Nate’s Substack
Artikelen over Nate’s Substack
Executive Briefing: The 5 Skills That Help One Person on Your Team Carry More of the Work
Going beyond the video: how taste, agency, focus, resourcefulness, and follow-through develop together, through work that changes your understanding of what you can take on.
Google bid $10 million for an airline’s old work emails to train AI. Much of what made that work matter never showed up in an email
Google wants to learn from the record of our working lives. We should take a closer look ourselves, because understanding what our work accomplishes could change what we attempt next.
Your customers won’t ask for Gemini 4 Argon. Their best AI product idea probably isn’t in their feature requests either. Four questions surface the work they gave up on
Google’s new Gemini 4 Argon model has impressive benchmark results. Google says it leads the Vals Index, which evaluates professional work across several fields. The initial rollout is limited to trusted cybersecurity defenders, with broader access planned. Google has described internal uses and early customer work, but most of us still can’t use it ourselves.
Executive Briefing: Before You Renew Software, Ask Your AI Power Users 4 Questions
The people using AI on your team are already making decisions about the future of your software. They are choosing which data matters, which application steps they can skip, which workflows they still trust, and which agent does the work. A surprising amount of your software strategy may already exist in those choices. Your leadership team has to go and learn it.
Hitting your ChatGPT limit? Try Sol before paying $300 more
Used together, Dots, Space, and Sol turn the context you've built with AI into a shared workspace. The questions to ask are what can it take on and what does that work cost?
Only Allowed Copilot? 5 Habits I’d Build That Carry to the Next Model
Your company may have already decided where you can put its information. You might have a strong opinion about which model is smartest. I see it in company after company: Microsoft is what the employer trusts.
Does your work cost less on Opus 5.5 now that its tokens are 20% cheaper? My 3-prompt guide shows which jobs do before you move them
With Opus 5.5, I can give the model direction, make a correction, and keep developing the thing I wanted. That sounds ordinary until you’ve spent a session explaining the same requirement repeatedly and wondering why a system this capable is so difficult to work with.
What are you still paying for that you meant to cancel? I handed mine to an AI assistant: $1,285 a year cancelled so far. The prompt guide for the tedious part of yours
I’ll bet you’re still paying for something because canceling it has never made it to the top of your day. Getting into the account, figuring out the rules, and dealing with whatever happens next keeps losing to work, dinner, or a child who needs something.
Executive Briefing: You Bought Better Tools and Your Finished Work Still Waits
AI is making some people dramatically more productive. Getting that speed through the rest of the organization is a separate problem, and it isn’t solved by making the fast people teach everyone else.
Inside NVIDIA: What a world model actually is, and how it connects to the LLM you already use
NVIDIA builds tools for developers. That is the place to start if you want to understand why a company most people associate with chips is building models that can help simulate a factory, predict what happens when a robot moves, or generate actions for a machine. I went to NVIDIA last week to talk with Ming-Yu Liu, the vice president of Cosmos Lab. Cosmos is NVIDIA’s world-model effort. Early in our conversation, Ming-Yu explained the relationship between NVIDIA’s computers and everything the company builds around them.
Your agent is giving you reasonable answers from half your context. A conversation with OpenAI
How do you turn individual AI ability into a team that learns faster, makes better decisions, and gives people some of their lives back? Last week, I went to OpenAI to ask.
You cannot tell which parts of your software should stop calling an LLM. My Jev guide has a prompt that scans your projects and names them
Software is about to get intelligent in very different places.
Executive Briefing: Where Your AI Money Actually Goes (+ the Token Saver Guide and the 15 Changes I Use)
At Dreamforce, Salesforce’s Rohan Kumar told me about a customer who had challenged him on something a lot of people are feeling. The customer had been hearing that AI was going to change everything. Meanwhile the products looked much the same. How were those two things supposed to fit together?
Can agents buy from your product? Three questions that tell you. Plus: Nate’s Library MCP
Some of the decisions that determine whether agents can use your product are being made as fraud decisions, pricing decisions, and onboarding decisions. They may never show up in a meeting about AI strategy.
In 1997 nobody could tell you why you’d want a gigabit connection. AI is in 1997
Apple shipped a lot on September 9. A $1,999 folding phone. Two watches. A health app that wants to read your bloodwork. The thing worth your attention, though, is an argument that was everywhere within about six hours of the keynote.
Executive Briefing: A Thousand Students Show What Happens When You Take the AI Away
Almost every decision being made about AI right now assumes someone is going to win. That assumption shapes what gets built and what gets restricted -- and I think it’s wrong.