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Jason Calacanis on Startups | jason@calacanis.com | Substack
While I started as an angel investor and Scout, I've invested out of venture funds for the past decade. Our fund sizes have increased over time, and we're a 20+ person team at LAUNCH (my venture firm). Our investor base started with individual investors but has grown to include more institutions.
So, the event and podcast have expanded their mandate as well.
The LIQUIDITY podcast will feature a rotating cast of guests, including general partners, limited partners, public market investors, and angel investors.
The LIQUIDITY event will be in Napa from June 2nd to 4th. We will open registration shortly.
best, JCal
PS - I'm also considering starting "the Jason Calacanis podcast" in the second half of 2024, where I talk to folks who aren't in tech. And, yes, I’m still hosting This Week in Startups and the All In podcast. :-)
individual investors but has grown to include more institutions.
So, the event and podcast have expanded their mandate as well.
The LIQUIDITY podcast will feature a rotating cast of guests, including general partners, limited partners, public market investors, and angel investors.
The LIQUIDITY event will be in Napa from June 2nd to 4th. We will open registration shortly.
best, JCal
PS - I'm also considering starting "the Jason Calacanis podcast" in the second half of 2024, where I talk to folks who aren't in tech. And, yes, I’m still hosting This Week in Startups and the All In podcast. :-)
Made this images using OpenAI’s Dall-E, which is ironic.
Today, the New York Times sued OpenAI and Microsoft for stealing millions of pages of their content to power the most promising technology platform since the iPhone: ChatGPT.
The charges aren't debatable and will be quickly proven if this landmark case ever makes it to trial -- and I think this one will.
Most language models train on an open-source project called "Common Crawl."
Common Crawl is like the Google search index, but it's available to everyone for free -- with some important caveats.
The Common Crawl terms of use are clear: if you want to use the data they've indexed, you must go to every content owner and follow their terms of service.
From that ToU:
"You also acknowledge and agree that all information, data, text, scripts, web pages, web sites, software, html page links, open data APIs, metadata or other materials (collectively, the "Crawled Content ") may be subject to separate terms of use or terms of service from the owners of such Crawled Content."
Of course, technologists, generally speaking, have little to no respect for IP.
I hear many peers say it's yours if you can index it, which is absurd and lacks empathy for content creators.
This attitude started with Napster and extended to Google's approach to using other people's content 20 years ago.
NAPSTER got smashed because the music industry is savvy and hardcore.
News sites got rolled by Google because publishers are dopey and meek.
Google's position back then was, "If you don't want to be in the index, just tell us not to crawl you in your robot.txt file!"
Of course, Google got so big, so fast, that it started sending massive traffic to sites like the NYTimes.
The publishing industry was so fractured and dumb at the time that they never considered how utterly worthless Google would be if the top 500 publications refused to let them index it.
So, Google brilliantly threaded the needle on "fair use" laws by making publishers feel like "a ton of traffic for a snippet of content is a fair deal."
Then Google gutted the publishing industry with its massive advertising platform, creating all kinds of downstream issues for society (a whole other blog post).
The publishing industry is smaller now, battle-scarred by decades of war with technology companies.
The NYTimes isn't the dopey publisher it was in the early 2000s. Today, they run one of the most successful subscription businesses in the world and compete in many areas outside of news.
This time, they won't get rolled; they'll fight to the death.
And this time, they're going to win.
OpenAI can't make the "fair use" argument that Google made because ChatGPT doesn't send traffic to publishers; it simply gives users an answer based on all the content they've liberated.
The NYTimes points this out in their suit, and it's devastating.
OpenAI will settle this suit for hundreds of millions of dollars, perhaps billions, I predict (something the two parties tried to do before the NYTimes filed).
The suit gives many examples of OpenAI using the NYT's content, and they've caught them dead to rights.
For example, the NYT quickly proves that OpenAI stole the Wirecutter's IP and brazenly gives results built off that IP -- but that doesn't link back, and that removes the affiliate links that pay for creating that content.
Game over for OpenAI and Microsoft with that example.
Here’s a screenshot from the lawsuit:
From the NYT lawsuit.
Additionally, the NYTimes points out their content is behind a paywall.
Today, I pay a couple of hundred dollars for the NYTimes.
I am also among the millions who pay OpenAI a couple hundred dollars a year for a subscription.
Using these services for 20+ years, my lifetime value is $6,000 each.
I'm also a massive fan of the wirecutter and use it for my decision-making process before smashing the Amazon buy button.
Recently, I found myself doing product searches with ChatGPT.
These two services are directly competing, and one does all the work: the New York Times.
The other steals their answers from the New York Times (OpenAI).
Now, it’s great that OpenAI is trying to do the right thing here and settle, but let’s be honest: they’re only trying to settle this because they got caught with their hand in the cookie jar.
These are amongst the smartest individuals on the planet, and they stole this content because it would make them rich.
The discovery will show technologists trying to find the best content in the world to train their $100B franchise while they personally sell billions of dollars in shares for personal gain.
Let that sink in: the OpenAI team is reportedly selling billions of shares based on a product trained on other people’s IP.
If OpenAI can do this, well, then the rest of us can train a model on Star Wars, Marvel, Pixar, and Disney IP and make the next generation of superhero and Jedi stories!
The judges and jury in this one will make short work of OpenAI and Microsoft. OpenAI and Microsoft need to pay for the lost revenue that the NYTimes is currently experiencing--that's obvious.
The more significant issue here is the Google v. Publisher rematch.
The New York Times will take an open-source language model, train it on their data, and create a ChapGPT competitor--that much is clear.
What if the NYTimes is successful with that model and they start buying more sites like Wirecutter and The Athletic?
OpenAI and the New York Times are direct competitors; you can’t steal a direct competitors IP.
It’s that simple.
Man, maybe I need to jaytrade ’some NYTimes stock.
These cats at the NYTimes aren't as dumb as they used to be.
The only question is, are they now tigers?
Would they have the audacity to compete with OpenAI?
If I were running the New York Times, I would announce a ChatGPT competitor today and raise ten billion dollars… from Google or Apple.
best, JCal
PS - forgive any typos. I decided to let these blog posts fly without an editor.
e will.
Most language models train on an open-source project called "Common Crawl."
Common Crawl is like the Google search index, but it's available to everyone for free -- with some important caveats.
The Common Crawl terms of use are clear: if you want to use the data they've indexed, you must go to every content owner and follow their terms of service.
From that ToU:
"You also acknowledge and agree that all information, data, text, scripts, web pages, web sites, software, html page links, open data APIs, metadata or other materials (collectively, the "Crawled Content ") may be subject to separate terms of use or terms of service from the owners of such Crawled Content."
Of course, technologists, generally speaking, have little to no respect for IP.
I hear many peers say it's yours if you can index it, which is absurd and lacks empathy for content creators.
This attitude started with Napster and extended to Google's approach to using other people's content 20 years ago.
NAPSTER got smashed because the music industry is savvy and hardcore.
News sites got rolled by Google because publishers are dopey and meek.
Google's position back then was, "If you don't want to be in the index, just tell us not to crawl you in your robot.txt file!"
Of course, Google got so big, so fast, that it started sending massive traffic to sites like the NYTimes.
The publishing industry was so fractured and dumb at the time that they never considered how utterly worthless Google would be if the top 500 publications refused to let them index it.
So, Google brilliantly threaded the needle on "fair use" laws by making publishers feel like "a ton of traffic for a snippet of content is a fair deal."
Then Google gutted the publishing industry with its massive advertising platform, creating all kinds of downstream issues for society (a whole other blog post).
The publishing industry is smaller now, battle-scarred by decades of war with technology companies.
The NYTimes isn't the dopey publisher it was in the early 2000s. Today, they run one of the most successful subscription businesses in the world and compete in many areas outside of news.
This time, they won't get rolled; they'll fight to the death.
And this time, they're going to win.
OpenAI can't make the "fair use" argument that Google made because ChatGPT doesn't send traffic to publishers; it simply gives users an answer based on all the content they've liberated.
The NYTimes points this out in their suit, and it's devastating.
OpenAI will settle this suit for hundreds of millions of dollars, perhaps billions, I predict (something the two parties tried to do before the NYTimes filed).
The suit gives many examples of OpenAI using the NYT's content, and they've caught them dead to rights.
For example, the NYT quickly proves that OpenAI stole the Wirecutter's IP and brazenly gives results built off that IP -- but that doesn't link back, and that removes the affiliate links that pay for creating that content.
Game over for OpenAI and Microsoft with that example.
Here’s a screenshot from the lawsuit:
From the NYT lawsuit.
Additionally, the NYTimes points out their content is behind a paywall.
Today, I pay a couple of hundred dollars for the NYTimes.
I am also among the millions who pay OpenAI a couple hundred dollars a year for a subscription.
Using these services for 20+ years, my lifetime value is $6,000 each.
I'm also a massive fan of the wirecutter and use it for my decision-making process before smashing the Amazon buy button.
Recently, I found myself doing product searches with ChatGPT.
These two services are directly competing, and one does all the work: the New York Times.
The other steals their answers from the New York Times (OpenAI).
Now, it’s great that OpenAI is trying to do the right thing here and settle, but let’s be honest: they’re only trying to settle this because they got caught with their hand in the cookie jar.
These are amongst the smartest individuals on the planet, and they stole this content because it would make them rich.
The discovery will show technologists trying to find the best content in the world to train their $100B franchise while they personally sell billions of dollars in shares for personal gain.
Let that sink in: the OpenAI team is reportedly selling billions of shares based on a product trained on other people’s IP.
If OpenAI can do this, well, then the rest of us can train a model on Star Wars, Marvel, Pixar, and Disney IP and make the next generation of superhero and Jedi stories!
The judges and jury in this one will make short work of OpenAI and Microsoft. OpenAI and Microsoft need to pay for the lost revenue that the NYTimes is currently experiencing--that's obvious.
The more significant issue here is the Google v. Publisher rematch.
The New York Times will take an open-source language model, train it on their data, and create a ChapGPT competitor--that much is clear.
What if the NYTimes is successful with that model and they start buying more sites like Wirecutter and The Athletic?
OpenAI and the New York Times are direct competitors; you can’t steal a direct competitors IP.
It’s that simple.
Man, maybe I need to jaytrade ’some NYTimes stock.
These cats at the NYTimes aren't as dumb as they used to be.
The only question is, are they now tigers?
Would they have the audacity to compete with OpenAI?
If I were running the New York Times, I would announce a ChatGPT competitor today and raise ten billion dollars… from Google or Apple.
best, JCal
PS - forgive any typos. I decided to let these blog posts fly without an editor.
Share this post
The greatest moment to start a company? Right Now!
“If only I had started a company during the desktop PC revolution in the 80s and 90s!”
“If only I had started a company at the start of the internet!”
“If only I had started an app or cloud company during the ZIRP run up from 2009 to 2021!”
“If only I had started a company during web 2.0 in 2005!”
I lived through all four of those tech supercycles.
I learned in the first one (the PC revolution), got famous in the second (dot com), and made my fortune during the last two (web 2.0 and ZIRP).
Thanks for reading Jason Calacanis on Startups! Subscribe for free to receive new posts and support my work.
The last four tech-driven “supercycles” are worth studying:
The 1980s: The PC revolution created Microsoft ($2.7T market cap), Apple ($3T), and Dell ($48.8B).
The 1990s: The dot-com bubble created Google ($1.7T) and Yahoo.
The 2000s: The web 2.0 created YouTube, Facebook ($855B), Dropbox, Thumbtack, and Tesla.
The 2010s: The ZIRP era, which created Uber ($126B), Airbnb, DoorDash, and Coinbase.
We’re heading into what I will name “The AI Roaring 20s.”
Why The AI Roaring 20s will be the greatest time to start your company
The next supercycle is starting right now, in 2023 and 2024.
There are four reasons this will be the greatest super cycle of our lifetime:
AI.
An unlimited, cheap, and global talent pool — powered by AI tools.
Unlimited venture capital for any winning startup (defined as a startup that can get to $500,000 in revenue), with reasonable gross margins and burn.
Absurdly low operating costs, including not just talent but marketing, technology, professional services, and tools.
Jason’s Law: Every supercycle drops the cost of starting a company by 50%.
1980s In the PC era, you needed 20 people and $6M in 2023 dollars to start a company. You needed to build core technology, rack servers, get an office manager and an office, and then spend two years building your product.
1990s This dropped to 10 people and $3m in the dotcom era. You racked servers, spent a year building product, and had an office.
2000s In Web 2.0 we started companies with $1.5m and five people. Co-location providers and office sharing started, as did remote work and offshore developers. APIs and open-source software cut costs and developer cycles dramatically.
2010s In ZIRP, we saw companies start with three builders and $750,000. Github, AWS, WeWork, Fivver, Upwork, and the global workforce meant a startup could launch a product in a 12-week incubator and scale it to millions in revenue in a few years.
2020s In the roaring 20s, you can easily start your company with three founders and $375,000 — heck, even $25,000. IDEs, cloud, open source AI models, no code, low code, and a decade of remote work and workers means your product can be in customers’ hands in under 30 days.
In Summary…
Now is the greatest time to launch a startup. Uber, Spotify, Google, and Facebook aren’t hiring; most are quietly or publicly “getting fit” (aka, culling the weakest members of the herd).
You can find two founders and teach yourself to code, do growth hacking, or be a UX designer in months, so what are you waiting for?
What’s your excuse?
Who's holding you back now?
You could drive Uber or DoorDash three days a week and work on your startup with two friends on the other four days.
There are unlimited problems waiting to be solved and talent that wants to work.
I’m investing in 100 startups a year, and I’m hoping that I can be your first investor.
If this is interesting to you, please watch this video.
Let’s…. do the work
best, JCal
The other images Dall-E came up with for a the prompt "you are the worlds greatest illustrator working for the world's greatest essay writer. the essay is about creating startups in the 2020s the writer believes now is the best time ever to start a company and build amazing, futuristic things we need a header image of 1920x1080 pixels for this blog post we want it to combine the feeling of the roaring 1920s in America with a technology-driven optimistic future "
Thanks for reading Jason Calacanis on Startups! Subscribe for free to receive new posts and support my work.
ned in the first one (the PC revolution), got famous in the second (dot com), and made my fortune during the last two (web 2.0 and ZIRP).
Thanks for reading Jason Calacanis on Startups! Subscribe for free to receive new posts and support my work.
The last four tech-driven “supercycles” are worth studying:
The 1980s: The PC revolution created Microsoft ($2.7T market cap), Apple ($3T), and Dell ($48.8B).
The 1990s: The dot-com bubble created Google ($1.7T) and Yahoo.
The 2000s: The web 2.0 created YouTube, Facebook ($855B), Dropbox, Thumbtack, and Tesla.
The 2010s: The ZIRP era, which created Uber ($126B), Airbnb, DoorDash, and Coinbase.
We’re heading into what I will name “The AI Roaring 20s.”
Why The AI Roaring 20s will be the greatest time to start your company
The next supercycle is starting right now, in 2023 and 2024.
There are four reasons this will be the greatest super cycle of our lifetime:
AI.
An unlimited, cheap, and global talent pool — powered by AI tools.
Unlimited venture capital for any winning startup (defined as a startup that can get to $500,000 in revenue), with reasonable gross margins and burn.
Absurdly low operating costs, including not just talent but marketing, technology, professional services, and tools.
Jason’s Law: Every supercycle drops the cost of starting a company by 50%.
1980s In the PC era, you needed 20 people and $6M in 2023 dollars to start a company. You needed to build core technology, rack servers, get an office manager and an office, and then spend two years building your product.
1990s This dropped to 10 people and $3m in the dotcom era. You racked servers, spent a year building product, and had an office.
2000s In Web 2.0 we started companies with $1.5m and five people. Co-location providers and office sharing started, as did remote work and offshore developers. APIs and open-source software cut costs and developer cycles dramatically.
2010s In ZIRP, we saw companies start with three builders and $750,000. Github, AWS, WeWork, Fivver, Upwork, and the global workforce meant a startup could launch a product in a 12-week incubator and scale it to millions in revenue in a few years.
2020s In the roaring 20s, you can easily start your company with three founders and $375,000 — heck, even $25,000. IDEs, cloud, open source AI models, no code, low code, and a decade of remote work and workers means your product can be in customers’ hands in under 30 days.
In Summary…
Now is the greatest time to launch a startup. Uber, Spotify, Google, and Facebook aren’t hiring; most are quietly or publicly “getting fit” (aka, culling the weakest members of the herd).
You can find two founders and teach yourself to code, do growth hacking, or be a UX designer in months, so what are you waiting for?
What’s your excuse?
Who's holding you back now?
You could drive Uber or DoorDash three days a week and work on your startup with two friends on the other four days.
There are unlimited problems waiting to be solved and talent that wants to work.
I’m investing in 100 startups a year, and I’m hoping that I can be your first investor.
If this is interesting to you, please watch this video.
Let’s…. do the work
best, JCal
The other images Dall-E came up with for a the prompt "you are the worlds greatest illustrator working for the world's greatest essay writer. the essay is about creating startups in the 2020s the writer believes now is the best time ever to start a company and build amazing, futuristic things we need a header image of 1920x1080 pixels for this blog post we want it to combine the feeling of the roaring 1920s in America with a technology-driven optimistic future "
Thanks for reading Jason Calacanis on Startups! Subscribe for free to receive new posts and support my work.
Share this post
Startup productivity in the age of AI: automate, deprecate, delegate (A.D.D.)
Over the past decade, I invested in over 350 startups and watched up close as founders figured out how to do more with less.
Startups, by their nature, are resource-constrained organizations when compared to the legacy businesses they are trying to displace.
Thanks for reading Jason Calacanis on Startups! Subscribe for free to receive new posts and support my work.
There is, of course, the rare exception of a market frenzy when startups are overfunded. I've experienced two in my lifetime: the dot-com bubble (~1998-2000) and the ZIRP bubble (~2019-2021).
Those approximate five years were fantastic times to sell overpriced equities and raise money, but they are so rare that founders should put them in the back of their minds (except as a time to consider selling some shares).
Since startups are most often resource-constrained, it's critical to look at what's taking up your time and ask the following three questions:
Can we automate this (with software)?
Can we deprecate this (because it's having little to no impact)?
Can we delegate this (to someone at a lower salary)?
While this A.D.D. framework might seem obvious as you read it, it's easy to forget (like many simple things).
How to avoid panicking your team
Now, it’s hard to implement this inside your startup because as you deploy it, folks will naturally be nervous.
They’ll immediately ask valid questions like:
“You’re going to automate my job?!”
“You’re going to outsource my job to a remote worker getting paid half as much as me!??!”
“You’re going to have me stop doing the busy work that takes up half my day!??!”
“Am I getting laid off?!?!”
The answer is “yes!” to the first three, and “your choice” for number four.
The brutal truth is that most jobs will be automated, delegated, and deprecated in the coming years thanks to AI and remote work (more on this below).
We must embrace this moment and “move up the stack” to higher-impact work as the easy work fades away.
The highest-level contributors in the 21st century are those who can implement this A.D.D. framework, confidently, and understanding there will ALWAYS be higher-level work.
If you run a hotel and magically, tomorrow, a robot could deliver room service and your bags perfectly at 10% of the price, you would immediately take that win. In fact, these robots exist and are currently being deployed, by many, many, many companies.
So, you take the win and redeploy the bellhop and room service staff (if willing to level up) to higher-level work that improves the guest experience.
If the guest experience gets perfected and you need fewer people to run the hotel, you should…. wait for it…. open another hotel. Or lower the prices at your current hotel. Or increase your profitability and raise the remaining employees' salaries.
That’s where society is headed, fewer people accomplishing more and doing more meaningful work.
This evolution has been happening for some time now, but with AI it’s going into hyperdrive.
Here's how you implement the A.D.D. framework:
a. Every week, ask your team to do an S.O.W. and E.O.W.: a start-of-the-week report and an end-of-the-week report.
b. After three months, review the significant items folks accomplished each week and ask them which items they think have the highest and lowest impact on the business. People will be candid with you.
c. Automate: sit with whoever the most tech-savvy folks in your company are and figure out how to automate the most critical tasks where possible. At my investment firm, LAUNCH, we have a half dozen folks who know how to use Notion, CODA, Zapier, Airtable, and Slack to build “mini-apps” that automate everything we do. Hands down, these are our most valuable team members.
d. Deprecate: When faced with a list of tasks that can’t quickly and easily be automated, ask yourself, as the founder, if this task is essential or optional. As a founder, you probably asked folks to do things last year that are no longer essential this yearl, but your loyal team members are doing them as if they are.
Your bad. Be ruthless in deprecating these items. If you're wrong, you can always add the items back.
e. Delegate: After you automate and deprecate, you'll be left with a bunch of important tasks that can't be automated and that you need to do. At this point, look at the hourly salary of the person doing them. Times that salary by 1.2x (for benefits and equipment) and then divide that number by 2,000 (the number of hours the average person works a year).
If a $100,000 employee updates a database with contact information and processes invoices for 10 hours a week, that is costing you $60 an hour ($120,000 / 2,000). A work-from-home executive in the USA would cost ~$25. In Canada, it would cost ~$15 USD. In Manila, it would be $5 an hour (and you would have a line out the door of folks who want that job).
The average $100,000 employee in America who implements the A.D.D. system will automate 20% of their job, deprecate 20%, and delegate 20%, in my experience.
This means every year, a high-functioning team should be able to free up ~50% of their cost/work on average (depending on how much you save when you delegate that 20%).
Why is this important now?
While these steps seem apparent, three things have made this framework critical:
Startup funding has collapsed by 75%.
Remote work has made all of us exceptional at managing and delegating work. Managing an American, Canadian, Argentinian, or Phillipino team member is the exact same on SLACK and Zoom.
Most importantly, ChatGPT, Bard, Claud, and countless emerging AI tools are making the automation of work accelerate at an absurd pace.
The great irony, I’ve learned, is that the remote workers from emerging markets are the ones embracing ChatGPT the most. It’s obvious why when you think about it.
These remote workers are typically working freelance for a dozen customers who only care about output. They’re very hungry, and they are absurdly customer-focused. They know that the faster and happier they make a customer, the more money they can make.
In conclusion
I’ve been working with our portfolio companies and our teams on this process for over a year, and it’s having dramatic results. This is a 1.0 framework, so please take it, remix it, and report your results to me.
We all want to do more meaningful work and we will always find new ways to be helpful to society.
PS - I’m going to start doing weekly posts here on Substack, to my x.com/jason account, and Linkedin. I am also planning on doing a paid subscription of some type to hire a full-time editor to work with me on these posts.
Will include some sort of subscriber Q&A and benefits as well (hit reply and tell me what you want). If you want to pre-pledge, you can do so at calacanis.substack.com. Which will give me some signal as to people’s interest.
Thanks for reading Jason Calacanis on Startups! Subscribe for free to receive new posts and support my work.
t my work.
There is, of course, the rare exception of a market frenzy when startups are overfunded. I've experienced two in my lifetime: the dot-com bubble (~1998-2000) and the ZIRP bubble (~2019-2021).
Those approximate five years were fantastic times to sell overpriced equities and raise money, but they are so rare that founders should put them in the back of their minds (except as a time to consider selling some shares).
Since startups are most often resource-constrained, it's critical to look at what's taking up your time and ask the following three questions:
Can we automate this (with software)?
Can we deprecate this (because it's having little to no impact)?
Can we delegate this (to someone at a lower salary)?
While this A.D.D. framework might seem obvious as you read it, it's easy to forget (like many simple things).
How to avoid panicking your team
Now, it’s hard to implement this inside your startup because as you deploy it, folks will naturally be nervous.
They’ll immediately ask valid questions like:
“You’re going to automate my job?!”
“You’re going to outsource my job to a remote worker getting paid half as much as me!??!”
“You’re going to have me stop doing the busy work that takes up half my day!??!”
“Am I getting laid off?!?!”
The answer is “yes!” to the first three, and “your choice” for number four.
The brutal truth is that most jobs will be automated, delegated, and deprecated in the coming years thanks to AI and remote work (more on this below).
We must embrace this moment and “move up the stack” to higher-impact work as the easy work fades away.
The highest-level contributors in the 21st century are those who can implement this A.D.D. framework, confidently, and understanding there will ALWAYS be higher-level work.
If you run a hotel and magically, tomorrow, a robot could deliver room service and your bags perfectly at 10% of the price, you would immediately take that win. In fact, these robots exist and are currently being deployed, by many, many, many companies.
So, you take the win and redeploy the bellhop and room service staff (if willing to level up) to higher-level work that improves the guest experience.
If the guest experience gets perfected and you need fewer people to run the hotel, you should…. wait for it…. open another hotel. Or lower the prices at your current hotel. Or increase your profitability and raise the remaining employees' salaries.
That’s where society is headed, fewer people accomplishing more and doing more meaningful work.
This evolution has been happening for some time now, but with AI it’s going into hyperdrive.
Here's how you implement the A.D.D. framework:
a. Every week, ask your team to do an S.O.W. and E.O.W.: a start-of-the-week report and an end-of-the-week report.
b. After three months, review the significant items folks accomplished each week and ask them which items they think have the highest and lowest impact on the business. People will be candid with you.
c. Automate: sit with whoever the most tech-savvy folks in your company are and figure out how to automate the most critical tasks where possible. At my investment firm, LAUNCH, we have a half dozen folks who know how to use Notion, CODA, Zapier, Airtable, and Slack to build “mini-apps” that automate everything we do. Hands down, these are our most valuable team members.
d. Deprecate: When faced with a list of tasks that can’t quickly and easily be automated, ask yourself, as the founder, if this task is essential or optional. As a founder, you probably asked folks to do things last year that are no longer essential this yearl, but your loyal team members are doing them as if they are.
Your bad. Be ruthless in deprecating these items. If you're wrong, you can always add the items back.
e. Delegate: After you automate and deprecate, you'll be left with a bunch of important tasks that can't be automated and that you need to do. At this point, look at the hourly salary of the person doing them. Times that salary by 1.2x (for benefits and equipment) and then divide that number by 2,000 (the number of hours the average person works a year).
If a $100,000 employee updates a database with contact information and processes invoices for 10 hours a week, that is costing you $60 an hour ($120,000 / 2,000). A work-from-home executive in the USA would cost ~$25. In Canada, it would cost ~$15 USD. In Manila, it would be $5 an hour (and you would have a line out the door of folks who want that job).
The average $100,000 employee in America who implements the A.D.D. system will automate 20% of their job, deprecate 20%, and delegate 20%, in my experience.
This means every year, a high-functioning team should be able to free up ~50% of their cost/work on average (depending on how much you save when you delegate that 20%).
Why is this important now?
While these steps seem apparent, three things have made this framework critical:
Startup funding has collapsed by 75%.
Remote work has made all of us exceptional at managing and delegating work. Managing an American, Canadian, Argentinian, or Phillipino team member is the exact same on SLACK and Zoom.
Most importantly, ChatGPT, Bard, Claud, and countless emerging AI tools are making the automation of work accelerate at an absurd pace.
The great irony, I’ve learned, is that the remote workers from emerging markets are the ones embracing ChatGPT the most. It’s obvious why when you think about it.
These remote workers are typically working freelance for a dozen customers who only care about output. They’re very hungry, and they are absurdly customer-focused. They know that the faster and happier they make a customer, the more money they can make.
In conclusion
I’ve been working with our portfolio companies and our teams on this process for over a year, and it’s having dramatic results. This is a 1.0 framework, so please take it, remix it, and report your results to me.
We all want to do more meaningful work and we will always find new ways to be helpful to society.
PS - I’m going to start doing weekly posts here on Substack, to my x.com/jason account, and Linkedin. I am also planning on doing a paid subscription of some type to hire a full-time editor to work with me on these posts.
Will include some sort of subscriber Q&A and benefits as well (hit reply and tell me what you want). If you want to pre-pledge, you can do so at calacanis.substack.com. Which will give me some signal as to people’s interest.
Thanks for reading Jason Calacanis on Startups! Subscribe for free to receive new posts and support my work.
Also, many of you have asked me about the talks from the All In Summit. Instead of flooding the podcast feeds, we posted them to YouTube and X/Twitter.
On my other podcast, This Week in Startups, we’re covering all the progress in AI on Monday’s show with my pal Sunny.
All the best, JCal
twitter.com/jason
email: jason@calacanis.com for life
If you know of any early-stage startups looking for investment, please introduce me or send them to launch.co/apply (which will get them a meeting with my team).
Also, many of you have asked me about the talks from the All In Summit. Instead of flooding the podcast feeds, we posted them to YouTube and X/Twitter.
On my other podcast, This Week in Startups, we’re covering all the progress in AI on Monday’s show with my pal Sunny.
All the best, JCal
twitter.com/jason
email: jason@calacanis.com for life
If you know of any early-stage startups looking for investment, please introduce me or send them to launch.co/apply (which will get them a meeting with my team).
