Substack, the email newsletter subscription business, today announced it will allow its writers and creators to invest in its startup starting at $100 and increments thereof.

Substack is looking to raise $2 Million at a pre money valuation of $585 Million.

They have 2 million paid subscribers, and 35 million subscribers, allowing for $300M to be paid to writers (their goal is writers keep 86% of the money earned from subscriptions).

You do not have to be an accredited investor (have over $1 Million in liquid assets) to invest in the round, and can invest at least $2200 or even start at $1000.

I think the valuation at $585M is rich, relatively speaking but I dont know all the numbers.

Here are some assumptions based on the data provided:

1. They are probably doing $150M to $200M in overall revenue given they have paid $300M overall to writers and have 2M paid subscribers. At an average of $7 per month per subscriber, it rounds up to $168M LTM (Last Twelve Months).
2. Their take is 10% or about $15M to $20M, which is their “actual revenue).
3. The growth rate seems tremendous, which I am assuming is over 100% YoY given 2 years ago they had only 100K paying subscribers.
4. So $20M in revenue, growing at over 100% YoY and you are paying 25X to 30X in Market Cap to Sales – Very rich, but this is the private market. They still are probably stuck in 2021 valuations.

The basic assumption I make when I form an opinion about new things (technologies, processes, startups, etc.) is that my opinion will have to change over time.

As the amount of knowledge one has increases, the first opinion becomes less relevant.

The last weekend I participated in hackathon at Surf Incubator. The focus of the hackathon was AI, or more in particular OpenAI APIs. Every team had 3-5 hours to hack a new AI app.

The one I chose to build was FashionGPT, which would take your selfie or photo and give you 3-5 options on how you would look with the latest fashion outfits from luxury brands such as Gucci, Giorgio Armani, etc.

It is a virtual trial room. You dont need to try new outfits, just see what you’d look like so you can share on Social media and get feedback before you decide to buy.

I worked with one other person, who quickly gave up and I complete the 3 modules – Javascript + HTML front end, Python at the back with Django on AWS. I pushed it to Github.

All the version 1 did was take your photo, then I asked ChatGPT for names of 100 top luxury brands, 100 top colors and 100 top outfits styles in 4 seasons (Fall, Winter, Spring, Summer).

The “prompt” to ChatGPT was a random combination of brand + color + outfit, using the create image endpoint, and then variations endpoint for 3 different colors and styles.

Until yesterday I had a very poor impression of the term “prompt engineer”. I thought that was a BS job. Since there’s no specialized “google searcher” role, why do you need a “prompt engineer”.

Turns out teasing information from LLM is a lot harder when you are not expressive. Most people are not.

I spend nearly 1 hour trying to build a random prompt base so the model could give meaningful new images from the existing set of images plus the “secret sauce” – the prompt.

“Prompt engineer” is a thing. I was wrong.

When you have a “Word document”, narrative style report – whether it is a PR/FAQ or a requirements document or any other:

1. There is a tendency to automatically “Email” the document for sharing, comment, feedback, etc. That is the first sign of trouble.

The document now becomes unwieldy. Comments, overwrites, tracking changes, etc.

2. There is a need to create a visual from a lot of writing. Which means some variables in the document (e.g. dates of multiple releases) need to be parameterized.

The document now requires manual visual creation. Also a pain.

3. There is a need to convert the “document” to a presentation for sharing with larger audiences.

The content now needs rework in a new (presentation) format.

Which is why I have now given up writing on Office 365 and instead moved all the documents to Google Docs style shared writing or Notion style Wiki (or will use Microsoft Loop)

I am going to write a series of posts on AI and in particular Generative AI. My focus is going to not be on the technology, but more the impact on specific jobs / roles.

Some assumptions I am making:

1. The generative AI genie won’t get put back into the bottle – meaning Governments cannot “regulate” companies to stop work on AI
2. There will be a host of winners and losers from this move to Generative AI – within each role and type of person.
3. While AI “evens the playing field for the “mediocre person” and the “good person”, the gap between the “great person” for a role and the others will only get larger with AI.
4. Most roles will change dramatically, not be completely eliminated. Unfortunately, instead of a company needing 10 product managers, they might be able to achieve more with fewer (5 or even less)
5. A small number of people (< 5% of the 1B on LinkedIn are active monthly users) are already using Generative AI in some form (ChatGPT, Jasper.ai) in their work already.

I am going to start with the Product Manager (PM). Specifically the technology software product manager. Not a Director or a Vice President, but just an individual contributor in a software company.

Most PMs (should) do 5 things well.

1. Assess customer needs and determine how problems customer’s have get translated into requirements
2. Prioritize what gets built by engineering / technology teams
3. Price, Position and frame the product – enabling marketing and sales teams to promote and sell
4. Collect customer feedback, track competitive landscape & measure profitability & market share
5. Train sales & support teams on product and resolve issues to incorporate into future product roadmap.

While the top 5 sounds very strategic and important, the day to day is filled with drudgery of joining tables, making queries on multiple databases, Excel wrangling, Document writing, rewriting and rewrite the rewrite.

Created with MidJourney: a man with the drudgery of working with Excel, multiple queries, doing lots of data analysis

With almost every product that a PM uses daily – including Microsoft Office, Salesforce, HubSpot, Atlassian, etc. all announcing Generative AI in their products, the “drudgery” should go away, making most PM more productive.

Which leads to fewer PM. While AI might not “eliminate” jobs, it will still displace many junior PMs.

So how can you future proof yourself?

1. Index on customer interactions, building customer trust and traction more than ever.
2. Aggressively use as much Generative AI in all you do with the intent to be more productive.
3. Research and keep up with trends and technologies outside your core functional PM job

Most everyone has probably heard of or seen the Awareness & Knowledge 2X2 matrix. Often quoted, the “unknown unknows” are the ones that are said to be the cause a lot of angst.

Lets say you work at a startup in the Silicon Valley (SV). And you know about Silicon Valley Bank (SVB). It is the “banker to the startups”.

Most startups have their first checking account with SVB and continue to maintain that relationship as the grow, since they offer Venture Debt, Line of Credit and other products that most “mainstream” banks wont offer to SV startups.

You may also know that all banks make money by lending money at a higher interest rate than the rate the pay for their deposits. The difference is their revenue or “Net Interest Income”.

In 2020-2021 deposits for SVB grew significantly. From about $69 Billion to $189 Billion.

SVB, like most other banks, has to now “invest” that money into safe deposits – treasuries paying a low rate in 2021.

Fast forward to today and the rates are MUCH higher. Fed rates went up too high, too quick.

So the “safe investments” that SVB had in treasuries are now not worth as much any more. In fact they decided to take a loss of $1.8B. Which is a very small amount of money relative to their deposits.

To cover for those losses they were planning to sell stock to the tune of $2.5B.

Some account owners decided to withdraw their money from SVB – “To be safe”. That created a panic – called a Bank Run.

Well it turns out a lot of startups pulled money out of the bank. $42 Billion to be exact. Many startup founders mentioned their venture investors suggested they do it.

Thanks to the bank run, today, FDIC decided to fold SVB, which means every account with < $250K ( federal deposit insurance limit), is clear but those with higher deposits (92% of accounts) are stuck. Why did the FDIC do that? That’s because SVB no longer had funds to support the bank run.

But, those companies who raised a lot of money and kept it “safely” in SVB, will have to wait until after Monday when FDIC will find a new mechanism to get them the money.

You are still a startup employee, whose company has an account with SVB.

You did not know the exposure to bonds would now create a miss to your paycheck next month. Hopefully FDIC finds a buyer for SVB and keeps the entire bank “alive” – on Monday.

Historically, however from FDIC, “most bank failures for non-insured accounts got back 10 cents to 20 cents on the dollar deposited”.

In the last 2 days their stock has taken a big beating (down 60% in day 1 and another 60% day 2).

What you dont know.

There are hundreds of “job listing websites” from AngelList to Ziprecruiter and LinkedIn to Indeed. The top 25 have consistency in their search, job listings (number of available jobs) and information about the job.

They all have the same user interface. I understand the value of simplicity and customer experience, but this is an area ripe for innovation.

1. ZipRecruiter – Search Title or Keyword, and location.

2. Monster.com – “remote” is the only different word

3. Simply hired – same except for “Job Title, Skills or Company”

4. CareerBuilder – adds Military Code

5. SnagAJob – at least the background is not plain

6. Craigslist – at least the location is predetermined for you

7. USA Jobs – government jobs, but same

8. Robert Half

8. Job.com

9. Google Jobs – the navigation that it provides begins on the top with one search bar

10. Indeed – more of the same

11. Glassdoor – Browse instead of search interface

12. LinkedIn – Single search bar for jobs, even though they know a lot more about you

Is this what candidates want in 2023?

Most of the younger people I talk to dont seem to care about title and are happy to take on a different role than their past might indicate (unless it is a job that requires you to be local e.g., cook, bartender, etc.).

What candidates do care about is:

1. Good manager
2. Company culture
3. Decent pay
4. Growing industry
5. Flexible hours
6. Health benefits
7. Professional coworkers and colleagues

What surprised me is even LinkedIn and Glassdoor not start with those elements, although they know that people care about these other aspects of the job more than location or job title.

If you were trying to build a new job board or website, I think you need to start with the meta data around those elements of the job first, although some maybe easy and others harder to obtain.

They way I would start is with the job posting. The company ( or individual) has to complete those sections (including pointing to Yelp-like reviews of the manager) such as culture, flexibility, benefits first.

That would allow you to help candidates filter by those criteria, or use a wizard-based interface to guide candidates through those questions before you help them with the right role or job.