AI Boosts Output, Sparks New Human‑Centric Job Bottlenecks
Why will AI create more jobs in plenty of industries? It’s because we’re going to use AI to accelerate output in one area, and then eventually you run into a new bottleneck somewhere else in the process that still requires humans. This example from the FT is an obvious one. More people asking legal questions from AI agents, which downstream eventually will mean there are more lawyers being pinged with questions. There are other drivers, too, like AI accelerating new business formation, more patent filings, new scientific research, and so on - all of which eventually land in the laps of lawyers and other regulatory functions. But the analogy holds for plenty of other work. More code will mean more security risks, which means more security researchers. Automating patient referrals in healthcare just leads to a bottleneck of not having enough doctors. More customer outreach via AI leads to more sales conversations. You can list thousands of categories like this. There’s a lot of areas where AI will lead to “efficiency” in the sense that we will automate something and then spend less in that area. But the value proposition taps out at some point because the world isn’t static. Your competitor will use AI to build a better product, go out and meet with even more customers, deliver a better service, run better ad campaigns, and you eventually have to match them or die.
Enterprises Need Dedicated AI Agent Deployers
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...
AI Boosts Security Demand, Not Replaces Talent
Security another great example of a job category that is about to have its Jevons paradox moment as well. “And counterintuitively, I think better AI tooling for security will increase the demand for security talent, not decrease it. Autonomous exploitability...
AI Token Demand Set to Explode, Driving Datacenter Surge
This chart puts the datacenter demands into perspective very clearly. Amazon has done more capex in the last 3 years than its entire history. Right now most AI adoption is on chat tools that are relatively token efficient. Comparatively, coding...
AI Boosts Lawyer Demand, Not Reduces It
We will likely have more lawyers in the future than today, because: 1) AI will cause so many more people to ask legal questions which will encourage them to need to verify or execute through an actual lawyer. 2) AI will...
Prompting Is Essential: Give AI Clear Instructions
The idea that prompting would be useless is like if giving clear instructions to a brand new colleague who just joined your team is useless. “Prompting” should just encapsulate the entirely of giving the agent everything it needs to perform...
Background Agents Will Power Nonstop Workflow Automation
Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or...
Automate Document Workflows in Minutes with Claude Agents
Background agents for knowledge work are here. You can use the Box API or MCP to automate any content workflow with Box + Claude Managed Agents. In 2 minutes you can be automating document review processes, data extraction, or connecting...
Model Capabilities Are Soaring—Prepare Your AI Strategy Now
Mythos from Anthropic is another clear reminder that there’s absolutely no wall in model capability progress right now. Meaningful double digit gains on critical benchmarks, and it appears we’re going to keep up getting insane gains from the other labs. And...
AI Agents Shift Work to Higher‑level Management
When you have agents going out and doing work for you, the work just moved up a layer of abstraction. Now the work is figuring out what to tell the agent to do, ensuring you give it proper instructions, getting needed...
AI Expands Demand for Engineers, Security, and Automation Roles
There are far more categories where AI agents making things more efficient will induce demand for that skill than spaces where agents eliminate the work. This is why the AI jobs predictions will not play out as advertised. AI making...
Context Layer Essential for Enterprise AI Amid Knowledge Gaps
One of the core things we’re going to have to contend with in AI is that even the most advanced models in the word can’t have all the relevant knowledge needed to be useful, because everyone has different use-cases and...
Larger Context Windows Enable Human‑like AI Agent Design
As AI models get better at handling tools, and as context windows get bigger without as much rot, you can start to design agents more similar to how people work instead of having to mitigate the model limitations with weird...
Human Cognitive Limits Drive Management; AI Can Break Them
“There is a limit on human cognition. Even if you're not reviewing everything they're doing, how much you can hold in your head at one time.” There’s a reason that at a certain scale, teams of people have a manager, and...
Ruthlessly Shed Legacy Scaffolding to Unlock AI Agent Gains
One of the biggest lessons thus far in building AI agents is you have to be brutally unsentimental in your architecture. The models get better and better at handling things you previously built scaffolding for, you need to ruthlessly jettison...