Silicon Valley Girl: AI, Tech and Career Growth - Grammarly CEO: AI Moved the Career Ladder (Most People Don't See It Yet) | Shishir Mehrotra
Episode Date: September 8, 2026Shishir Mehrotra ran product for YouTube, founded Coda, and has sat on Spotify's board for over a decade. He now runs Superhuman, the company behind Grammarly, which 40 million people use every da...y.In this episode, he reverses the career advice he gave for twenty years — stop trying to be a great executor, start learning to manage. He explains why the best jobs never come through the recruiting funnel, walks through the framework he built at Google for how promotions actually work, and points to the moment mid-career where the rules quietly change and most people panic. He pushes back on the word "replaced," gives away the interview question he used for hundreds of hires until he talked about it publicly too much, and shares what Bill Campbell told him in 2000 that changed how he measures his own success.📩 7 skills that get you promoted —https://siliconvalleygirl.beehiiv.com/p/7-skills-that-make-you-irreplaceable-adc6?utm_source=spotify&utm_medium=description&utm_campaign=futureproof-sub&utm_content=7-skills 𝕏 : https://x.com/siliconvalleymm🔗 Instagram: https://www.instagram.com/siliconvalleygirl/💼 LinkedIn: https://www.linkedin.com/in/marinamogilko📌 My Companies & Products: https://Marinamogilko.co
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You learn to be a manager.
I spent years giving people the opposite advice.
What would you say to people whose job is already automated?
This is Shashir.
He spent 20 years deciding who gets promoted.
He ran product for YouTube.
He sits on the board of Spotify,
and now he runs the company behind Grammarly.
40 million people use it every day.
You think about a world with AI everywhere, what happens?
It actually pushes that entire ladder up.
The original skill didn't go away.
It just shifted.
The job you're doing today and the job you get promoted for,
aren't the same anymore.
Since it's become my number one indicator of someone I want to work with, someone I want to
hire is how good are you at all?
You represent someone who has been in multiple careers.
So you worked at YouTube, you worked at Spotify, you started your own company.
Now you're the CEO of Superhuman, which also incorporates grammarly and helps humans become
superhumans.
So if you had to start your career from scratch today, what would you do?
in the next 12 months to stand out on the market.
I'll give a couple pieces of advice.
I think one thing that people often don't think about is how to stay out of the recruiting
folder.
What I mean by that is the most interesting jobs.
In fact, all my transitions for the most part have happened through an interaction where we
weren't talking about recruiting.
We weren't going through a job conversation.
And so I think a lot of people focus on how do I interview well and how do I get through
the screening and so on. But actually, the most interesting candidates I've ever hired or places
I've jumped in usually happened through some interaction that didn't start with a, I'd like a job
or would you take this job? So for that, I think it's be interesting in the world, start projects
that people might see, write things that people might see. Not only is it easy to produce those
things, the outlets for being able to spread them are so wide. I think that's really important.
I mean, the way I ended up at, I've been on the board of Spotify for over decade now,
and it started with the paper I wrote.
You know, Daniel was interested in it and we started talking about it.
And then it led to, hey, would you do more of the company?
On social media?
Actually, it wasn't even shared.
In this case, it was passed around through different people.
It's called Formits of Bundling.
It's how to think about bundles.
Somebody sent them the idea and said, you should talk to share about it.
And we ended up chatting about it.
So I think the main advice I give people that in a world full of candidates,
trying to find spots.
You had to find your way to stand out.
and the best thing to do is actually avoid recruiting.
That's not the funnel you want to be in.
Everybody has a, you know, in your email, you got your, you know, we use superhuman.
So we have our splits.
And, you know, I have my one for recruiting.
And it's a lot of people looking for jobs.
And, you know, those all go right through my recruiting team.
Then there's other ones that are interesting people I want to have a conversation with.
Huh.
And that's the pile you want to be in.
I like how you visually presented it to me right now.
Because once you're flying for a job, you're,
ending up in a folder that's full of other candidates. I mean, I have, I have an auto split for
it. Superhuman allows you to write AI-based prompts for auto-organizing your emails. And so the,
I have one that explicitly takes everybody looking for a job and puts them in a corner. And I go through
them and I read them. But, you know, all I'm doing is directing where, where they, where they might go.
I'm not really thinking, is this an interesting person that I want to come spend time with and learn
something? And then unexpectedly, it might lead to lead to an interesting opportunity. The second thing I'd say is,
I think it's a fairly generic advice that everybody should learn every AI tool that you possibly can.
I think the more interesting advice is you learn to be a manager.
This is tricky because I spent years giving people the opposite advice, learn to be a proficient executor.
The best managers we hire are ones that can do the job themselves and kind of work their way, work their way into management.
And I think the world is reversing a little bit.
And the skill of the how do you write code or how do you write the specific blog post and so on,
It's very important still, but as we use AI tools, we're put in a position of feeling like
managers. And I think that's a, it's a different skill. How do you learn it when, in my opinion,
becoming a manager and I've learned this through practice, right? I started by myself. I did,
I did a lot of manual things by myself. I learned what's good, what's bad, and then I hired. So this
is how I transitioned into becoming a manager. What would you say to people whose job is already,
like manual job is already automated. How do you even learn what's good or bad?
To be honest, that's what we're hiring. Right. So we're hiring judgment. I think it's really important
that every skill that you learn takes practice. And you have to put yourself in a position to
practice. I also think every skill you learn is best learned in low-stakes scenarios. So one of the
things I have a framework for something we call eigen questions, which is the art of asking the right
question, which is very related to what being a manager feels like. I also, I also,
also I wrote a post about it and a huge section of the post was how do you learn to do this.
And one of the things that I think people miss in learning is they try to apply it in the highest stakes situation they can.
And if you think about other things you learn in life, you learn an instrument, you learn to play a sport.
Imagine if the only way to learn was to do it, you could only learn a sport and you could only play in broadcast games.
Or you're trying to learn an instrument and every single practice was actually a recital.
And everybody was watching and the stakes were super high.
It wouldn't make any sense.
You got to, you know, you got to come down in your basement and play your guitar.
You got to get out on the driveway and shoot some hoops.
Like that's how you, that's how you learn.
And so I think what I advise people is if you're trying to learn the skill,
if you're trying to be good at how to do AI Center Design, for example,
do it in a side project.
Do it in something that's very low stakes.
Do it with a friend.
Do it in a thing that you can repeat over and over again and get very quick feedback loops on.
Because then you'll get good at it before to,
that high-stakes situation. And I think it's not easy to do because you have to force yourself to,
you know, the equivalent to get out on the driveway and shoot hoops is different in every job.
But it's become easier now than ever before. As you're learning your skills, find your way to
practice, find your partners to practice with and do it, do it in a lower-stakes situation.
So basically work on a project by yourself and then when you're applying for a job,
you have something that you can show. It might not be by yourself, but don't do it. You don't have
to do it in the main work scenario. It's particularly true of skills that are creative, that are judgment,
that are, you know, how do you learn that form of judgment?
Well, it's hard when you're in the job.
You're in the recital.
Every meeting has lots of people in it.
And you're the one that's trying to learn.
And so for you to be vulnerable and say, well, I thought that was pretty good is, you know,
you're going to get judged.
And so you want to find lower stakes places to do it.
So when this happens, when somebody who comes to your company has already some management skills,
has some experience starting a side project.
What happens to career ladder?
When you came in, no experience, did manual things, then you got promoted.
Do you think it's getting erased?
No, actually, I think, so let me tell you about my view on career ladders.
I have a framework I use for this.
It's called PSHE, problem, solution, how execution.
So you start off as, in this case, I'll say product manager, and I'll describe the others
in a minute.
You start at the bottom.
We hand you a problem.
We hand you a solution.
We hand you the how.
We tell you, you should go talk to this team, you should write this document, so on.
And all you have to do is execute.
You just have to do that task.
At some point, we hand you a problem, we hand you a solution, you figure out the how to organize the team.
You figure out how to do the milestones.
You figure out the cadence.
At some point, we hand you a problem and you come back with creative solutions.
You know, and ideally solutions that nobody thought of, solutions that are really solved the problem beyond what people expected.
And at the very top of this, we hand you a space and you tell us the problems.
I know you told me to go work on activation, but actually our biggest problem is brand.
Or I know you told me to go work on sales, but our biggest problem is marketing.
That latter, PSHE, is a very different axis than scope.
And one of the leaders is the woman who's running infrastructure for Google.
She went and very mathematically took her whole team and put them on both axes.
What came back was really interesting.
It came back as an S curve.
So what she said is early in people's careers, they mostly moved on the scope axis.
You're mostly working at that E level, you know, the execution level.
And we're just giving you bigger and bigger projects.
Later in your career that happens again.
You're at that P level.
and we're handing you spaces and you're working on bigger and bigger projects.
But in the middle, it reverses.
And so it looks like an S.
And she drew a big circle around it.
And she called it the trough of disillusionment.
He said, this is the moment where everybody freaks out.
Employees look and say, I thought you told me the game was scope.
And now it's not scope anymore.
And managers and promotion committees look.
And they say, well, these two people actually the same scope, but what matters now is how they do the job.
You can use the exact same technique for engineers, for designers, actually for salespeople,
marketers, so on.
It changes your value system.
It says, what are we actually valuing with our more senior employees?
What is the ladder guide about?
It's about identifying the right problem, about finding the best solutions, about figuring out
how to take that and deliver it and then how to execute.
You think about a world with AI everywhere, what happens?
It actually pushes that entire ladder up.
Okay.
When I sell my business, I want the best tax and investment advice.
I want to help my kids.
and I want to give back to the community.
Ooh, then it's the vacation of a lifetime.
I wonder if my out of office has a forever setting.
An IG Private Wealth Advisor creates the clarity you need
with plans that harmonize your business, your family, and your dreams.
Get financial advice that puts you at the center.
Find your advisor at IGPrivatewealth.com.
Yeah, it seems like the problem and solution
can now partially be handled by AI.
But at least that's what I'm seeing in my company.
Actually, I would say executing, if you can define a problem and if you're good enough to find the right frame for the solution, then sometimes, and if you can figure out how you're going to get to market, AI can help you execute it.
Sometimes AI can help you one level up and say, all right, I understand you can build this.
Can you help me understand how to get everybody on board?
Can you help me understand how to test the market?
Sometimes it can invent solutions, but you're a, you're a, you're a, you're a, you're a, you're,
ability to judge that is in your head. And it can very rarely do something without a good prompt.
And so the ability to identify the problem you should be going and working on is almost entirely
in the human's head. I mean, AI can help at every level. So it's just like having a great
thought partner. But the idea of, you know, does a ladder guy go away? If anything, what we've
done is we've just given everybody this great set of executors. So basically the execution part,
then how much of it is getting replaced by AI? I don't like the word replaced. Because I feel like
replaced signals a zero-sum game. It's interesting that this particular technology has drawn that
word in a way that most past technologies have not. Maybe I'll give you an example. When power drills
came out, there was a lot of questions about, does this change the need for a construction worker,
for handyman, for so on? And of course, that's not at all what happened, because what happened,
we decided we're going to build skyscrapers. Did it replace jobs is a very interesting way to think
about it. The net number of people who worked in construction skyrocketed. I think changed. I think
change is hard. I do think we're going through change faster than most people are used to. And I think
it's easy to paint a boogeyman narrative around any new technology. Amazon came as the end of
bookstores. And we've watched these stories before. And I don't mean to say that there's not going to
be change. But I think the word replace in particular, I don't like that word. Because I feel like it
starts with a zero-sum frame. So what's happening at that execution level then? I think you're getting a
much broader workforce. What do you do with that workforce?
When all of a sudden you can deploy them, you go and build skyscrapers, go build bigger and bigger things.
Tell me about the progression from execution to problem in terms of a career.
This is something that's already happening, right?
The careers have diminished for people from, I think it's 18 to 25 beginners in their career.
And sometimes, you know, I am hiring someone who is just starting and their social media manager.
and all they can do is can come up with stories,
but I don't want them to just be able to draft a story.
I want the strategy because I already have Claude, right?
And it can do so many things.
What would you say to those people then?
I think you have to adapt.
I mean, I think every industry change leads to a change in roles.
If I go back to the construction analogy,
being the person who can, you know, run a screwdriver really fast,
stop being important once power drills came out.
Now there's a different set of skills.
And so you have to retrain.
And I do agree with you.
It's happening so quickly that sometimes people haven't adjusted.
I think marketing, the example you gave is a really interesting one.
This change in marketing is large.
But if you go back in time 20 years, this is, you know, marketing is dramatically changed.
And in the last, you know, if you go to 50 years, you think about marketing in the madman days.
You know, marketing at the time was you would hire an agency.
They would work with a very small number of companies.
They would build one ad would last an entire year with one jingle.
One perfectly crafted thing.
And then digital marketing started coming out.
And I watched this happen while we were at Google.
We'd watch these firms change over how they operated and said,
hey, you're not building one ad.
You're building millions.
And now the type of people they hire completely changed.
And it's people that were systems thinkers, people that had a different approach to marketing.
But honestly, like the original skill didn't go away.
It just shifted.
And you said, actually taste in coming up with that great message and that great jingle
was actually elevated.
But now you have to do it in a way that scales across a million ads instead of across one.
You don't have to be like this genius who comes up with just one good thing a year.
You have to be able to produce like multiple times today.
Actually, I think you need to like if I go back to your example of I don't need someone that comes up with stories because I have Claude.
Actually, I don't think that's true.
You need somebody who comes up with great stories.
Great stories.
It gives great ideas, not just editing.
That's right.
They give the great ideas and Claude can go amplify them.
Yeah.
And Claude can create hundreds of variations of them.
But if you can't come up with that great idea, then you're never going to be able to create the next ones.
And then you, now that you're not to do hundreds, now you have to be able to judge.
And so that ability to come up with great stories makes you also need to be a great reviewer of great stories.
How do you learn that?
This is back to where we started.
I think you have to practice.
I don't think it's an easy thing to learn, but it's a thing that, you know, how do you learn judgment is you practice over and over again?
Maybe it's worth, I mentioned earlier, this technique I call eigen questions.
So eigenquestion, it's a made-up word.
It comes from a mathematical term, eigenvalues and eigenvectors from linear algebra.
So an eigenvector is the most discriminating vector in a multidimensional space.
The math doesn't really matter.
An eigen question is the most discriminating question in a set of questions.
Or another way to say that it's the question when one answered, it will answer the most other questions.
The question that was number six on the list is actually the one that answers all the other ones.
So this idea became called eigen questions.
or another way to say this is the hard part is not about finding the right answer.
It's about asking the right question.
Yeah.
And so you go back to PSHE, that's what, you know, P versus S versus H versus E.
P is the question.
S is the answer.
H is the delivery mechanism and E is the actual execution.
The, so it's a very connected idea.
This technique, eigenquestions, became a technique that we trained for, that we recruited for.
Since it's become my number one indicator of someone I want to work with, someone I want to hire is how good are you at eigenquestion.
And so we spend a lot of energy on how do you learn this.
I know I'm coming back to your questions.
Yeah, yeah.
I know it's fascinating.
And it turns out that it's a very learnable skill.
But the easiest way to learn eigen questions is to do it in safe environment.
So I'll give you an example.
One of my favorite interview questions, I can't use this question anymore because I've talked
about it publicly too much, so I can give it away.
But I've probably done hundreds of interviews with this question.
So I said, okay, a group of scientists have invented a teleportation device.
How do you bring it to market?
I've asked this question, engineer.
to salespeople, to marketers, doesn't really matter.
Usually what happens is people then start asking questions.
Teleportation, what do you mean?
I answer a little bit, but mostly I'll say, why don't you get all your questions out?
And so they'll start asking questions and they'll say, how big is it?
And it does destroy the person or not?
Is it two-sided?
Is it, you know, is it fast?
Is it slow?
Is it expensive?
Is it safe?
People ask all sorts of questions.
Is it black?
Is it green?
They'll ask all sorts of different questions.
And I'll just say, okay, keep asking your questions.
We'll make a list.
And then I say, okay, hold on a second.
These scientists, they are really annoyed with all your questions.
You only get to ask two questions.
Which two questions do you ask?
And it's really interesting to watch people go back to that list and say, okay, I only get to ask two questions, which one?
There's lots of good answers.
There's no right answer.
But one answer that stood out to me was this person ended up drawing a two-axis chart and said,
one question I would ask is, how safe is it?
And they said, I think it can, like, all I really care is, is it safe enough for humans or not?
That's a really important question, right?
That's one.
If it's not safe, then.
Well, actually, it's interesting.
If it's not safe enough for humans, does it have a market?
And I think there's actually a good question.
And I'll get to that in a second.
And then the second axis was, is it more expensive CAPX or OPEX?
So, capEx, you know, is it more expensive to buy the teleportation units or is it more
expensive to use the units?
So if you just think about that as a two-by-two, you get these interesting quadrants.
So you say, well, if it's safe for humans and it's more expensive OPEX and CAP-X,
meaning that's pretty cheap to buy but expensive to use,
then you want to put them everywhere.
You want to put them where you put telephones and tax machines.
And in every house, in every corner,
you never know when you're going to need one,
but we're going to put a teleportation device there.
Okay, let's take another corner.
So it's safe enough for humans,
but it's more expensive cap-ex and OPEX.
Well, then you want to put them where you put airports.
Like, we're pretty good at finding,
and then you go to market motion is probably pretty close to our airports get funded.
That's a brilliant answer.
You've got to work through the government.
What about the other access?
What if it's not safe enough for humans?
So what are the cases where it's not safe enough for humans?
Like, what would you do with it?
And I mean, I've had them, I often will prompt people into that category if they,
if they pick this axis and, you know, say, oh, actually maybe what we should do is use it for
hauling away trash.
I don't really care if it disappears.
I don't care if it gets all mangled up.
It's going to get distributed anyway.
Or maybe it's actually things that are really high stakes.
So like one of my favorite answers was we're going to use it to ship organs to Africa.
You know, people need, need transplants.
how do you get organs there.
It's actually really hard to get them there.
You know, this is maybe a way to get there.
So this idea of like, how do you come up with an eigen question is really hard?
That particular prompt, the teleportation device, what would you do with it?
You can ask a five-year-old that question.
You should try it with yours.
Yeah.
And you'll get good answers.
I mean, and interestingly, sometimes you'll actually get better answers than you get from adults.
Because they'll like, they'll even say it in a funny way.
It's like, teleportation.
Do you blow up?
Yeah.
But they'll quickly get.
But that's a great question because this is the safety issue, blow it off.
So they're asking their question.
Yeah, that's right.
That's the question, right?
So they may not frame it in the like, in the businessy terms, but they get to the heart of the idea very quickly.
This idea of teleportation as an example, I have a list of 100 of these.
And you can come up with them.
If you want to get good at asking right questions, find domains that maybe it's low stakes.
Do it as a game.
Do it with friends.
I think it's important to practice in very low stakes environments.
I think you highlighted a very important mind problem that we're.
all happening. We're focused on a problem we want to solve immediately and we're not thinking about
big picture. And what you're talking about reminds me how we were discussing with my husband,
having 11 nanny versus like just hiring help by hours and like all my arguments, but oh my God,
we need help in the morning. But his bigger picture is like completely different. Shashir has been
hiring for the same thing for 20 years. He ran product for YouTube, founded Koda, and now runs
superhuman, the company behind Grammarly.
40 million people use it every day.
Because Chishir is hiring a lot.
I thought that pulling out the seven skills he's actually hiring for
is an interesting exercise.
What do these skills look like and how to practice them
without putting anything at work at risk?
It is in this week's Future Proof newsletter.
It's free. Link is in the description.
Okay, we're working on Taste.
Can you actually show me some AI workflows
that you're using since you're running an AI company?
company. And what my audience is really interested in is not another morning briefing agent,
because we've heard of them. We know how to set them up. I get lots of morning briefings.
Now I need a morning briefing of the morning briefings. Exactly, right? Because there are so many.
But is there something that a lot of people who are watching can set up in their job to make themselves
stand out in their company or if they're a solopreneur in their business? I'm happy to share.
I think I'll take the excuse to talk my own book. And so I'll talk about a product we're building.
I'll just give a little context before, give you the demo.
So I run a company called Superhuman.
We build an AI Native Productivity Suite made of multiple different products.
We make a really popular mail product, really popular document product.
But the product that we're probably best known for is a product called Gramerly.
Gramerly is a very popular product.
Over 40 million daily active users, you know, does hundreds of millions of dollars in revenue.
The interesting thing about Gramerly is that the core technology of Gramerly is actually not about grammar.
So the core of Grammarly is about bringing AI to work right where you work.
So two fun stats about Gramerly.
One, Granly does over 100 billion LLM queries a week.
Works out to per user per day, over 3,000 per user per day.
So if you use Grammarly, we are likely your number one generator of LLM queries.
It's mind-blowing to people to think about it.
And it's easy to understand why, because it works at the speed of typing.
As you type, we're constantly trying to figure out what are the different suggestions that we can
we can give you right in this moment. So we have to do it very quickly and we do it at that
that huge scale. Second interesting stat is Gramerly works in a million unique surfaces a day. It works
in every web app, desktop app and mobile app that you can think of where we can observe what you're doing.
We can annotate it in a way that's unobtrusive to you in the application and we make it,
we can make changes on your behalf. We sometimes describe this technology. We call it the AI superhighway.
It's we bring AI right to where you work. The interesting part of that analogy is today we are up till
three weeks ago, we only ran one car on that highway. And that's the one that happened to be,
happened to have your high school grammar teacher in it. And it's an incredibly valuable car.
Tens and millions of people find it immensely valuable every single day. But it's a vast
utilization of that infrastructure. So we decided to split the product into two. And so we
took Grammally and turned it into what we call an agent. And we took the bottom half, the AI
Super Highway, and we built a new product around it called Superhuman Go. And we built a new product around it called
Superhuman Go. It's a very simple idea. It allows you to build AI agents. It can do everything that the rest of the
agents can do, including sending you morning briefings. But the unique thing it can do is it can work right where you work. It's like Grammarly, but with your own knowledge, your own connectors, your own tools, so on, and with your own prompts.
If you download Grammally, you'll get a big G in your extension bar, or you can do the same thing with the desktop app. And you can just go and say use superhuman go and I'll flip it over to go mode. And at that point, what used to be a G turns into,
the superhuman logo, which we call it Hero, and you get a set of agents.
And you can go add your own agents.
And is only yours?
These are, I have a demo account here, but I use a very similar set for myself.
So, but you end up with very personal data.
So this is, but it's very close to what I do.
So I'll show you some examples.
So one of my, one of my personal favorite agents is this one.
So this is called a knowledge checker.
And so what this is doing, so this is the agent builder.
So you can build an agent that does anything.
And I think a lot of agent builders are quite similar these days.
You give it a set of tools that has access to.
You can connect any different tool to it.
We have a wide set of connectors that'll, that synchronize data, or you can connect any MCP.
You have some instructions on what you want it to do.
But the most important part is the triggers.
So these triggers are, you can trigger on anything.
You can trigger on a schedule.
So that's like you were saying, the morning briefing every day.
there's a set of events you can trigger on every time I get a Slack message or so on.
But the most important trigger for us is what we call the while writing trigger that says while I'm writing, I want you to go and make these types of suggestions.
You can pick a color and so on.
Do I understand this correctly?
Or are you saying when I have this agent on, like if I'm replying to someone with a summary of another email, like I'm planning a party and somebody send me information about their home and I'm replaying.
lying to guests, I can just ask superhuman to pull that information, like fact check what I'm saying.
Exactly.
Oh, exactly. So I'll show you an example.
You don't have to have multiple windows and I go back before.
So it's not only just not multiple windows. So I think if you think about some of these
cases, I'll show you, I'll show you a couple of different cases. This is a professional use case.
I'm writing a launch announcement. I'm a marketer. So these are, these underlines look like
grammarly. And some of them are. This one is literally from grammarly. But some of them are coming
from other agents. So this one, for example, is coming from, I have a launch project manager agent
that tells me that this is not actually pending legal review. I still need to go deal with the
design design review. Or this one might come and this is my legal guardrail agent that says
you're not supposed to say it that way. Here's a more correct way to say it. So it checks everything
you wrote. It checks everything. So you could use it. Maybe you use it in Gmail or maybe use it in a document.
Here's an example where maybe you want to use it in an email.
If I write, sell my revenue for this quarter is this.
And if it's connected to whatever it's connected.
It'll go fact check it.
And I don't have to trigger it.
It just fact checks it.
Fact checking is one of my favorite agents.
Where does the knowledge come from?
So it's fully resolved, meaning it's a project somewhere?
Each of the agents has different data sources.
And so, for example, that agent I just gave is the source finder agent.
is this one I have here.
And I can go see this one has access to, in this case, I gave it access to my mail, my calendar,
and my docs.
But you can give it access to anything.
And so that'll come through and give you suggestions based off of what's happening with, you know,
each of these tickets or you can, you'll check a revenue number or so on.
And I think in that way, you can design an agent that feels like, I mean, one way to think
about it is if Gramerly felt like it's magical to have your,
your grammar teacher follow you everywhere. It's like sitting on your shoulder. Who else do you want
sitting on your shoulder? And one of the things, that's the main part of the demo, but one of the
ways I think about this is if you think about the world of AI, I think there's sort of three
metaphors for how people think about AI. So one is the most common one is chat. And that's like this.
It's like I have this agent that feels like a human and it's magical. It's obviously captured
everybody's imagination. There's lots of products that have a chat metaphor. Another metaphor is what we
called do. So that's a metaphor of I have a task list. I want you to take things off my task
list. It's also a really powerful metaphor and many tools that are that are focused on that.
Our view is that there's a third metaphor we call assist. So I can think about assist chat do.
Assist is I need an agent that comes where I'm working before I ask anything and helps me in a way
that I didn't expect. So for example, this, you know, would I go check a fact on a particular
email? You might remember to do that. And if you know, like you're saying, you're writing an email to
somebody about the party and you put in the wrong address or you put in the wrong time or you put in
the wrong name, you know, would you remember to take that and put it into one of your chat bots that's
connected to the right data and actually get back to that reply? Probably not. And that's the reason
why we get that, you know, our users give thousands of queries per day. If you were a really good chat
GPT or cloud user, maybe you would generate 10 queries a day. That would be a lot of interaction. But we get
thousands. And the reason is because we're there working with you right where you work without you
NASC. So I think it's a very interesting way to rethink AI. So what are the top three life-changing
agents? The fact-checker. The fact checker is a really interesting one for all the reasons you already
got to. No, I'm already because this is what I'm doing. Like, I have two phones because I'm checking
one email and replying to another. That one's amazing. I have another one I use personally called
the placeholder filler. And I have a, they're very personal, by the way. Because if you think about,
like, you want an assistant that knows you. So mine is, I have a, I have a.
a writing pattern, which is when I'm, when I'm writing, I'll often leave, uh, empty things that I'm,
I'll come back to. And I just put them in brackets. And so I'll say, you know, I'll be outlining
something. I'll say we should, I should start with a quote, right, you know, a customer quote about
this. And then I'll keep writing and I'll, I just put it in brackets. And it'll go and find it.
And it'll go and try to fill in my placeholders with whatever the best suggestions it can. I,
I give the agent access to all my information. And so I can go and fill those things in. Um, so that's a
really productive one for me.
Can I do online search as well?
Yeah, anything.
Yeah.
So anything you want it to connect to to.
I mean, you have to decide what you want to give it to access to.
You can have these agents be, they can be collaborative.
So you can share them with other people.
You can put them in collaborative spaces.
You can put them in Slack or wherever else you like as well.
So like another common use case we see from customers is customers will use it, for example, for compliance checks.
So for some companies, that's, we're working right now with a major magazine,
publisher. They have a dozen or so magazines. And they have 16 review departments. So if you're a
reporter and you're writing a story, you go to the fact checker, you go to the brand people, you go to
the citation checker and the source checker. And they gave all these different folks to do. I'm not
even sure I know all the departments they go to. They took all of them and turned it into an assistant
that they just deployed and it works everywhere. And so rather than remembering to go to every
department now your story slowed down. It's just happening while you're going. And you also
get it much earlier. So instead of waiting till the end when, oh, I thought my story was done.
And, you know, I wrote the whole story based off of this fact that turned out to be wrong.
Yeah. Like you want to know that much earlier in your process. Yeah. I really like that,
the proactivity and also being where you are in the moment. Yes. Anything else? Number three.
Oh, boy. Let's see, number three. I mean, I think there's a set of use cases. For me, the calendar one is really
interesting. So I have it connected my calendar and it'll do the, like the example you gave of
your suggesting a time check that that's accurate. The more interesting ones is it'll come and see
if I'm trying to schedule something and it'll underline it with my availability and with an
option to go and book the meeting. And so I'll come in and, you know, say, we should meet
tomorrow and I'll come underline it and say, actually, I've checked both your calendars and tomorrow
2pm works. Would it highlight if, because this is what happens to me all the time. I have two
different emails. I'm discussing the same date.
Would it tell you like, hey, you actually propose, you would just propose that.
You just have to build that in your prompt.
Just imagine you can take grammar and give it to your own instructions.
And, you know, anything that you wanted to do, you can do.
Yeah.
So the main difference I see, because my audience experienced in like using this little clot extension
or like comment browser is that you don't have to trigger anything.
Yeah.
It's just there.
Those are still in this frame of a cis chat dude.
Those are still chat, right?
Those are still, I need to remember to open it and think about.
well, okay, can you check that time?
I didn't promise to anyone else.
And if you remember that, you know, that's great.
But how many times you're going to remember that?
You're going to forget.
And the key about what made grammarly so interesting is it works everywhere.
Every web app, desktop app.
It'll work in IMessage.
It'll work in Apple Notes.
It'll work in, you know, it'll work in, you know, Google Docs and Word and, you know,
all the different tools that you might be in.
And so this idea of, you know, really feels ever present.
And now you can design that assistant to do the set of them to do whatever you like.
I think it's great.
I think this is really the mode that you have because people want their assistance, won them there without asking for them.
Otherwise, it's AI becomes a chore.
It's like I have to remember to go use it.
To use AI.
By the way, if you want to know what actually gets you promoted now, subscribe to this channel.
I sit down with the people making those decisions, founders and CEOs who write the promotion criteria.
And I asked them what they are really looking for.
Okay, I wanted to wrap up this conversation with the most valuable advice you got from Bill Campbell.
You worked with one of the most iconic coaches in Silicon Valley, who unfortunately already passed.
But he mentored some of the top CEOs.
And whenever I have a problem, I ask my chatypt to become a coach like him.
What would you tell people who are watching who are in this transition?
era. Maybe they're scared. Maybe they're excited because they see all the opportunity is something that
he told you. I worked with Bill. I started working with Bill in 2000. So this was, um, at the time he had
left into it, he was hanging out of Kleiner Perkins. I got to know Bill at a period where he was in
his coach mode, but it was before all the big shots. And so I, you know, I got lucky. And that period
is helping out all I had started a company that was funded by Kleiner Perkins and he would hang out and
and help out whatever he saw as the most interesting companies. Immensely helped.
I mean, he was, I don't know, I can't overstate how, how much impact he had on me and on the team.
You know, almost, I was a 21-year-old first-time CEO learning how to do everything.
He taught me he taught me how to run my first staff meeting.
He taught me first time I had to fire someone.
He walked me through, this is how your talk track is going to work, how to deal with my investors,
how to hire people.
Like, there's so many different pieces.
The most memorable conversation with Bill was he, I'd been working with him for about a year.
and I came to him and I said, hey, Bill, I just realized that we haven't done an advisor agreement
with you. And I felt really bad because, you know, we had other advisors of the company and,
you know, we had given them some cases, some compensation, some equity or so on. And you've been,
you know, immensely valuable. And I don't want to, I don't want to take advantage of that. So I'm
happy to put something in place. And he said, she sure, don't worry, I don't need it. I was offended.
to be honest, it was the, you know, what's wrong with my equity?
And he said, no, no, I didn't mean it that way.
He says, you know, I've been lucky through my life.
At this point, everything I get goes right to charity.
So if you want to give it to me, it's fine, but you could also just give it to charity and that's okay too.
But honestly, you should hold on to it and use it to grow the company because it's not the, not the way you should use it right now.
And I said, well, that's really interesting, Bill.
It feels like I'm surrounded by people that all want a little piece of the,
company and you're like the only one that's putting you adding so much value and that somehow that's not
that's not what's motivating you so what motivates you and he gave me this really interesting answer
and he said well i just look at all the people that um that have worked for me or that i've mentored
and i just make a list of how many of them are fortune 500 CEOs and that's my bar this was back in
2000 so there's you know since then it's you know Larry Page and Steve Jobs and Jeff Faisers and so on but
in 2000, he already had a list of 20 people.
Wow.
And he's just working through this list.
And you could just see this sense of finding success in other people's success.
Yeah.
It was such a different way of thinking about the world.
And it completely changed my worldview of, you know, zero-sum games.
What are you?
I'm sure everybody's had that experience of somebody you love is working for you
and decides to go on to do something else.
And Bill taught me if you're going to be,
a good partner, a good manager, a good leader,
you need to root for your people's success.
You need to judge your success that way.
It's actually, that's how it carries on.
And it was interesting when Bill passed,
they held his funeral at that Sacred Heart,
you know, up the road here.
And every single person who came up to the stage
had almost the identical story.
He had infinite time for me and he only cared about me being successful.
And as far as I could tell, you know,
that's all that mattered to him.
And every person looked around and said, how do you have time for you?
And how did he, you know, it could just seem like he was in your corner rooting for you in a way that was very different.
And so, you know, very much changed my way of thinking about interacting with people.
This is such a great metric to optimize for.
Because we're always looking at numbers.
This could be a number, a number of people.
Oh, he was very numeric about it.
I mean, he was a sales guy.
I mean, he had a, he had a metric.
And he had the list.
He knew them by heart.
Yeah.
Yeah.
That's amazing. I think everyone who's watching this, if you don't have this metric yet, think about it.
Like, how do you measure people who become successful thanks to your work?
Yeah.
That's awesome.
Thank you so much.
Thank you.
If Shishir made you rethink, what are you being promoted for?
Watch my conversation with Ryan Roslansky.
He was the CEO of LinkedIn at the time of the interview, and Ryan will tell you exactly which jobs are appearing and what companies are looking for right now in the age of AI.
