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Dear subscribers,
I’ve started to get a surprising amount of work done by talking to AI while walking outside. I believe that:
We’re moving from manually using a keyboard, mouse, and laptop to directing agents in the cloud using voice.
In this post, I’ll cover five shifts that can help you get ahead of this change:
Voice will become the orchestration layer
Personal computers will move to the cloud
Products will be built for agents first
Most software will become commoditized
Trust will determine the winners and losers
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I’ve been using tools like Wispr Flow to dictate instructions to AI for the past year. Recently, ChatGPT Voice has taken this to the next level by making voice the orchestration layer for everything I do on a computer.
While out on a walk or in bed, I’ll turn on ChatGPT Voice and just start rambling:
“Use my chief of staff thread, check any open email loops I should respond to.”
“List the top 5 PRs for (project), let’s work through them one by one.”
“I just interviewed (guest), run the /podcast-production skill in a new thread.”
ChatGPT Voice will provide instructions to all these different threads and report back when each task is done. It honestly feels magical compared to tracking everything myself with a keyboard and mouse.
Recently, I taught my 8-year-old how to use ChatGPT. She doesn’t even know how to type but is already building games with AI just by talking to it.
For her and the generation that’ll grow up with AI, voice is already the default interface.
You’ve probably seen the meme of people walking around with their laptop lid half open to keep their agents running.
I think this ritual will come to an end soon because what I really want is a persistent personal computer that lives in the cloud:
An early version of this is running OpenClaw or Hermes on an always-on Mac mini. The latest version is Grok Bot, which comes closest to giving agents their own persistent cloud computer that has files, a browser, and more:
I’m sure both ChatGPT and Claude are working on a similar solution.
Your laptop’s specs will matter less when your real computer is in the cloud.
Take OpenAI’s rumored hardware device. It’s a hockey-puck-sized smart speaker that doesn’t have a screen. Soon we’ll all just be talking to agents that live in our cloud computers to get them to do work.
I’ve been trying to scratch my builder itch ever since I left my PM job. Recently, I shipped two free, open-source tools that people loved:
(4,400+ GitHub stars) gives agents instructions for removing AI slop from writing.No AI Slop(570+ GitHub stars) lets people edit HTML and Markdown files and send feedback to agents, just like a Google Doc.Human Review
I think people like these products because I built them for agents first:
**Both work inside your favorite AI harness.**I don’t want to use another app or website — I want tools that work with ChatGPT.**The agent is the primary user.**For example, Human Review sends feedback to the agent to make fixes.
My point is that many productivity products will look more like skills and tools for agents to use instead of websites and apps that people visit.
I laugh when I see taglines like “Anyone can build an app now!” The truth is:
Software has become easier to build but much harder to monetize.
Consider the following:
𝕏Pieter Levelsrecently shared that he’s seeing declining traffic and revenue across indie SaaS products, including some of his own:
Traditional SaaS companies are also facing pressure.
Airtable sold for $1.29Bafter once being valued at $11B, and𝕏Canva cut its revenue forecast by 20%.
Many SaaS tools are becoming harder to justify paying for when people can just build the same thing inside ChatGPT or Claude. I recently interviewed Amol Jain (Head of Core Engineering at Replit) and asked him this spicy question:
“What vibe-coded apps actually make money?”
He walked me through two examples:
($100K+ ARR) connects local businesses with creators for marketing.TryNearby($180K in 6 weeks) helps companies assess, train, and certify employees’ AI proficiency.GenAIPI
Notice that neither company sells software by itself. TryNearby has a local creator network, while GenAIPI combines AI training with a trusted credential. The software makes both services easier to deliver, but it isn’t the scarce part.
Software without a real advantage, like proprietary data, distribution, or services, will become a commodity.
I’ve been staying in Vancouver, and most of my friends and family here still use vanilla ChatGPT for Q&A. When I ask them why, they say: “I don’t trust AI enough to give it access to my email, calendar, and other apps.”
I believe that trust is the biggest barrier to broad agent adoption.
Cloud computers will only make the trust hurdle even higher. While testing Grok Bot, I came across this screen on its cloud computer:
If this were on my laptop, I’d probably be comfortable entering my password. But because it’s on a cloud computer, I hesitated. Before proceeding, I’d want to know what the computer remembers, who can access it, and how I can revoke access.
The winning products will make trust and transparency first-class product features.
To recap, I think we’ll rapidly transition from using keyboards, mice, and laptops to directing agents in the cloud using our voice. If you want to get a head start:
UseTalk to it and give it instructions like “Spin up a chief of staff thread to look for emails to respond to.”ChatGPT Voiceto orchestrate your other threads.TryConnect it to a few of your favorite apps to see how a persistent cloud computer works.Grok Botto experience cloud agents.**Vibe code products for agents first.**Instead of vibe coding another standalone app for humans, build a tool that agents can use. Here’s myGitHubfor inspiration.
Personally, I think monitoring agents on my laptop all day is incredibly draining.
I much prefer to close my laptop lid, go outside, and talk to agents to get work done. If you haven’t tried this yet, you really should.
