# Building Proactive AI Agent Workforces For Founders

**Podcast:** The Startup Ideas Podcast
**Published:** 2026-08-12

## Transcript

There are people that are spitting up agent workforces with hundreds of agents and sub-agents, and they're getting incredible amounts of work done.
But how do you do it?
And how should you think about it?
And what are the strategies to actually create an AI agent workforce that under-promises and over-delivers?
Well, today I brought on Allie K.
Miller, and she's one of the most well-known AI voices ever.
She's worked with IBM, she's worked with AWS, and she's managed multi-billion dollar P&Ls in the AI space.
I asked her a simple question.
How do you manage your fleet of agents?
In this episode, we cover a lot of ground, but by the end of it, you're going to understand how should you strategically think about spinning up AI agent workforces, where there's opportunities to create startups in the B2B space with AI agents, and a lot more.
Enjoy the episode and I'll see you at the end.
Today's episode is brought to you by Brex.
My company's been on Brex for a year and a half, and I started because I kept hearing companies like Vercel, OpenAI, Anthropic were using Brex, and I figured if they're using it, why shouldn't I?
It's been a game changer.
The thing that got me is how smooth it is.
It's got high limit cards.
It's got banking.
It's got AI that handles the back office busy work like expense reports, which I don't want to do on its own.
It's really just built for this agentic world.
If you're building something new, It's time to get Brex.
Check it out at brex.com slash solutions slash startups.
Link in the description.
I can't tell you how excited I am to finally have Allie Miller on the podcast.
I've been begging her to come on.
She's one of my favorite people in AI and I don't say that lightly.
Welcome to the show, Allie.
Thank you, Greg.
And you are also one of my favorite people.
So I'm actually very excited to talk about all the AI things that we're working on.
By the end of the episode, what are people going to learn?
One of the biggest mindset shifts that I'm going through right now is I feel like the term managing agents is wrong.
And my hope is that people will understand what that mindset shift is, see a few examples and figure out how to start, how to make that mindset shift, what the first step should be.
Okay, perfect.
So where do you want to start?
This is and I'm happy to debate you on this because we haven't chatted about this, but I feel like managing agents feels like I am their direct manager.
And I'm like, Susie, go over there and Betty, go over there and Jeremy, go over here.
And I feel like I am three rungs above at like an SVP overseeing level where I feel like I am setting up the infrastructure and then.
they are figuring out the best way to execute within that.
And so I feel like I'm moving from managing to like waiting for escalations.
Or I feel like I'm moving away from delegating and more just deciding what should or shouldn't happen.
And so it's a little bit more of the like a like a liability role where I just get to be the final say of what happens and come in for like critical thinking steps.
But.
Am I the only one that feels like that is happening?
It feels like that word is wrong.
I see managing agents everywhere and it just feels like anyone that is still talking about, you should manage agents.
It feels like early 2026 talk.
Also, do we want to manage agents is also the question.
Managing people's heart.
A big reason I think a lot of people like AI to do stuff for us is so we don't have to manage things, you know?
So that's something else I've been thinking about.
Like I ran an org of about 100 people at AWS.
The parts of people management that I loved, it was...
The making them better and empowering the shit out of them and seeing them completely blow past their ceiling, watching them get promotions.
Like that was the fun part.
And also seeing what we could do together.
Things like, oh, we have to fill out this thing with the paper and the button and like get me out of there.
So I think the admin side of people management and the admin side of agent management, I want that fully gone.
The things that I love about people, I'm bringing that over into agents, which is just like, how do I act as ambitiously as possible and get you to break through your ceiling?
And one of the best prompts that I have done with my AI workforce is three words.
And with like a little bit of explanation, but like at its core, it is three words that is the best prompt ever.
So I have...
My AI chief of staff is Simon.
Simon runs like this whole org.
And so I have 34 agents that work in this workforce.
And it dawned on me that I was already functioning at the limit of my own imagination in my business and that I could be doing way more ambitious things if only someone could.
manage me, right?
Like could break, help me break through my ceiling.
And obviously I have a lot of mentors and you're amazing at, you know, shaking people up and making me second guess how I'm doing things.
It's really helpful.
But I, it dawned on me.
I was like, why am I not leaning on the AI agents to help me with this?
Like, why is everything that they're working on initially prompted by me?
Even if it's a scheduled task, I still had to come up with that task and tell it to do it.
So the best prompt.
Three words.
And it's just do smart things.
Like my AI workforce has access to every single context doc I've got.
Context docs about my business, my friends, family, my 2026 personal goals, business goals.
It has access to my meeting transcripts, email, calendar, Notion, Stripe, Supabase, GitHub, whatever.
And I just several times a day wanted to look across all those things and just do smart things.
And seeing how Fable 5 and GPT 5.6 and that level model is reacting to that vague flavor of prompt.
Like you couldn't do this a year ago.
Now you absolutely can.
So when you hire a human being, I think there's like three types of employees that you can have.
One is someone who doesn't complete tasks.
Not a good employee if they're not completing tasks.
The second is they're completing the tasks, like satisfactory or exceeding, but they're not really thinking about new tasks.
If you step away from the business, you're probably not going to see insane growth.
And then the best employee that you can possibly hire is...
doing the tasks, exceeding expectations on it, but also thinking about new tasks that they should be doing and actually going and doing those and exceeding expectations or being very satisfactory on that.
So what you're saying is, basically, you're just giving more responsibility to your team of agents.
In a way, because you're giving these three words to it and you're saying, hey, I'm shifting the responsibility of...
do smart things to you.
Like you have to, you have to like, there's a bunch of fog that you have to figure out.
Yes.
I would say I'm giving them more breadth, more scope, more flexibility.
I'm not allowing them to now send a hundred emails.
And before I used to have to check all the emails, I still check all the emails.
So the, the tier of risk has stayed the same, but the width has expanded.
It's.
It's almost like unbelievable that those three words actually make a difference.
Yes.
This is like I and by the way, so so I agree with your assessment on this like tiers of employees.
And Alex Lieberman shared this like pyramid of proactivity that I turned into.
I'll send this to you so that you can pull it up right now as I'm talking about it.
But it is five levels of proactivity.
And at level four.
It's like, I've already solved this thing.
Here are the trade-offs or whatever.
And at level five, it's like, I've already solved this thing.
Here's how I'm going to deal with it if it goes wrong.
Here's the next steps, all the things that you just laid out.
I would say that the difference between someone who's at level three and two in your analogy is someone that understands goals and someone who's been given the power.
to rethink how things get done and the power to actually execute.
And I give my AI workforce goals.
Like those are written out.
And every single quarter, also share with you this tweet that has like the prompt that I think everyone can use.
But every single quarter, I'm going through a goals review with my AI agent workforce so that the goals documents that are living on my desktop and are duplicated in the drive so that all this cloud workflows can actually work.
All of that is so that AI, when it is in that expanded scope world and it's taking on net new tasks, it's doing it in a goal-oriented way.
It's like giving it a product mindset.
I think it would be extremely limiting if you only treated this thing as an engineer when it could be the greatest product lead you've ever had.
I think you tweeted about you're really focused on proactive agents, right?
Is that what you're talking about?
When you talk about proactive agents, is this what you're talking about?
So when you talk to the AI labs, and I know you do, and I know I do, and a bunch of others probably do, but the word of the year feels like it's proactive.
So I don't want to be the first domino anymore.
I don't want to be the bottleneck in my own work.
Any single moment that I realize that I am the limiting factor of helping a billion people transform their lives, work, and business in the AI age, I have to remove myself from the process and go, bad alley.
Like, what are you doing?
And so a lot of that, especially in the kind of tail end of 2025, first half of 2026, was switching into proactive agents.
So we had proactive automations that were trigger based.
I'll give you a really easy example.
Every single time I drop a video recording into our video folder, so basically anytime I do a screen recording, it goes into this one folder and automatically it gets generated, automatically generated is a transcript of that video that gets, you know, then saved into our little transcript-y thing.
Social posts get generated that are in my voice.
So nine different social posts get generated for X and LinkedIn and Instagram Reel scripts and all this stuff.
So that presumably the thing that I was filming, was for a social video.
So that was easy automation land.
But that is just one example of like a proactive, very well-defined workflow.
What I think is more interesting for the back half of 2026 is proactive of undefined workflows.
So like AI is probabilistic all the time and not deterministic.
But I want to take that.
probabilistic nature of reasoning, like the step zero of reasoning, and apply that to the actual tasks that it takes on.
So in order to do that, whether you're talking to a human or an agent, they have to know what's the goal, what's the North Star, what's that vision, they have to have access to tools, permission to use these tools in the way that actually gets work off your plate, and a sense of what would normally trigger that sort of action.
So and I can I'm going to share one thing on screen here, which is every single day.
Let me just give me one second.
So essentially, like I want my whole company to be queryable.
I want AI to have context on everything that's happening.
And it dawned on me that, yes, it had access to all my meeting transcripts and it had access to my Gmail and all this stuff.
there was a lot that was not yet codified.
And it was things like, oh, everything is becoming proactive.
I want to be more proactive.
Or this client, they think that what they need help with is workflows under the CMO, but actually what they have problems with is reskilling and finding new roles for this one department.
So anything that is not codified inside of, again, meetings, emails, whatever, or Slack.
I have asked AI now to prompt me every single day with this.
And, you know, I got to put it in my brand colors and I didn't want to have to think with, you know, maybe 10% of my brain still working at the end of the day.
So I give it like a little prompt.
It reminds me to dictate because that's four times faster than writing.
And so I will bank these entries to be like.
You know, I talked to Greg.
I feel like the entire focus is on proactive agents, proactivity and flexibility.
And I want to look more into his three levels of employees.
And so like I might do this for five minutes or 40 minutes at the end of the day.
I might do it throughout the day and then I just save it out.
And then it's like this goes into my personal wiki.
And all I want to do is.
make sure that the agents that are working at that really flexible layer, where again, I am not managing them, I am enabling them, and they're coming back to me with those escalations and decisions.
I want to make sure that they have the right context or else all their stuff is going to be wrong.
And we saw this in the beginning of our AI workforce stuff.
It was like, oh, I saw that, you know, Greg confirmed that interview.
And it's like, No, Greg confirmed it, but we're still figuring out dates and I'm doing it over text and, you know, iMessage MCP broke since you can't see that.
So there was a lot of stuff that we had to continually fix and it took probably months to get to where we are now.
But we have clawed in every single one of our chat channels.
I had a very weird, I have to send, I have to show you this.
Let me just share my whole screen.
By the way, this, so the brain meets diary thing.
So when you.
When you add today, well, you had like 86 entries, right?
So your AI agents, does your entire AI workforce have access to that?
Or just some, how do you think about that?
Question.
Essentially, my AI workforce right now is one AI chief of staff with six directors.
Those directors are largely over like business functions.
So one is education.
One is all the client work.
One is kind of operations.
One's marketing one product.
And then Phoebe, all these are named after friends characters.
Phoebe is like the chief dreaming officer who's just like being wacky and weird in a corner.
And so she's.
This is let me take another just like moment here.
The reason that it took us months to get to where we are now with our AI workforces is that you have to take stock of what assumptions you have made about your work and how you are living day to day.
And you have to be willing to be like, oh, that thing that I've been doing for almost 40 years, I feel like we should change it.
And that's a really jarring change to work, especially when you've like.
been an overachiever, right?
I'm sure you feel this too.
And so one thing that I am constantly having to remind myself is we have all these agents that do all these tasks and we have skills and we have this and that.
And I have to remind myself that like that is operating in 2015 world if I give all of them job titles that existed in 2015.
So if I name them CMO or chief product officer and the person underneath it is a front-end engineer and a back-end engineer and all that stuff.
then it feels like I'm operating in 2015 org structure.
And one of the most wonderful uses of free will and just delightful things is going, oh my God, all of these employees basically cost zero dollars.
And so at the margin, I can hire any flipping person I want to.
And so I just wanted this weirdo.
So I hired Phoebe as like a weirdo in the corner who's just looking at all these things that we're working on.
And Phoebe acts as this like almost end layer for things that are getting generated to go like, how do we 10X it?
Like I...
I joke, there's this guy, David, that I worked with at Amazon, who was one of the reasons that I joined there.
And he is like one of the most ambitious thinkers I've ever met.
And I joked that I would pay him and I still, it's a joke, but I would pay him to do this.
Like, um, I want, I wanted him to put me in a room like Spanish Inquisition.
inquisition style with like a bright light on my face and to ask me a question.
Like I was running a multi-billion dollar business at Amazon with 400,000 global startups running AI strategy.
And if he asked a question of like, how would you do this?
And I answered, I wanted him to just slap me across the face and be like, how would you 10X that?
And I want a David for how I'm structuring my AI workforce.
I'm now able to do that on my own.
I'm sure David would be disappointed to hear that.
But it's rethinking roles.
It's rethinking how you're spending.
Again, how you're thinking about that margin.
And so Phoebe is one of them that I would have never hired in human world.
And Toby is another.
I'll send you a screenshot of my workforce.
But basically, Phoebe is that chief duty officer and Toby is Simon's assistant, whose only job is watching the AI workforce work.
take down notes, what still has friction, and who needs access to what.
So going back to your point of, hey, I have this AI diary that I'm maintaining.
If we found that one agent did not have access to this, and Toby was like, every single time you keep correcting this one agent's output, have you thought about giving your agent access to this?
Now, This is just context that lives on my desktop.
So any of these agents can really see it.
But if it was a specific tool, if it was a specific folder that is outside of normal cloud land that I try and have hard rules on, then I would absolutely use AI as a means of figuring out those friction points to then expand.
Question on designing your actual workforce.
So I agree, by the way.
you have to think about how do you create an AI native workforce without job titles from pre-AI native land.
So I agree with that.
But tactically, if I'm a founder, it's so much easier to be like, I need a CMO, I need a CPO, I need this.
And I think everyone should start there.
The starting point is, what does it feel like to work with one agent?
After that, I would say, what does it feel like to work with one agent who is doing things on my behalf proactively?
Then I would say, what does it feel like for two agents to work together on a task or for one to direct the other, like one to route to the other?
And then I would say, okay, what does a workforce look like and how do all those things interact?
And I have, you know, like a mission control where I'm seeing how all this stuff is moving around.
And then you go, oh, now I understand how they're trading notes.
Now I understand how context has passed.
Now I understand that things have to run in parallel.
Now I have to understand that this agent actually didn't need access to these tools.
Now I understand that that agent can run off of a smaller model.
Like not everything needs Opus.
All of my sub-agents are like Haiku and Sonnet.
So all of that is in the discovery phase of building out the AI workforce.
I think start with traditional job titles.
No, I was thinking to myself, I wish it wasn't that hard, right?
Because it does feel like there's a ramp up time to actually get to a point where you have an AI workforce that's working for you that is efficient.
And I think a lot of people, what happens is they try, they fail.
And they're like, this isn't for me or the models aren't good enough yet.
Or and you know what I mean?
Yeah.
So here's my take on that.
I think that you can spin up a workforce with one prompt.
Right.
Like I've shared this prompt publicly.
You can just prompt and say, I am a founder.
I am building an AI personal shopper.
My team is three humans.
Here's what we do.
Here's where we're based.
Here's our goal.
Whatever.
You can say that and just say, interview me.
We're going to build out an AI workforce together, something that runs more efficiently and achieves my goals of saving at least five hours a week.
capping my meetings to 15 hours per week and make sure that I get into my capital raise by October, right?
Like you can do that in one prompt and have it interview you and then you have a workforce.
To go from...
ah, yes, all these agents exist and they all have markdown files and they're doing some stuff to, ooh, now it's at the 90% plus level.
And ooh, I needed this extra little context with this diary.
And that role isn't working.
I'm going to switch it.
That is all going to come through iteration because it's so specific to each person.
The advice that I would give is stop relying on only yourself to find these blockers.
AI as a watchdog is one of the best use cases that exists right now.
And almost no one is doing this.
So like having an AI watchdog in Slack to catch for duplicative work or having an AI watchdog on your calendar to see when there are conflicts or an AI watchdog over your meetings just to see where disagreement is happening.
Like 10 years ago, I remember working.
This was at a large scale enterprise, but we were working on like comparing contracts, right?
It was like before the edit, after the edit.
And it was like compare and contrast with AI.
And 10 years ago, that was like the greatest use case ever.
And yet no one today is using AI for this like weird cross-functional gap analysis at a more advanced level than we would have done 10 years ago.
And it's still just like such a meaty use case.
I think Claude Tag is a big help here.
I think it's a mess.
Right now, in this exact moment that we're recording this, I think it's a mess to set CloudTag up, but I'm sure it'll be fixed by the time this comes out.
I've also set up my own Cloud code to come in.
I have a Slack channel that is called Loop Alley.
I'll send you a screenshot of non-private information, but it is called Loop Alley.
My freaking human team can talk to my AI workforce in that Slack channel.
So there is...
No ceiling to this stuff.
Like I'll have a teammate who like if I'm in private emails with someone that the teammate will write into the Slack and go, hey, did did that large financial services client like did they respond to Ali's email?
And my workforce will respond back to that person.
And that person will not have to wait for me for five hours to get back to them.
So.
So that sort of thing, the ratcheting up of how advanced your AI workforce can be, how multiplayer it is, that's going to take time because people are still figuring out best practices now.
Things are not easy to set up right now.
But that baseline of, hey, interview me, I want a workforce, I want something just doing stuff for me at a high enough level, you can set that up and connect into tools in under three hours.
The other thing is because a lot of people are not doing it.
that's the arbitrage opportunity.
Yes.
It's kind of like stick through it, optimize it.
I'm curious actually from your perspective, what opportunities are you seeing that people could be building, making money, that sort of thing?
I'm just curious what comes top of mind.
I think AI workforce, first of all, like of all AI users, if you look at the percentage of people who are paid AI users, and if you look at the percentage of those who are using things like Codex or Cloud Code, it is minuscule.
So already, if you're just trying to be in the top like 1% of AI users and you're using the stuff and you've built out even a basic workforce, you're already top 1%, probably top 0.5%.
Getting it to that advanced level, I think, is absolutely arbitrage because it feels like I'm operating a company of a thousand people and not my small, you know, scrappy gremlin group.
That is still absolutely one.
I think the second that that I would do is that AI is a watchdog over any single thing that I'm normally tracking.
So maybe it's and I don't just mean visibility.
I think dashboards are dumb, but I want visibility with.
anomaly detection or insights or something.
So don't just tell me what my social media following is or views or whatever.
Tell me what are people talking about?
What are people best reacting to?
What is not performing well?
What should I do tomorrow?
Write me a script that helps me for that.
So kind of this AI is a watchdog, but with insights into action, I think is the second.
And the third that very few people are talking about, but it's probably one of the biggest arbitrage opportunities because of how good the models are now is to, instead of building out the thing, build the factory for the thing.
What do you mean by that?
So let's say that you want to build, um, a product.
And we just released, there's something called the AI First Index that I run with all of my Fortune 500 clients, where I interview their executives and I evaluate how AI First they are across like 16 different dimensions and all this stuff.
And we decided through a combination of humans and AI to create a product for the public to be able to benchmark themselves on how AI First they are as individuals and as a company.
In that process, I could have done one of two things.
I could have gone to Cloud Code or Codex or Antigravity or whatever.
I could have gone to any of these and said, hey, I want to build out this thing.
Interview me.
You know, look at my AI first index reports that I've used with previous clients.
Find every single workshop I've ever done with clients where I mentioned the AI first index, whatever.
Do that and build out the product.
And then we iterate for several hours, days, whatever, until something is perfect and we release it.
That is option one.
Option two is realizing that that's probably not going to be the only product you build or will not be the only iteration of that specific product that you build.
And so it's like going one level up in abstraction.
It's like what dev tool companies did for engineering, but you're creating dev tools, that level for yourself.
You're going to like the kernel level for yourself.
And so you're moving down the stack for yourself.
And instead of just building that product.
We instead built out a mini and very beginner software factory where we're building out primitives like obviously we have to deal with login.
Obviously, we have to deal with payments.
Obviously, we have to deal with social sharing.
We have to deal with writing newsletters to promote these things.
And so you end up instead of just building that one product, you go, there is going to be a flywheel that comes out of this.
There's going to be explosive opportunities that comes out of this.
Why not take advantage of that now?
And so it's like a measure twice, cut once kind of thing.
But the measurement is building out that foundational layer so that the next product that you build, the next iteration of the AI first index or whatever you're building out is so much faster, so much better, so much stronger.
And so we're building these like loops, these optimizing loops, again, that aren't super autonomous and are very heavy handed with humans.
But that is the arbitrage opportunity on.
products that are revenue like that's already that product's already profitable and now i have the ability to build endless products that are profitable at faster speeds than i built the first one that's crazy that's absolutely crazy and like no one is talking about this no it's the it's the the dark headless factory headless like ai headless not you know um but that is that's what i want i want that I want to learn through the mess.
Like we had a web hook issue, whatever.
Like I want to learn through that mess and then I want to never make that mistake again.
And so you have to think about how this factory works, not just for product building, but maybe it's for how you want to run your content engine.
Maybe it's how you want to deal with net new leads.
Like think of the factory behind the one singular task instead of the one singular task itself.
That is.
one of the biggest ways to rethink work in the AI age.
What's, uh, what's Ali Miller's current POV on, you know, software, you know, the SAS apocalypse and software, the value going down, down, down, like in a world where everyone could create a software factory.
Also, I just, I like, I wish I had an agent that was yelling at me about my posture.
So like, maybe I'll, I'll create a new one for that as I, um, I think mediocre software is dead in several years.
And the reason that I think it's actually a longer timeline than most people are predicting is because of what I shared about how often people are actually using this stuff.
So you could go into one of the most AI-first...
you know, banks or AI for software companies.
And if you ask them, have you rebuilt DocuSign?
Have you rebuilt parts of Salesforce?
Have you rebuilt all these things knowing that you can?
They would say something like, no, because we're already so bandwidth constrained.
Or no, because we've prioritized this other thing.
As long as we are still bandwidth constrained, and as long as there are still billions of people who have not used these sorts of tools, you're not going to have mass adoption inside of the enterprise of the replacement to SaaS.
Does that make sense?
Like, if it continues to take, I don't know, 100 hours or something to rebuild something at the scale of a CRM, companies that only have people who are sitting there and can work for 100 hours and who know how to do this are going to be able to take advantage of it.
And it's only going to be when that drops down to like, under three hours and is a fun click and drag interface, which I would even argue and say replet lovable or not at that level yet, right, for that complexity of software, you're not going to see a high complexity enterprise grade, highly secure SaaS do that.
Also, people don't want to maintain that software too, right?
Oh my God.
People are willing to pay someone else to maintain software.
Absolutely.
I built an app.
This was a year and a half ago or something.
I built an app that only lives on my desktop that allows me to better manage photo stuff.
And someone yesterday brought this up in a call and I was like, oh my God, I have an app just for this.
And then I opened it and it was aired out.
And I'm like...
I don't want to deal with this right now.
Like this is not at all what I want to do.
So you're totally right.
The maintenance is rough.
I think like Boris kind of describes one of the like future employee types is just like the maintainer.
But I have a really hard time seeing mass SaaSpocalypse until the ease of making prototyping, making customizing and maintaining and securing.
is at like 95% plus.
I mean, even in a world where there's the maintainer, if something breaks and you're an enterprise, you want someone to call.
You want to go into someone's office, right?
Yes.
You also want someone to blame.
You want someone to blame.
That's an important piece.
I think a lot of people are forgetting that like...
the question of is AI going to replace this, this, this, whether it's a task, a job, a company, a product, something.
Often I am asked, the first question I'm asking myself is who's liable now?
Who would be liable in that other world?
And do I think that that trade-off is worth it right now?
Like I work with Fortune 500 CEOs every single day.
No way.
No way.
They want to be able to call because they want someone to unblock.
They want someone to secure.
The other thing is that let's say that, let's just say it's a Salesforce example and that you could build a shitty CRM or a simple CRM or something that's just running on your own.
But Salesforce has relationships with all the AI labs.
They are, you know, getting into early testing.
And so by the time a new model comes out, you are facing it as a day one person.
They're facing it as a day.
30 maybe.
And so you're also going to be on a very big lag.
And so as you're thinking about that cost trade-off, I think in addition to all the things that we just talked about with enterprise-grade security and maintaining, whatever, you just also don't want to experience that lag.
Like we're moving to a world where being fast to the punch and getting a 30-day, 60-day, 100-day leg up on someone is going to be massive for business.
What about for consumers?
So like I get that like an enterprise, you want someone you can...
speak to and you want security.
But for consumer, it's like, for example, your app idea around, let me know when my posture is bad.
I'll even move the camera up.
By the way, I also have horrible posture.
Okay, well then let's build a product.
Yeah, exactly.
Let's say you build a product and I build a product.
Ultimately, may the best product win.
Yeah, hopefully.
Hopefully.
I don't think that's ever been the case, though.
That's right.
I mean, the best songs aren't on the Billboard 100, you know, in the sense of the marketing, the promotion of a piece of IP is really what drives a lot of awareness.
But that's also an arbitrage opportunity.
It's almost kind of exciting that it's not only based on code, or design for who wins it's like kind of nice to know that if you're someone who's really personable that you can get a leg up if you're able to like open doors that other people can't exactly like on the one hand you could say it's not fair because it's so subjective and on the other hand you could be like oh yeah but if i lack that one skill or if i'm not the best in class at that skill and i'm just kind of passing muster on that skill i still have a chance yeah yeah so I agree.
Just to sum this up, when people say software's going to zero, on the enterprise side we both agree some software might go to zero, but you want someone that you can speak to, you want security, you want someone to maintain it.
On the consumer side, it feels like it's sort of shifting from science to art.
And now the people that are going to win are going to be the more creative, maybe the video first people, the people that can like understand how to create Instagram reels that a posture app can go viral and the code is actually going to matter a lot less.
But the amount of opportunity that exists both in enterprise and consumer to me couldn't be higher.
Like I, so I think a lot of people will say the phrase like, look for the bottlenecks and solve the bottlenecks.
And I always kind of disagreed with, or I don't think it's fully complete.
The phrase that I say is like, look for the bottlenecks.
Then evaluate the value of fixing those bottlenecks and then pick the bottleneck that is high value to fix.
And so if right now the bottleneck is not on writing code and the bottleneck is not on coming up with good design, but the bottleneck is getting something from a local HTML file into like an actual iOS app, then that might be where you spend your time.
Or if the bottleneck is that no one's really figured out how to get, you know, stronger word of mouth and referral codes.
And like, that's still kind of messy.
Um, and I, and I know this as a product maker and advisor, whatever, like that is still a messy spot.
So like, maybe if you fix that, your, your, uh, whatever they call it, like the, the covariant, the word of mouth covariant thing, um, um, could be above one.
Like that is what I would be.
spending my time on finding the bottlenecks and finding what is still high value.
I think video creation, no matter how much AI is helping me edit or, you know, edit the script or whatever, it is still a slog to be able to make video.
So that is still a bottleneck and it's very high value.
Um, but you know, people in the B2C space, I'm sure can think of a lot more.
I don't know.
I just think of like certain B2C products that I use and I'm like, why did I pick it?
Um, I use Whisperflow every single day.
I don't like their mobile experience at all, but I still use it because the value is so high.
Have I seen a single video about Whisper?
Did I see a single video before I started using it?
No, I now see them, you know, everywhere.
Could it be subconsciously though?
You like see their brand places?
Like you might be watching, I don't know, you know, Chris Williamson and then they sponsor Chris Williamson.
You kind of just see it, you know?
Yeah.
I think like influencers still have a ton of sway here.
The rise of the B2B influencer, which like, I feel like I was one of the first and it is, it's so amazing to see more people creating business content, but that is still a bottleneck in, in building like B2B trust.
That is a massive bottleneck.
And so finding creators that can help you there.
But I think.
B2C has a ton of opportunity.
I worry if you look at the YC splits right now, when I was working with YC when I was at AWS compared to now, the ratio of B2B versus B2C has skyrocketed.
Like there's just not as many B2C companies in these incubators getting built.
You could either say when they're zigging, I'm zagging and double down and do a B2C thing.
Like there was this woman who created an app.
She's never coded a day in her life.
She created an app that takes a few photos of your face and she takes that and creates a model of your face and gives you like aesthetic photos that are like you in a grainy, rainy day riding a bicycle or whatever.
She had 300,000 users out the gate.
Like there's still a lot of opportunity in B2C, even if.
the big incubators are seeing that activity less.
So maybe that's another opportunity for people to explore.
Well, yeah, and I think we've been talking a lot about agents, and I think there's just an opportunity to create agent-first version of some of our favorite apps.
You just look at a bunch of different B2C apps, just go look at SentryTower.com.
Not affiliated, but you can just see...
what's charting and what are people downloading?
And it's like, okay, in a world where super intelligence is now on tap, how can I make an AI native version of this?
Or undercut from a price perspective or just drive more value.
There's now opportunity to enter some of these markets.
I completely agree with you.
And I think agent first software is absolutely one.
Two things that I actually think are really interesting, or maybe three by the time I get to it, but interesting research avenues to learn more opportunities like the one you just mentioned.
So one, YC posts videos on Instagram for what type of applications they're looking for.
And agent-first software is one of them.
So listening to what YC is asking for, assume that they are already thinking 18 months out.
So that's definitely one.
arbitrage research opportunity.
The second is Matt Van Horn's last 30 days research skill, which is just amazing.
I've like inner, um, I've integrated that with my like Claude wiki.
Love it.
Um, and the third is, wait, can you tell people I've had Matt, I've had Matt on the pod, but just quickly, like, what is it and why, why do you think it's chef's kiss?
So there are a lot of public skills that I think are done by geniuses in their space.
One that was kind of first out the gate or one of the first out the gate that is made by a lovely man named Matt Van Horn is slash last 30 days.
And it's on GitHub.
You can just grab it.
But it is the ability for AI to figure out today's date, scan the news of the last 30 days, but scan it in interesting ways, synthesize it in interesting ways and just fan out.
crazy amounts of agents in parallel to be able to bring it back to you.
So as I'm thinking about, you know, if I'm going into a company and I'm running a workshop for their 200 executives, I don't know about the insurance space as well as I should.
And so like, if I need to quickly get spun up on an industry, I'll use it.
Um, or quickly get spun up on a specific company, I'll use it.
So I use it there, but for this in particular, you could just do slash last 30 days and then say like, Startup ideas that could be built by someone with the following background or the following skills or have the last three jobs of this, this, this.
Like, use it in interesting ways to see how you can carve out a new path that people are not doing.
The third, which I have access to, and I think there are public avenues to get it, is that I might...
Let's say I am at like a CMO summit.
And so every single person in the audience is a CMO.
I can hear the types of questions that they're asking, right?
I can hear the fear zones that they have.
I can hear questions that they used to ask three years ago and are no longer asking today.
And so finding companies, people, influencers, creators, Greggs of the world to like follow.
to hear the inside scoop of what these people are thinking of.
Like, I can tell you that CMOs, all of them are asking about like, how do I get discovered by agents?
How, what does the agent first shopping experience look like?
What does brand consideration in the AI age look like?
You know, all of that is being considered right now by CMOs, but it is often coming from a place of fear that they are worried that their business is going to be depleted, that their pipeline is going to be crushed in two years if they don't figure it out now.
So figuring out paths to find those fear points would probably be the third.
I love it.
Allie, anything else you wanted to cover?
I just want to screen share the insane Claude reaction because this, and this is me also cursing at Claude, but whatever.
So I wrote a not super nice thing about.
Claude in one of our Slack channels.
And this was like late at night.
And I was just like getting it out there so I could talk with my team about it later.
And all of a sudden there was an emoji reaction of a salute.
And I was like, I don't think a single person on my team has ever used a salute.
And I hovered over it and it was Claude.
I was like, what are you doing?
And so I wrote back to it.
Did you just, you know, emoji react?
Like, is that you?
And Claude was like, yep.
That was me.
I'm here.
And I just, if there's one thing that I want people to think about, it is the leaning into the weirdness of what it looks like to have not just an AI workforce, but to have a multiplayer AI workforce that other humans can chime in on and have it be proactive.
Right?
That is absolutely the second thing.
and giving it that flexibility to more roam free.
And the third is what it actually looks like for a teammate or a system to up-level, whether that's in dark factory type space or just answering better questions inside of Slack.
Those are the things that I would be considering.
And don't be scared like me if Claude emoji reacts to a lot of your messages.
Yeah, I mean, it's...
You know what that is like?
It's kind of like, you know, it's a winter day in New York City.
And for some reason, it's like middle of February.
And all of a sudden, it feels like summer.
Like, you know, there's like random hot days.
And you're like, this is amazing.
And you're like 90% excited, but like 10% frightened.
Because you're like, it's not supposed to be so hot now.
Your analogies are always so, you're like a genius with analogies.
Yes.
That's what it's like.
And that's 90% cool, but 10% frightening.
Yes.
Yes.
I'm like, I'm like still going to continue to try and lean into that weirdness and find ways that I can like take that weirdness and use it to my advantage.
Um, but I'm going to keep that fear next to me so that I don't lose my mind.
A hundred percent.
Yeah.
Uh, I hope people enjoyed this episode as much as I did.
Allie, I absolutely love chatting with you.
You're one of my favorite people to talk to.
Please comment on YouTube just to hype Allie up, honestly, and have her hopefully come back on the podcast again.
Allie is a must-follow.
I'll include where you can follow her on her socials, in the show notes, and the description.
Yeah, Greg, thank you so much for having me.
My hope...
is that every single person got the tactical things that they need to just like immediately, immediately take action on this.
If anything was not clear, let me know.
I am going to like jump on and help people.
And Greg, I will absolutely come back.
You are one of my favorite, favorite creators.
You can always call me.
I appreciate it.
Allie, I'll see you next time.
Sounds good.
Bye.