibaba’s Qwen app turned “buy me a boba” into milk tea appearing on your doorstep. One-sentence ordering plus a promo that dropped drinks as low as RMB 0.01 sent boba shops and delivery platforms into chaos (see video below) and put Qwen top of mind for a lot of consumers. Alibaba says users placed nearly 200 million orders through the one-sentence ordering flow over the holiday. That’s a lot of intent converted into commerce, and it helps explain why Alibaba wants the agent to live somewhere beyond your phone. Next step: wearables. Qwen is expanding into smart glasses (shown at Mobile World Congress, with pre-orders opening March 2), plus earbuds and a ring aimed at global markets. The logic is simple. Wearables are shortcuts. They let Qwen catch you mid-thought and route you straight into Alibaba’s rails: Alipay for payments, Amap for navigation, and Taobao for commerce.