Category Archives: AI

AI, Startups, Tweetstorms

Help Wanted? Hire my software!

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Originally posted as a Twitter thread on October 08, 2024

Help Wanted? Hire my software!

Airbnb famously grew by “[growth] hacking” Craigslist — automatically responding to listings to encourage a cross-listing to Airbnb:

https://hackernoon.com/how-airbnb-hacked-craigslist-for-viral-growth-24l35eg

As software “becomes” labor (https://a16z.com/ai-turns-capital-to-labor/), we will see similar hacks to sell software — responding to job postings with software products that do a meaningful percentage of the job’s responsibilities. “I know you’re looking for a ‘Bachelor’s Degree preferred with 5 years of experience X’, but our AI-powered software product can do everything you need, is fully trained, and only costs $20,000/year…and can start tomorrow.”

Try going through Craigslist or Monster for job listings — and notice for each job how many of the responsibilities could be done with AI *in its current form* or where AI will be very soon, particularly with more integrations…here’s a local optometrist:

One of my favorite restaurants where I live uses *zero* system for reservations. You have to call, they’re closed in the morning, and the number is always busy during peak dining times. I asked the owner — why not use an online reservation system? They’re so inexpensive now!

His answer: “We are *always* at capacity. We have never had a day where our tables are not full. This would just be an additional expense, and the employee who answers the phone is needed to greet/seat diners anyway — so the reservation taking has no extra cost.”

I asked him: “What if she retires or quits?”
“Well, then I’d hire somebody else”
“What if a software products could do everything she did, for half the cost, spoke 100 languages, never called in sick, and was never late. Would you hire that ‘product’?”
“That sounds crazy, but I guess?”

We’ve already started to see some of this. AI-powered products focused on specialized “complex workflows” are taking on tasks like the ones seen in the prior Optometrist advertisement. And some technology-laggards are adopting these tools first because (like with my restaurant example) they’ve just avoided tech because it’s felt like an extraneous expense…

AI, Economics, Finance, Startups, Tweetstorms

New Essay: The Transmutation of Capital into Labor

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Originally posted as a Twitter thread on August 22, 2024

New Essay: The Transmutation of Capital into Labor

https://a16z.com/ai-turns-capital-to-labor/

The first era of software took analog files, digitized them, and made them accessible with a specialized interface. Think PeopleSoft for HR files, Quickbooks for ledgers, Epic/Cerner for health…

This has played out for 50+ years as more industries have moved to running on software, not files. Cloud lowered the adoption barrier. Adding financial services to cloud made more markets “big enough” for specialized companies (e.g., Toast, ServiceTitan) to exist.

But the same humans that acted on the analog files now act on the digital files! And sometimes it’s impossible to align hiring and training (of those humans) with business needs.

This is what’s exciting about AI. It’s not filling software budget. It’s filling “labor” budget.

Wages in the US alone are $10T+ per year. The worldwide software market is a few hundred billion dollars.

The original “digital filing cabinet” winners have a tremendous amount of potential to add AI, but also have a daunting task of shifting from “per seat” pricing to “per outcome” pricing. Zendesk monetizes per seat. What if a business needs 95% fewer seats because of AI?

Some of the biggest startup outcomes will likely be “net new” industries where a business runs on nothing but Excel…because the software budget was small, the human budget large, and the ability to hire humans was so hard…think compliance officers at a bank.

There’s a saying in economics: “the cure for high prices, is high prices.” As the price goes up, more widgets get manufactured, which increases supply, which lowers the price.
But when it comes to humans and wages, there’s too much latency because of training, licensing, etc.

AI will largely augment employment, and fix many of the “market failures” present with highly skilled yet episodic labor. Imagine: I need your skill for 3 days a year (peak demand), but you need to go to school for 3 years to earn it.

AI, Economics, Startups, Strategy, Tweetstorms

Outcome Based Pricing

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Originally posted as a Twitter thread on June 21, 2024

Can’t wait to see the first “incumbent” (in a large software field…like support, CRM, HR, etc) switch from “per-seat” pricing to **per-outcome** pricing.

I’m writing an essay on this now, but consider Zendesk at $115/seat per month…or ~$1.4M/year for 1000 agents:

Let’s say an agent is paid all-in $75,000/year and answers 2000 tickets per year.

This makes the human cost of a ticket $37.50, and the software cost $.69.

The human cost obviously massively outstrips the software cost…and unlike software licenses, it can take months to “install” (find, hire, train) a human to occupy that seat. And in many areas there is simply a dearth of qualified humans given licensing latency

In other words, you can’t simply lift wages and produce more workers…if it’s a role that requires licensing or sufficient training (think mortgage brokers, nurses, etc)

Not to mention the fact that it’s hard (and cruel!) to “flex” humans. Southwest Airlines can’t hire tons of humans when bad weather threatens to cancel flights and then fire tons of humans when weather is clear. But software is perfect for this

So: given the rate of improvement in AI for asynchronous support — what will it take for Zendesk to switch from (in the prior example) $115 per seat per month to, say, $10 per successful ticket answered BY Zendesk? Still much cheaper, more flexible, instant provisioning

It’s obviously going to happen, but how should they price this — it’s the ultimate example of value-based pricing? How to have this interact with existing “seats”? How to have teams not feel threatened by their new AI colleagues filling “seats”?

Whole industries will change, and new ones will be created now that software can produce the outcome vs simply be the tool.

Salesforce charges per-seat pricing for salespeople…why not charge per sale?
Maybe Workday can charge for HR “resolutions”
Etc

AI, Fintech, Payments, Tweetstorms

How AI Will Erode Bank Profit Pools

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Originally posted as a Twitter thread on May 17, 2023

I’ve often written about how friction/inertia preserves giant gross profit pools in financial services.

The missing link to change this is what I would call a “consumer signup RPA” — which AI can do

RPA: Robotic Process Automation. Take an “API-less” process and “just do it”

Nowhere is this more true than depository accounts. A 4 week Treasury Bill from the *US Government* pays 5.49% and a 1 year Treasury Bill pays 4.73%.

How much does the biggest bank in the US pay for the same…which of course is insured by the same US Government for ONLY up to $250K?

.02% and 3%, respectively…for a higher level of risk. You’d have to be insane to choose a CD with Chase vs a T-bill.

So WHY do consumers leave excess money or buy CDs with Chase? Three reasons:
1. They don’t know what yields are (Chase takes advantage of them)
2. It’s too hard to buy T-bills directly (try signing up for http://treasurydirect.gov)
3. It’s too hard to move money back and forth

The promise of Fintech (and in particular, tools like @Plaid) is that friction/inertia will no longer be an impediment towards consumers switching from the worst services to the best services.

Round One of this was “tools to read” information — let’s import your credit card purchases, or read your checking account number in.

Mobile Wallets have the promise of being a platform for financial services (the App Stores equivalent = financial products). I wrote about this back in 2016:

https://a16z.com/2016/04/25/digital-wallets-fintech-platform/

But AI is also going to transform this, because the incredibly painful (consumer) process of, say, buying short duration T-bills directly from the US government could now be…very easy. Or the seamless movement of money to meet bill pay needs and invest excess cash.

And the missing link for all of this has its technological answer in the form of Generative AI. AI has been used extensively in fintech, but primarily for “scoring” and “approving” things — speeding up backend processes.

But Generative AI is the mirror image: help automatically answer things on behalf of a consumer, bringing a generative robot to a 1990s workflow from a bank (or government) that’s unlikely to embrace, say, RESTful APIs.

And it’s not just about seeking higher yield or lower debt cost, which are particularly salient in today’s higher interest rate environment. Friction/inertia also keep people on their metaphorical financial Flip Phones vs meaningfully better products and experiences

Gen AI also has cost-saving, transformative opportunities for the big guys, too. But if they keep ripping off their customers, they’re finally going to start paying the price as “assistants” make breaking up easy to do…

AI, Economics, Finance, Strategy, Tweetstorms

The “Finance” Opportunity of AI

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Originally posted as a Twitter thread on January 27, 2023

What is the “Finance” and “Financial Opportunity” of AI?

If “Bit Manipulation” is a key part of your COGS or SG&A, there’s a huge opportunity or huge disruption coming your way (or a PE firm that might just buy you).

Two sections follow: “Known Knowns” and “Known Unknowns”

Known Knowns: There are companies already doing X, and thus there are two opportunities:
-sell a tool to turn “bit-manipulation-by-people” costs -> GPU usage (AI base marginal cost)
-create a vertically integrated company that competes with a legacy player…by doing the above

Financial services (unlike, say, Campbell Soup or Boeing or Fedex) are primarily “bit manipulation” — little atom moving needed!

How do you apply for a mortgage? Insurance? Reinsurance?

A lot of the cost is…movement of bits. Move info from here to there, validate X, etc.

Companies, and people within companies, tend to be extraordinarily slow routers of information. Person X emails Y, who’s on vacation…who upon return asks for more info, and then passes it to Z, etc. Do it more quickly, save money and win share.

There’s a tremendous private equity opportunity here, which is the “finance” opp. Any company might see a *dramatic* difference in bottom line once more of these bit-manipulation functions are automated. It’s like going from seamstress -> loom -> textile factory…for bits.

Next: Known Unknowns. What I’m fascinated with are companies that cannot/do not exist today due to a market failure between what companies/consumers will pay and what people will work for…in the realm of bit manipulation.

For example: “Find all counterfeit listings of my product on Reddit/FB/Twitter/forums, for $100K/year” or “Reach out to unhappy customers and get more information, for $100K year”
There’s probably lots of demand at a given price but impossible to provide service at that price

So there are no “market comparables” or set of companies to look to. It’s just an old fashioned supply/demand curve where there’s no quantity demanded at the price where labor is willing to supply…

Working on an essay on this with some data from existing companies — more to come soon.

AI, Economics, Regulation, Tweetstorms

Bureaucracy is a Regressive Tax

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Originally posted as a Twitter thread on February 11, 2021

Bureaucracy – in government, the medical system, and more – is a HIGHLY regressive tax in that rich people can pay to solve problems, and the poor must use their time, miss work and lose income…and more.
This is why I love @DoNotPayLaw + @jbrowder1

This is not hyperbole…

I had to go to the ER a few months ago. My bill didn’t match my insurance statement. Insurance company tells me not to pay. Provider threatens to report me to collections. This consumes HOURS of times and damages credit, making borrowing (and living!) more expensive

I am lucky to be able to say “it’s not worth my time” and do just fine — either pay it or deal with the consequences, which are insignificant to me. Millions cannot.

AI, COVID, Education, Tweetstorms

Remote Education

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Originally posted as a Twitter thread on July 30, 2020

There’s an opportunity to turn remote education from a weakness to a strength — from a badly rendered “sage on a stage” (constant in education for 100s of years, but *worse* online!) to individualized instruction. To see why, let’s take a trip to 1984 — not Orwell, but Bloom

Prof Benjamin Bloom wrote a seminal work in 1984 showing that individualized instruction lifted outcomes by 2 standard deviations — outperforming 98% of regular students:
http://web.mit.edu/5.95/www/readings/bloom-two-sigma.pdf
But he remarked, it was “too costly for most societies to bear on a large scale”

But the Internet has solved this problem, conceptually! What we need(ed) was a forcing function to abandon the status quo, which Bloom showed is demonstrably worse than individualized tutoring. We potentially have that in Covid, which has incredibly made the status quo *worse*

Homeschooling was “weird” and “dangerous” (https://news.harvard.edu/gazette/story/2020/05/law-school-professor-says-there-may-be-a-dark-side-of-homeschooling/) but now parents get to see (Zoom-spying!) how ineffective the “status quo” is — and speaking as a parent who knows the Bloom data and the traditional/dumb homeschooling stigma, I now care only about the data

Schools have (had?!?) one big thing going for them — kids learn how to socialize, to get along with other people, to deal with adversity, unfairness — side note, but this (school!) graduation speech by Justice Roberts is the best ever: https://time.com/4845150/chief-justice-john-roberts-commencement-speech-transcript/

But Zoom school has none of this. It’s worse in every way than what was already a proven-to-be-suboptimal model for education!

I hope some forward thinking schools will try to go on remote education offense, whereas most are just going on “how do I turn this thing on?” defense.

I encourage everyone to read the Bloom paper. We now have the means (so many great tutoring platforms for a fraction of the cost of private school). We have the motive. And with Covid, we have the opportunity. Fin.