Proofread Anywhere – teaches people how to make money online as proofreaders
Female founder was face of the course
One-time fee, various tiers
Community access
Smaller courses as side offers
Buyer didn’t think of it as just a proofreading course, but as one of many ways to “make income online”
$500 course is main offer
How can she charge that much?
-Premium positioning -Large audience, with existing brand affinity
-Course has a good reputation
Launched in 2014
Founder is Caitlin Pyle 50K people have done it
Backend uses Clickfunnels
Well-known in Clickfunnels community
Buyer was already familiar with her brand
She started as a proofreader herself, teaching her own experience and story
Big risk if buyer takes over a brand whose founder is the face
In this case, Caitlin created all the content, but she wasn’t running the business – already had a professional operator
She wasn’t actively marketing it, either — mostly from Facebook ads
She’d already created 6-12 months of ad creatives They bought rights to use her image for 2 years after acquisition
Buyer had previously done a similar transaction – had sold his own business and was face of that brand, saw it play out successfully
One way is slowly transition a new face in
Did it with a podcast host before
“Most people don’t care”
New users won’t really know or remember
Plan to hire some of her best students as brand evangelists – already 50K (or 15K?) students Could be even more powerful story – took the course and now make living as proofreader
Most users’ intro to brand is a free webinar, free workshop – but stepping up immediately to $500 course can be jarring Want to implement a lower priced ($29) offering
Downside of Udemy – difficult to build sales funnel to really grow students (top classes on Udemy have say 1000 students)
Proofread Anywhere uses Clickfunnels
Buying a course and taking it off Udemy can be risky – but could be potential strategy
Must read if you’re interested in AI and its implications; Tyler’s commentary on the recent explosion of AI into the popular consciousness (driven in large part by ChatGPT) has been, in my view, the most realistic+pragmatic:
“I don’t have a prediction for the rate of improvement, but most analogies from the normal economy do not apply. Cars get better by some modest amount each year, as do most other things I buy or use. LLMs, in contrast, can make leaps.”
“I’ve started dividing the people I know into three camps: those who are not yet aware of LLMs; those who complain about their current LLMs; and those who have some inkling of the startling future before us. The intriguing thing about LLMs is that they do not follow smooth, continuous rules of development. Rather they are like a larva due to sprout into a butterfly.”
He doesn’t read the news
Likes trolling on Twitter…”Twitter’s fun”
“Twitter’s gonna be fine”
HIS INVESTMENTS
400 personal investments, a few thousand including YC
All the companies he’s added value to are those he thinks about in his free time – while hiking, texting the founder an idea
Most successful investment? Stripe on a multiples basis
Helion – fusion energy
Personally invested $375M (!)
Other thing besides OpenAI that he spends a lot of time on
New energy system that works on super low cost Hardest challenge is how to replace all (current) generative capacity on Earth really quickly
“Who can deliver energy the cheapest, and enough of it”
Simple machine, affordable cost, reasonable size
If fusion works…will change dynamics of what’s possible – enables more downstream (eg, more powerful planes)
Hermeus – supersonic jet company
Led $100M round
Was also involved with a competitor Boom – but different tech and approach
Huge market with multiple needs
Worldcoin
He’s a cofounder, on the board, but not day to day involved
Will tell its story soon – believes it will go over well (unlike earlier negative media coverage) We give up more privacy to Facebook than Worldcoin
Phenomenal team
Launch in months
Interested in any tech to experiment with global UBI (versus what one country can do)
Re: crypto — “honestly not super interested” “Love spirit of web3, but don’t intuitively feel why we need it”
Inception Fertility
In-vitro gametogenesis
In shadow of AI Next 5-7 years of biotech will be remarkable
Human life extension – “yeah maybe that’s gonna work”
Investing for 20 years, president of YC for 5-6 years
Garry (new YC president) will do a lot of things differently and be wildly successful
Last few years were really hard for YC YC can remake itself now – tourists are leaving now
—
ARTIFICIAL INTELLIGENCE
OpenAI has pulled together “most talent dense” AI team
“Gonna be tremendously good”
Why did ChatGPT and DALL-E so surprise people?
“Don’t know…reflected on it a lot”
If you make a good UX on top of something – believed users wanted to interact via dialogue
Pieces were there for awhile
Standard belief was AI would take over low skill / truck driving / generic white collar
Going exact opposite direction – taking over creativity where we thought humans might have special sauce
It’s not an intuitive finding
Released GPT-3 three years ago – thought ChatGPT would be incremental, was surprised by public reaction
ChatGPT will cause societal changes – eg, academic integrity “Stakes are still relatively low”
Covid did show us society can update to massive changes faster than he expected
Given expected economic impact – “more gradual is better”
GPT-4 will come out when we’re confident we can do it safely and responsibly
Will release tech much more slowly than people will like
GPT-4 rumor mill is a ridiculous thing
Re: ChatGPT – built a thing, couldn’t figure out how to monetize it, put it out via an API, and users figured out how to use it
Would like to see AI super democratized, have several AGIs in the world Cost of intelligence and energy trends down and down
“Massive surplus…benefits all of us”
Believes in capitalism – best service at lowest price
Society will need to agree on what AGI should never do
Broad absolute rules of the system
Within that, AI can do different things – safe for work one, edgier creative one – different values they enforce A user can write up a spec of what they want, and AI will act according to it – “should be your AI…to serve you”
Microsoft – only tech company he’d be excited to partner with this deeply
Satya, Kevin Scott, Mary McHale
Values-aligned company
“We’re very much here to build AGI”
“We wanna be useful to people”
Re: Google’s AI – hasn’t seen it, assume they’re a competent org
We’re in a new world – generated text is something we all need to adapt to, like we adapted to calculators
“I’d much rather have ChatGPT teach me…than read a textbook”
Anthropic – rival AI, stressing an ethical layer
Very talented team
Multiple AGIs in the world is better than one
Society decided free speech is not quite absolute – in similar ways AI / LLMs will need to have bounds too
Video is coming… no confident prediction about when Legitimate research project – could take awhile
AUDIENCE Q&A
When fusion online?
By 2028, could be plugging fusion generators into grid (pending regulators)
Re: AI worst and best case?
“best case is so unbelievably good that it’s hard to imagine, discovering new knowledge in a year instead of 70K years”
“Bad case is lights out for all of us” More worried about accidental mis-use in short term, less about the AI itself being evil
How far away is AGI? Much blurrier and gradual transition than people think
Re: state of San Francisco
Real shame we treat people like this
How elected leaders don’t fix the problem
Tech has some responsibility for it
But other cities do better than this Super long in-person work and Bay Area
Re: ChatGPT reaction
Expected one order magnitude less hype, users, of everything
Less hype is probably better The tech is impressive, but not robust Use it 100x, see the weaknesses
How Sam uses ChatGPT? Summarize super long documents, emails
For translation
Re: Google code red, threat to search
When people talk about new tech being end of a giant company, they’re usually long
Change is coming (for Google), but not as dramatically as people think
Before Google, memorizing facts was important – and now we’ll change again – and we’ll adapt faster than most people think
Prefers hybrid work, like YC – few days at home, few days in office
Skeptical that fully remote is thing everyone does
Most important companies will still be heavily in-person
Safety engineering for AI is different from standard safety engineering – consequences are greater, deserves more study
Raising capital now is hard, especially later stages – but other things easier – easier to rise above noise, hire, get customers What he’d do now — recommends for founders – “do AI for some vertical”
Advice for AI startups
Differentiate by building deep relationships with users, some moat like network effect
Plan for AI models continually improving
OpenAI is a platform, but also wants to do a killer app (platform + killer app) to show people what’s possible
Guest: Tim Ferriss
Host: Carly Reilly (w/ Bankless)
“The way you do anything is how you do everything”
Experimented with NFTs for last 2 years
Describes himself as writer or podcaster to unfamiliar people
Very competitive person – wants to suffer a little
Cockpunch – origin story
-Started w/ desire to be less precious about creative projects, looking for joy and fun and laughter
–Likes playing with new technology sandboxes
-Was drawing characters with gauntlets – the name Cockpunch popped into his mind
-Lets him play with 3d modeling, rigging, voice acting, music – lets him acquire skills that can be transferred to other places – vehicle for learning
AI art competition
-entrants had to show their work
-based on Cockpunch characters
-teaching himself – and then teach others
Chose fiction to let himself focus less on metrics, a “quantitative prison”
“Most people who want feedback…want positive reinforcement”
In any new space, tries to find someone with 10K foot view across many projects to get advice
Lots of folks get lost in weeds with NFTs / web3
Decided on 5555 mints – wanted to make sure it sells out
“There are a lot of whiny bitches in web3”
Likes advice of Scott Adams (Dilbert creator)
Thinks in terms of 6 month projects and 2 week experiments
Snowball of relationships and skills from project to project
Created term “Emergent Long Fiction”
Fiction lets him learn from new people
Set a few conditions upfront – a few characters, realms, drivers
There’s competitive games But where it goes from here – he doesn’t necessarily know (hence “emergent”)
Set constraints and explore how creative you can be
Most people don’t know what they want
Hard to get clear signal when you ask a large audience what they want
Bullish on tokenized assets and digital scarcity
Been thru many cycles of tech
Always some new tool / platform that people say you have to use (eg, Vine)
“Assume there’s always a market for quality in any medium — and just get fucking great”
Web3 isn’t going away
But NFTs – he doesn’t know – it’s one of the meanest most aggressive communities
In this bear market, he’s down 70% net worth – but it doesn’t entitle him to behave like an asshole
Public perception of NFTs (in his audience) has soured tremendously – like a dirty word
But he likes to cull his audience from time to time if they don’t have patience or understanding
Cockpunch as an unlock has exceeded all his expectations – relationships, what he’s learning
Fiction doesn’t always mean a novel – it means story telling
Didn’t plan to do a Discord – it self-organized
In Discord – use your Cockpunch NFTs, with attributes – uses ChatGPT to write a match summary (blow by blow) of a cock fight
Others added music, voice commentary
New book: Kluge, the haphazard construction of the human mind
Hamlet: “what a piece of work is man…how noble in faculty”
Bertrand Russell: “it’s been said man’s a rational animal…all my life I’ve been searching for evidence that could support this”
Argues man is the RATIONALIZING animal (not the “rational animal”) – searching for reasons to explain why we do what we do
Default thinking is that natural selection leads to human optimalism
But how to reconcile with the manifest clumsiness of the human mind?
Visual system evolving for a billion years
But distinctively human things – like talking, rational deliberation – these are much more recent (eg, 50-100K years ago)
Hill climbing metaphor – issue of local maxima
Evolution won’t necessarily lead to superlative adaptation
Human spine is a kluge – but not best way to support bi-pedal creature, leads to back pain / fragility – eg, multiple columns would be better solution
Evolution builds kluges because it has no foresight nor hindsight – it’s effectively blind
Evolution is always in a hurry – shipping deadline of “now”
Darwin didn’t say “survival of the fittest” – what he meant was fittest of the available options
It’s really “Descent with modification”
Bird’s wing is a modification of the forelimb of all 4-legged creatures – wasn’t designed from scratch as best possible wing
Concept of “evolutionary inertia”
Genes are conserved Evolution is a tinkerer using spare parts
Kluge is about 3 things
1. Limits of human mind
2. Where they came from
3. What we can do about them
Computer memory – there’s a master map of where everything is stored – like a series of safe deposit boxes
Stored once, saved forever
Human memories are nowhere near as reliable – there’s no master map
Human memory balances 2 things: RECENCY and FREQUENCY
That’s why you often forget where you put your keys, where you parked your car
That’s why pilots use checklists to make sure they do all the required tasks Evolution didn’t bless us with an erase feature
Brain uses a broadcast system to retrieve info and memories – doesn’t know where individual memories are
Memory is context dependent – if you study while stoned, you might be better off taking test while stoned
Even your posture (eg, seated or standing) can affect memory recall (!)
Seems to apply to rat + maze experiments too
Eyewitness testimony is particularly subject to these memory errors
Shooting incident with 30 eyewitnesses where the witnesses cannot agree about what happened
Framing: “estate tax” versus “death tax”
Garbage in > garbage out
We take biased samples of data and reason from those limited samples
Confirmation bias – eg, religious beliefs, presidential elections
Depression – being depressed means you’re more likely to have depressing thoughts, negative spiral – normal brains have ability to stop this process
Languages have lot of ambiguities – “the spy shot the cop with the revolver”
Moral dilemmas – trolley problem – a person’s judgment can be affected by how messy the experimental room is!