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The hardest round to raise so far in 2023 is the Series B. Although, all the early & mid-stage rounds have fallen to levels not seen for 5-10 years.

Q1 volumes by year show broad declines across early-stage venture capital. Seeds peaked at 1500 in Q1 of 2020 falling to 155 in Q1 of 2023.

In late 2021, Office Hours welcomed Claire Hughes-Johnson, former Stripe COO & VP at Google. During that session, she alluded to a book sharing her expertise in building exceptional teams at two of the most successful startups.

That book, Scaling People : Tactics for Management & Company Building. is a book a management team could take to an offsite to develop or re-imagine the entire operating system of a business.

The book starts with a company’s founding documents, expands to the operating cadence, and culminates in the business’ operating system.

Within the span of a few days, Startupland has experience an extraordinary set of events. The collapse of Silicon Valley Bank & 2 two others, then the intervention of the US Treasury to backstop deposits.

During that time, founders & management teams responded with tremendous fortitude under pressure, developing contingency plans to assure the success of their businesses - yet again!

It was an inspirational moment - and a challenging one.

With all the broad macro economic shifts, startups are pursuing their core markets much differently in 2023 than in 2022. To illuminate those trends, I’ve constructed a brief, 28 question go-to-market survey here..

My goal is to understand how startups have evolved their sales, marketing, customer success, and cash management from the go-go days of early 2022 to 2023. Then to publish the results & answer questions about them at an upcoming Office Hours.

As machine learning becomes core to every product, engineering teams will restructure.

In the past, the core engineering team & the data science/machine learning teams worked separately. The core engineering team ships the product & focuses on reliability.

For most companies, the data science team analyzed data & wrote machine learning models to support the business functions : sales, marketing, customer support. These teams operated downstream of the data warehouse. But they are movin’ on up to work on products in front of the data warehouse.

Over the past week, I put ChatGPT to the test, enlisting it as copy-editor for a forthcoming blog post.

Here was my process:

• I dictated a blog post outline into a Google document
• I prompted ChatGPT to revise the post for clarity & pasted the text
• I copied ChatGPT’s response, edited it some more & consulted ChatGPT for three rounds just like John McPhee

So, does a robot copy-editor work in practice?

In August, I wrote about why Omni’s technology reinvents BI once more. The Omni founding team hails from Looker & Stitch. They’ve set out to solve the problems customers faced with the previous generation of BI.

Today, I can show you what this means in practice because Omni is commercially available.

Anyone who has managed a larger BI deployment has faced the challenge of managing hundreds, perhaps thousands of metrics. As more users calculate figures, consistency across teams becomes a company-wide challenge.

The FTC reportedly will sue to stop Adobe from acquiring Figma. Similar questions have surrounded Microsoft’s acquisition of Blizzard; The US Department of Justice seeks to unwind the Google/DoubleClick merger; British regulatory bodies forced Facebook to reverse its Giphy acquisition. Visa abandoned plans to buy Plaid after facing a suit.

We’re entering a period wherein governments regulate large technology businesses more actively. Startups evaluating M&A have additional factors to consider.

I served on the boards of two companies that plodded through regulatory review. Looker & Kustomer each spent roughly a year waiting for approval.

In CloudFlare’s latest earnings report, the management team highlighted the strength of enterprise buyers within their customer base.

I wondered if this were broadly true. Do public software companies with largely enterprise customer bases benefit from superior growth to their peers with mid-market or SMB focuses?

Enterprise & Mid-Market public companies have seen a relatively constant decline in growth rates through the last six years. SMB businesses benefited from a post-Covid surge when the US re-opened - a phenomenon that seems to abate with time.

I’m watching public company earnings to identify early trends in the software market to inform startups’ plans for 2023. Yesterday, Cloudflare announced earnings. I’m adding Cloudflare to the list of tracked companies for this series.

CloudFlare’s annual growth rates haven’t slowed in the 5 quarters, unlike Microsoft, Google, & Amazon’s growth rates.