Wow, summer has come and gone and with that many a founder is prepping for the post-Labor Day fundraising push. This post is not for the latest and hottest, brand new AI companies but more for the founders going from seed to A. IMO this is so much harder to do at the moment versus starting a new co from scratch and raising. To that end, I’m resurfacing a post from early this summer, June 3, to prep you for Q4 “The seed to A fundraising log jam and the importance of Big Mo.”
What's 🔥 in Enterprise IT/VC #344
As an enterprise founder going from seed to A, how do you stand out?
In addition, you may want to arm yourself with the latest and greatest SaaS benchmarks. I clipped a few charts from the SaaS Growth Report from ChartMogul and added some commentary. There are so many 💎 in this report, and I highly encourage you to read the rest here.
Chart #1 shows the time to reach $1M ARR from first sale. 🔑 here is from first revenue meaning that for many developer first or infrastructure cos which require a much longer time domain to build a product and community, the 9 months could represent more like 2-3 years to get to the first $1M.
IMO, it’s not getting to the first $1M, it’s more about do you have an early semblance of an ICP and repeatable way to grow that base from $1-3+M. This has not changed much from my thoughts in 2019 👇🏼.
Once you get dollar 1, get ready to run 🏃🏼♂️ fast! Some folks I know may hold off charging their initial customers for a few months to make sure the momentum for more customers is sitting right behind that first dollar (once again read What’s 🔥 #344 from earlier this summer to show the momentum).
Next question how long does it take for the best to go from $1M - $10M - still 3 years which is pretty phenomenal. Going back to my point above, waiting to charge until you see what is behind dollar 1 can help you get there faster. This allows you to work out product kinks with a few key design partners, better hone your value proposition, and also figure out the initial ICP (ideal customer profile - more on that below). When your initial design partners are happy and can’t live without your product, you can turn on the revenue switch for them and hopefully have a nice list of others ready to get started. Momentum and velocity matter after dollar 1 and the first $1M. I know a number of infra cos at moment, despite the slowdown in B rounds, raising at $150-400M post with this kind of profile - $1 to $3.5-4 to $4 to $15+…Yes, these are absolutely insane prices in which to grow into, but it is still happening in the market for a select few.
As always, 🙏🏼 for reading and please share with your friends and colleagues. Happy Labor Day and good luck on your fundraising!
Scaling Startups
Reminder: Focusing is about saying NO!..great video clip from Steve Jobs
Lenny Rachitsky continuing series of how successful B2B startups got going - this one on ICPs (Ideal customer profile) is 🔥 and something many founders miss
AI IMO not a category but if you want to raise $$$ in 2023, this says it all - 25% of all VC investments going to AI-related cos
Enterprise Tech
🤯 OpenAI Passes $1 Billion Revenue Pace as Big Companies Boost AI Spending - Need I say more? (The Information)
The billion-dollar revenue figure implies that the Microsoft-backed company, which was valued on paper at $27 billion when investors bought stock from existing shareholders earlier this year, is generating more than $80 million in revenue per month. OpenAI generated just $28 million in revenue last year before it started charging for its groundbreaking chatbot, ChatGPT. The rapid growth in revenue suggests app developers and companies
How PLG is done - take $1B ARR run rate + 80% of Fortune 500 using ChatGPT and you have a recipe to move upstream with a full blown enterprise offering - Lots of startups getting killed with this release, much expected but now in market - OpenAI releases ChatGPT enterprise, protecting privacy of data and wow, claims teams at 80% of Fortune 500 using consumer version
We’re launching ChatGPT Enterprise, which offers enterprise-grade security and privacy, unlimited higher-speed GPT-4 access, longer context windows for processing longer inputs, advanced data analysis capabilities, customization options, and much more. We believe AI can assist and elevate every aspect of our working lives and make teams more creative and productive. Today marks another step towards an AI assistant for work that helps with any task, is customized for your organization, and that protects your company data.
Since ChatGPT's launch just nine months ago, we’ve seen teams adopt it in over 80% of Fortune 500 companies.A The 80% statistic refers to the percentage of Fortune 500 companies with registered ChatGPT accounts, as determined by accounts associated with corporate email domains.
We've heard from business leaders that they’d like a simple and safe way of deploying it in their organization. Early users of ChatGPT Enterprise—industry leaders like Block, Canva, Carlyle, The Estée Lauder Companies, PwC, and Zapier—are redefining how they operate and are using ChatGPT to craft clearer communications, accelerate coding tasks, rapidly explore answers to complex business questions, assist with creative work, and much more.
Sid Sijbrandij, co-founder/CEO of Gitlab, nails it on why so many OSS cos are changing licensing models and lays out need for PBCs with Open Charters
HashiCorp is just the latest company to switch its licensing model and probably won’t be the last. As OSS companies gain commercial success the financial benefit of being open source diminishes. Open source companies generally have a low rake, creating more value than they capture, and high growth. Over time, growth slows, prompting the need for a higher rake. Companies seek to cut off “freeloaders’’ to gain more market share. They then adopt open source-adjacent licenses in an attempt to cut off competition. From a shareholder perspective, the short-term benefit is clear: capturing more value can quickly offset a growth slowdown. Whether or not it’s good for the company in the long term depends on how much growth was still ahead for the project compared to the rake increase.
Great start to OpenTF, the truly open Terraform alternative to Hashicorp in midst of license change to BSL. ⭐ do not equal success so I look forward to lots of pull requests, the open product roadmap and customers gaining confidence. Truly awesome to see the interest so far but need to deliver - btw, I’m biased as an investor and board member of Env0 who is one of the cos behind this along with Terragrunt and Spacelift. More from the Register here - “OpenTF forks Terraform, insists HashiCorp is the splinter group”
More usage of coding copilots = more insecure code so how to solve that problem
Still lots of questions before full enterprise-wide deployments of Generative AI based apps (from NY Times - The A.I. Revolution Is Coming. But Not as Fast as Some People Think)
Lori Beer, the global chief information officer of JPMorgan Chase, talks about the latest artificial intelligence with the enthusiasm of a convert. She refers to A.I. chatbots like ChatGPT, with its ability to produce everything from poetry to computer programs, as “transformative” and a “paradigm shift.”
But it’s not coming soon to the nation’s largest bank. JPMorgan has blocked access to ChatGPT from its computers and told its 300,000 workers not to put any bank information into the chatbot or other generative A.I. tools.
For now, Ms. Beer said, there are too many risks of leaking confidential data, questions about how the data is used and about the accuracy of the A.I.-generated answers. The bank has created a walled-off, private network to allow a few hundred data scientists and engineers to experiment with the technology. They are exploring uses like automating and improving tech support and software development.
AI ain’t free - 🌔shot, big idea, big bet - Ex-Meta Researchers Have Raised $40 Million From Lux Capital For An AI Biotech Startup (Forbes) - $200M post-money
Rives’ team appears to realize its moonshot status. EvolutionaryScale projects that it will spend $38 million in its first year, with $16 million going to computing power, per the pitch document. Costs multiply from there, up to $161 million in year two and $278 million in year three (with $100 million and $200 million spent on compute, respectively). But throughout the document, the company repeatedly emphasizes that it could take ten years for biology AI models to help design products and therapies.
Google Next conference was big on AI - here are 20 biggest product launches
What Brian Armstrong, founder/CEO of Coinbase would build in crypto today
Markets
Signs of life in the enterprise from Jamin Ball?
40% of software companies with June quarter ends guided Q3 above consensus.
So far, 60% of software companies with July quarter ends have guided Q3 above consensus.
Takeaway - the market, and companies outlook / optimism, improved in July
Consistently excellent. Thank you, Ed.