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As generative AI captivates Startupland, startups will do what they have always done: integrate new technology to build transformative businesses.

Incumbents have seized the moment with Microsoft, Adobe, & others integrating generative AI into their products quickest.

In response, startups must develop moats to stake out their market. What are these moats?

At the moment, capital & technical expertise create competitive advantage. Models require millions of dollars & technical expertise to deploy: document chunking, vectorization, prompt-tuning or plugins for better accuracy & breadth.

Sales cycles shifted dramatically in 2023. Slower sales cycles create pipeline shocks & startups are feeling the impacts.

The average startup saw a 24% increase in sales cycle from early 2022 to 2023. 60 day sales cycles are now 75 days.

But the latency isn’t evenly distributed. Startups selling to enterprises have increased 36%, twice those of Mid-Market & SMB focused companies. This figure is statistically significant with a p value of 0.0005.

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.