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AI will automate 25-50% of white collar work including data analysis. Does that mean will data teams shrink in size?

On the contrary, while AI can automate some work, it will also demand much more from data teams.

Typical tasks - writing SQL & charting data - will become mostly automated. This ease of use will enable data teams to focus elsewhere : on the sea of demand for data coming from the edges of the company.

I’m watching public company earnings to identify early trends in the software market to inform startups’ plans for 2023. Yesterday, Microsoft & Google announced earnings. Amazon, Cloudflare, & Mongo announce soon.

At last, we see a change in slope in the annual growth rates of the cloud services. Both Google & Microsoft announced growth rates in GCP & Azure that held steady from one quarter to the next.

The Pilgrims who journeyed across the Atlantic to colonize America raised four rounds of financing sent via ship each year during the summer.

The second round of financing, the Series A, was the hardest to raise because the colonists missed plan : pirates pillaged their beaver pelts.

Free delivery to rural Americans created the retail catalog boom of the 1890s pioneered by Aaron Montgomery Ward. Catalog fraud soon blossomed.

To compete with Dr. John Harvey Kellogg, Charles Post founded a wellness clinic in Battle Creek, Michigan, which served Grape Nuts as a breakfast. The two companies would pivot to form two great cereal giants that would co-opt medical marketing techniques claiming to cure cancer with corn flakes to grow.

For many startups today feel like they are operating under dark skies. It’s supposed to be hard - you’re changing the world.

Reflecting on the last three quarters :

Startups have parted with colleagues to extend runway in a difficult fundraising market.

Some have significant balance sheets & discovered the ostensible product-market fit isn’t as strong as the business may have believed.

Muted valuation multiples have replaced the neon pink sticker price valuations of the early 2020s.

Last Monday, I published a chart that looked like this. It shows the standard deviation in Series A round sizes over time. I needed about 20 minutes using a language called R to create it.

Then I tried to replicate it using ChatGPT3’s Code Interpreter feature & I spent less than 5 minutes duplicating it, most of the time waiting for the computer (see video at the end of the post).

Large language models enable fracking of documents. Historically, extracting value from unstructured text files has been difficult. But LLMs do this beautifully, pumping value from one of the hardest places to mine.

We have a collection of thousands of notes researching startups. We are tinkering with deploying large language models on top of them.

Here are some quick observations about our initial experiments :

The Future is Constellations of Models. When faced with a search box, a user might ask quantitative questions. For example, how many people from Google have a met in the last month?

In There’s No Such Thing as Series A Metrics, Charles Hudson explains that there is no magic milestone to raise a Series A.

In this environment, I agree. The $1m ARR figure used to hold in 2018 & early 2019. But the data shows how much the market differs from a few years ago.

Series A round size standard deviation has grown by between 4-5x in 4 years.

Threads, Facebook’s newest social product & direct Twitter competitor, has surged to 70m monthly active users (MAU) as of this morning.

What does that mean for B2B marketers?

About 1350m users open the Instagram app every month. About 368m click on Twitter’s blue bird, 72% fewer.

Threads, launched on July 5th, counts about 70m or about 20% the size of Twitter. At 70m users, Threads current population is 5% of Instagram’s.

In August of last year, public markets switched from valuing SaaS companies primarily on growth to primarily on profitability. In the past two months, high-flying software companies have seen 40-112% increases in valuation.

I wondered if the public markets have begun to change the way they value these businesses.

The answer is yes - if you’re a top quartile company.

Yesterday, Databricks announced its intent to acquire Mosaic for $1.3b. Perhaps not coincidentally, Snowflake announced a deepened partnership with Nvidia to offer customers models & training on Nvidia’s Nemo platform.

Clouds are picking teams in one of the most important dislocations in software.

Cloud <- -> LLM Infrastructure
Microsoft <- -> OpenAI
Snowflake <- -> Nvidia
Databricks <- -> Mosaic
Google <- -> Anthropic
Oracle <- -> Cohere
Amazon <- -> HuggingFace