Andrew Winter retweeted
I feel like the awkward Catch22, and really my main gripe, with personal agents right now that's not really talked about is that there’s still not a great way to measure adoption/impact/success, or any other proxy for relative value vs. the competitive set and ‘worthiness of more capital investment’, besides obviously legacy metrics like product engagement and usage.
And so Muse/Instinct/Grokbot/etc. are forced to care about and optimize for me opening the app and sending more messages, to the point where they are sending me constant notifications to get me to keep opening the app.
Replacing my email inbox notifications with agent notifications is a neutral experience at best, and honestly it’s probably worse. Leaving a message unread is cognitively much more draining than leaving an email unread.
But the promise of the personal agent is to make it so I never have to see notifications ever again. The software notification should be a relic of the past.
I simultaneously want to pay $200/month (or much more) for a world-class agent product, and also literally never open the app or interact with the agent at all, basically ever. My agent should be like my tax guy, where once a year I sit down and spend a few hours with it tracking progress, signing documents, setting guardrails, and aligning on priorities for the next year.
The current agent paradigm is basically just all of us subscribing to the same basic Mint plan to manage credit card spend.
Where is the UHNW offering? Who's building the $10k/month agent that I never have to talk to?
I want the full-self driving agent, even if that means there's actually a guy in a room taking the controls at times without me realizing it, as long as I don't have to think about it or open another app.
Andrew Winter retweeted
I think this might be called Wittgenstein's Ladder (but if it's not I am officially petitioning to coin it as Winter's Elevator @johncoogan @tbpn), and it's similar to Ford / Faster Horse, but my version of this is that you originally needed stairs (or a ladder) to get from the 1st Floor of a building to the 2nd Floor, at which point you could build an elevator between floors.
Once you have the elevator though, the stairs become obsolete. We needed the stairs to get to the 2nd Floor so we could make the elevator, but the elevator is not just 'a slightly better version of stairs', or a model improvement that still relies on the same underlying technology. The stairs literally do not matter anymore once you have the elevator.
This is how you should be viewing the software industry today. Most software and most business processes built over the past 50 years relied on a legacy set of stairs, but the AI agents just got off the elevator.
Every business process today was inherently created around the limitations of scarce resources. AI agents get rid of scarcity as a bottleneck.
Vinod Khosla has a great way of framing this - that we’ve built our workflows around the idea that we’ve had to ration the time of our most expensive talent. Every process, and even piece of software, is wired to optimize around this limitation of time and energy.
Now imagine that talent is available 24/7, on demand, and can be deployed in parallel at scale.
If you’re creating a business process, figure out how you would redesign it for a world where you no longer have these traditional bottlenecks. And as a result, it would probably look entirely different.
The best, most comprehensive take on AI I’ve read. After a year of confusion and fear about the future, I finished it feeling like a weight had physically lifted.
It’s long. Make the time.
@vgr is undefeated.
contraptions.venkateshrao.co…
Andrew Winter retweeted
I think this is really spot on and worth reading. Also very similar to how we approach AI Adoption at Won.
A few additional thoughts:
- The legacy 'technical' vs. 'non-technical' gap was never as large as people made it seem. In retrospect, more companies should probably have been investing more in engineering upskilling before AI. @Austen was early to this.
- With AI, the gap is less about technical proficiency and more about 'builders' vs. 'non-builders'. More technical folks are certainly more likely to be builders, but it's a not a direct correlation, and you likely have builders popping up in places you never expected.
- AI as 'The Great Bundler'. We've seen this already across tools, eg just using Claude/ChatGPT (often w/ connectors) instead of opening individual SaaS apps, but I expect we will see this more across human capital too. If you're a builder, past some level of domain proficiency, why would you just be a builder focused on Design, or Finance, or CX? Job titles and scopes are going to evolve rapidly and horizontally.
- Maybe <5% of the workforce dedicated to building (i.e. Engineers) was too low, but it was probably never going to be >10%. Automation tools (Zapier, Make, n8n, etc.) were on a path to bring that number closer to 15-20%, but AI has blown past that and is likely approaching 50%. However, 50% is still not 100%, hence we should still be realistic about what the KPIs for AI adoption might look like.
- From an ROI perspective, AI feels much more reasonable than teaching everyone at the company how to code, but actually once you knew how to write code the cost was basically just the upfront investment. AI is different, and the investment cost (token spend) is recurring. If you're not careful, AI adoption can become a runaway train.
- Just as an observation, defaults and herd behavior are extremely powerful. It feels like upskilling was generally default 'Off' for over a decade. It is now default 'On'. Defaults are also, as they are in this case, never precisely optimal, and they come with tradeoffs.
- Plus a few diagrams I'm riffing on while thinking through this.
Andrew Winter retweeted
The math doesn't math anymore. Ecommerce is a harder game than it's ever been and there's less money for brands than ever.
Brands, Agencies, and Service Providers need to change their models.
Andrew Winter retweeted
Hi, I'm Felix. I'm an eng lead working on Claude. I love watching people take flight and do things they never thought possible.
We often describe that as "being more ambitious" when using AI, which is tricky advice to follow. I wrote a tutorial:
felixrieseberg.com/how-to-be…
Andrew Winter retweeted
The Bar Tab
A few weeks ago I wrote that the music was playing and everyone in venture capital felt obliged to dance.
A few weeks after that I wrote that history doesn't repeat but it rhymes, and walked through the last time a band this loud played a room this full, which was 2000,
A lot of you wrote in to ask what comes next. I didn't know. So I did what any responsible investor does when he doesn't know something: I got a napkin and started doing arithmetic I wasn't qualified to do.
Fair warning. Every time I tried to make the numbers kinder, they got worse. This is a known property of napkins.
Start with the size of the band. Microsoft, Alphabet, Amazon, Meta and Oracle spent about $230 billion on AI capex in 2024, about $400 billion in 2025, and have guided to around $800 billion this year. Goldman has $1.2 trillion next year and $1.4 trillion the year after. Add it up through 2029 and $4 trillion is the floor. Consensus is closer to $5.5 trillion. I'm using $4 trillion because I'm an optimist and because I only had one napkin.
Now, a bar tab is a thing that eventually gets handed to somebody. What does $4 trillion have to earn? Say 12%, which is about what a sane person wants for setting that much money on fire in West Texas. That's $480 billion a year. Call it $500 billion of free cash flow by 2029. Then I remembered a GPU is not a building. Amazon depreciates servers over five years, and Michael Burry thinks that's charitable. If you want 12% on $4 trillion of equipment that'll be scrap before my youngest finishes college, you need about $1.1 trillion a year. I'm going to keep using $500 billion anyway. When the story is bad enough, you don't need to make it worse to get people's attention.
Five hundred billion of free cash flow at a 50% gross margin means $1 trillion of revenue. Somebody has to write checks to the hyperscalers for a trillion dollars a year of AI compute by 2029. Who? Some of it is the hyperscalers buying themselves a round: Meta's capex buys Meta's ads. But the biggest outside checks come from the frontier labs, the handful of companies that train the models the rest of us build on. Full disclosure: Menlo is an investor in this category, so adjust for the fact that I'm a man with a drink in his hand telling you the bar is overpriced. Say the labs are half of it. That's $500 billion of revenue, as a group, by 2029.
Their combined run-rate today is north of $100 billion. Three years ago it was $2 billion. That is the fastest revenue ramp in the history of business, it isn't close, and it still isn't enough. To hit $500 billion the category has to grow fivefold in three years, 70% a year, every year, from a base the size of Coca-Cola. There's no precedent for that. There was also no precedent for the last three years, which is the whole trouble with this moment. The people who've been right so far have been right by ignoring precedent, and a man who got rich ignoring precedent is the last man alive who'll start consulting it.
So there are two forks in the road, and both of them are toll roads.
Fork one: the labs don't get there, and the $4 trillion doesn't earn its keep. People say "debt crisis." Careful. Here's where the rhyme matters. In 2001 the trillion dollars of telecom debt was junk paper issued by CLECs with no revenue, and the bondholders got sixteen cents. Today the four big spenders fund about 70% of their capex out of operating cash flow and carry AA ratings. The debt lives at Oracle, CoreWeave, xAI, Meta's off-balance-sheet vehicles and in about $350 billion of private credit. That's not 2008. It's 2001 with better credit: write-downs, capex cuts, and a few bodies in the second tier. The band doesn't die. It just stops taking requests.
And here's the thing nobody says out loud. About 40% of AI capex is GPUs, and Nvidia's gross margin is 75%. So roughly 30% of the $4 trillion has already been earned. By Nvidia. The return on this capex has, in a sense, already happened. It went to one company in Santa Clara, which is like finding out the band got paid up front and the tab is yours.
Fork two: the labs do get there. Then $500 billion a year has to come from somewhere, because money is not conjured, whatever the deck says, and there are only three somewheres.
It comes out of wages. US compensation of employees is $15.7 trillion. Five hundred billion is 3.2% of it. At $100,000 per fully loaded worker, that's five million jobs, which takes unemployment from 4.3% to about 7%. "Productivity" is what we call this at conferences.
Or it comes from growth. Five hundred billion is 1.6% of US GDP. If AI makes the economy 1.6% bigger than it would otherwise have been, nobody loses, every deck was right, and I owe a great many people an apology, which I'll deliver cheerfully and from a boat. I'd note that AI is already adding about a point and a half to GDP growth, but that's the capex itself, not the output. So far the bar tab is being counted as revenue, which bartenders have been doing since the invention of bartenders.
Or it comes out of someone else's budget. The world spends $1.44 trillion a year on software. Five hundred billion is 35% of every software dollar on earth, so software can't be the whole answer, but it's the first place the labs will look, and the IT services and outsourcing budgets behind it are another $1.7 trillion. In this version the thing that goes to zero isn't the hyperscalers. It's SaaS at ten times revenue. If you're long SaaS at ten times revenue, read that sentence twice.
The honest answer is a blend, and the whole game is which blend, because every blend has a different loser.
In fork one it's the lenders. In the wage version it's people with jobs. In the budget version it's everyone long software. In the growth version nobody loses, which is exactly why I don't trust it. In thirty years I have never seen a version where nobody loses. I have seen a great many decks that promised one.
Reflexivity ends when the story and the cash get too far apart. The story is $4 trillion. The cash is $100 billion, growing faster than anything ever has. That gap closes one of two ways: the cash catches up to the story, or the story comes down to the cash. The music's still playing, the floor's still full, and I'm out there with everybody else, because that's the job. But I've started keeping one eye on the bar. In 2000 the bartender came around in about ninety days. He didn't ask who'd had the most fun. He just asked whose card was open.
Andrew Winter retweeted
I am surprised that people are surprised this is how I prompt Claude.
Talk to Claude the way you would a coworker. There's no secret to prompting. There's no need to be overly scaffolded or prescriptive for most tasks -- give Claude a goal, and it will figure it out.
Back in the Sonnet 3.5 days, your prompt mattered a lot. Nowadays, it's much more important to communicate to the model:
1. What you want it to do
2. How much effort you want it to spend
3. How it should verify that it did the right thing
Andrew Winter retweeted
🚨 The @a16z Consumer AI Top 100 is back - but this time, it's 150!
We added revenue data from @yipitdata to track how consumers are spending not just time, but money, on AI.
The result? A story of heavy concentration among AI's power users. Our takeaways 👇
Andrew Winter retweeted
there’s something quite awkward about all the personal agents in the current hype cycle
muse, grok bot, instinct, dots, and whatever google, anthropic will come up with
none of them is “mine”
i’d be trusting a vendor for some of the most sensitive data about me and bet on them handling it with extreme responsibility. what if they have a data leakage incident? what if they hired a wrong employee? what if they simply break bad?
i’d also be betting on their model. right now i’ve set up a lot of my stuff in grok bot, but what if their model falls behind? what if another model becomes 10x better on pure intelligence? then i’ll either miss out on a better assistant, or have to bite the bullet and do a full migration
i’d also have to bet on their product. they may not build the features i want. they may not allow me to customize enough. and one day my assistant may show me ads
that feels like way too much betting than what i’d be comfortable with, if i truly want literally everything in my life to go through and be taken care of by an assistant
with all that considered, i’m more bullish on open source personal agents that run on people’s own computers. but i think these open source projects have to break out of the assumption that their users are developers and they can just throw a repo at them and ask them to launch a terminal
a well polished, fool proof, community maintained, vendor agnostic, free personal agent that everyone can run by themselves without locking into a SaaS - that’s what i think many people will need
Andrew Winter retweeted
Here's my take on OpenAI dots vs. the other personal agents:
1. These are really two separate races. dots and Grok Bot are going after work tasks. Muse is going after personal tasks. So I don't think dots competes directly with Muse.
2. Dots' biggest advantage is that it lives inside ChatGPT. My onboarding was seamless because everything was already connected. And with my ChatGPT memory and Astra behind it, it answers big questions like "What should I do to grow my business?" better than other agents.
3. I also think of dots as ChatGPT's official chief of staff agent. My favorite way to use it is to call it on a walk, ask "What should I take care of today?", then have it hand work off to my other ChatGPT threads.
4. In contrast, chatting with my dot in the app is a worse experience. Since it's juggling several tasks at once, it's hard to tell which one it's responding to. I prefer Grok Bot (where each bot works on one thing at a time) or talking to my dot in Slack (which has more obvious conversation threading).
5. I'm a broken record about this, but cramming Codex, Work, dots, Spaces, Pages, and more all into ChatGPT is overwhelming. My hunch is everyone at OpenAI is agent-pilled, so it's hard to take a step back and think about how casual users will learn all this stuff. This is the biggest gap imo - OpenAI needs to think a lot harder about onboarding for normal users. My mom will have no idea how to use any of this.
📌 I talk more about all this in my full dots review and tutorial here: youtu.be/z5X1eMU6isI
OpenAI's new always-on agent, dots, is here!
Here's my new video showing you how it works and how it compares to Grok Bot and Muse. I've been testing it for a few days and it:
→ Flagged a five-figure revenue opportunity
→ Got my mobile app ready for launch
→ Made some great memes in Slack
dots' biggest advantage is that it's natively integrated into ChatGPT, but that also comes with some trade-offs.
📌 Watch now: youtu.be/z5X1eMU6isI
Andrew Winter retweeted
It might seem like people in tech and investing have lost their minds. And in some sense that is true. But a lot of the behavior is rational in some sense, even if it’s not “honorable”
Why is it happening now? Yes, some people have AI psychosis. But something deeper is happening
In life, there are two types of games. Single turn and multi turn games. Single turn, or one-shot, games are just what they sound like. One turn and the game is over. No more turns.
Multi turn, or sequential, games have multiple turns. Which means history, reputation, and consequences for your actions have a large impact. You expect to see the players on the board multiple times in the future
Most things in the game of life are multi turn. Careers are long. Investments take time to come to fruition, and you will want to redeploy the capital
But when the stakes get high enough, people start to squint at the board and see that they can end the game in one turn. Or at least they think they can.
I’ve talked a lot about how AI is the big one. So it’s not crazy to me that some people are looking at the board and thinking there might be only one turn left, and they are just going for it.
Andrew Winter retweeted
I did the math. We can increase US GDP by 2.4% if the WiFi worked on United Airlines.
pretty interesting that the category is converging on the same visual grammar almost comically fast too.
you’ve got a blob, a face, some “eyes”, you gotta give it some soft geometry, add in some emotions via animations, & of course a very friendly affect.
every major company is arriving at roughly the same offering:
persistent memory, email/calendar/messages, browser + computer use, background tasks, proactive notifications, voice, app/tool execution, ambient context, & some notion of a personal agent sitting above everything.
remarkable levels of convergence with very little differentiation whatsoever.







































