If you believed the news, then every single successful startup founder had it figured out from Inception on their way to 🚀 📈. In addition, founders would feel the need to always build in public and show flashy vaporware videos before shipping the real thing. The good news is that What’s 🔥 readers know that is rarely the case and success can be created in many forms.

Let me share one of our latest overnight success stories from the boldstart portfolio, Clay, co-founded by Kareem Amin and Nicolae Rusan and later with added co-founder Varun Anand. Our initial investment closed a little over 7 years ago in June 2017 with an intro from our friends at Box Group. This past week Clay announced that it has raised $62M since Inception with a Series B led by Meritech and including existing investors Sequoia, First Round Capital, Box Group, and us at boldstart…at a $500M valuation 🤯! This is the first time it has announced any of its funding.

My partner Eliot Durbin’s post Medium post shares some of this journey from Inception to Series B and what happened for the 4-5 years before Clay’s official launch on Product Hunt in 2022.

Clay is reinventing data enrichment and sales outreach for growth marketers and rev-ops teams, by dramatically improving customer research — and then using that to scale outreach. Since launching on Product Hunt in 2022, they have grown to over 100k users and >2,500 customers including OpenAI, Anthropic, Intercom, and Notion. Clay is a classic overnight success story, 7 years in the making.

Clay began focusing on developers, allowing them to instantly start using and extending an API by writing live code without any setup. When we first met co-founders Kareem Amin and Nicolae Rusan back in June 2017, they were on a mission to democratize programming, making it accessible to more people. Here’s a snapshot of their initial pitch:

Clay started life as a product for developers to build live, reusable functions which ended up becoming a more programmable Airtable. Eliot adds:

Like many great companies we work with at boldstart, Clay had to iterate on the early product, exploring several ideas like reimagining the terminal and a front-end builder. Then lightning struck; the idea of integrating APIs into spreadsheets emerged as a way to make both developers faster AND programming more accessible to non-developers. This proved to be a powerful experience, like a programmable Airtable.

The challenge then became how to focus their go to market strategy given the broad range of use cases for the tool. Clay solved for this by leaning into one of the most popular use cases, researching prospective customers and then using that data to personalize sales outreach. They began dogfooding the product, using it for themselves to enrich data on potential customers and using that to improve their outreach to those customers. Bingo! Technical growth marketers and RevOps teams started adopting Clay, programming it, and automating their manual workflows. 

Ian Jennings from Testdriver.ai just nailed Clay’s 7 year overnight success story.

1. Make APIs easier
2. Make devtools
3. Make something too broad
4. Make something narrow
5. Win!

Here’s Kareem from Clay sharing where they are today.

Thanks to the Clay community, we have grown 10x YoY for the past two years – almost entirely through word-of-mouth. We are incredibly grateful to have become the tool of choice for both small agencies and large scale-ups like Notion, Anthropic and Verkada.

This is the first time we have announced any of our funding. I’m proud of the progress the team has made and the community we’ve built. I’m excited to have the resources to scale the platform even further.

Clay first launched on Product Hunt in February 2022 with a team of under ten, and we now have over 50 employees, 100k users, and 2500+ customers. Customers are using Clay to drastically increase data coverage, perform better, more efficient research, and generate higher quality, more personalized messaging — boosting outbound campaign response rates by 2-3x.

Some of the lessons learned are:

1. More than one way to build a successful startup

2. Horizontal platforms are incredibly hard to sell from Inception, it can be done, but brutally hard

3. Narrower ICP and use cases, solve a killer pain 10x better for a specific user

4. Sell the product, market the vision - I’ve written about this before but it plays off of #3, start with narrow product vision and pitch the future roadmap

5. Power of community as a moat - Clay has grown entirely by word of mouth, more than 11k people exchange ideas and provide feedback in our Slack community, and there are now dozens of Claygencies (agencies that specialize in Clay), some of which have multi-million dollar run rates. Grassroot bootcamps and newsletters are teaching people how to grow their companies with Clay.

6. AI - 🤣, yes, the company started without AI, and AI is certainly an accelerant for its existing product

Clay’s vision is much broader than what you just see - it is now the “orchestration platform for modern go-to-market teams.”

‍Clay enables creativity at scale
With Clay, a single person can now run campaigns—whether outbound, inbound, expansion, or retention—that previously required coordinating the entire GTM team.

We decided to build a more powerful tool that targets technical users like growth marketers and rev-ops because this enables customers to centralize and manage all of their GTM workflows and experiments in one place. 

This means companies can send fewer, better messages—and only to people who are a good mutual fit. And sales representatives can focus on nurturing customer relationships and closing deals.

As always, 🙏🏼 for reading and please share with your friends and colleagues.

Scaling Startups

#as the 4th of July is coming around the corner, what better movie to reference than Top Gun Maverick! Looking at a number of failed startups in our portfolio I can say a large majority of them come down to not being able to ship product quickly enough.

"The perfect is the enemy of the good" - ship something good enough to test vs. iterating every concept in your head

It sounds simple but I can't tell you how many times we see brilliant founders stuck in a loop in their own heads

#from Arthur Brooks, The Atlantic - “An Emersonian Guide to Taking Control of Your Life” - tried and true lessons from Emerson’s famous essay

1. Be a private person; never share details of your life with total strangers.
2. Don’t conform to any conventional wisdom; question everything.
3. Make independence your goal; walk alone when necessary.
4. Don’t take the easiest path; choose to do hard things.
5. Get the cultural garbage out of your life; focus only on what edifies you.
6. Change your mind as you see fit; make no apologies for doing so.
7. Commit to complete honesty; this includes honesty with yourself.
8. Do not count on external forces for your happiness; look within.

#Everyone wants to be first, Inception/Seed up >54% vs. 2019, next up is Series A at 21%

To win at being first/Inception, funds need to be small enough so those smaller checks of <$2M are not pure option value so founders know you care and big enough to lead or co-lead a jumbo round of $10+ in proven founder you've back before.

Game is changing as multi-stage firms only getting bigger esp. with some groups like a16z rumored to be adding PE and bifurcating to specialists...

Next era is go big, go niche and specialize, or go home

Further evidence in the race to be first - there is no limit to how big an Inception round can be as EvolutionaryScale launched out of stealth with a $142M “seed” round!

And on point, Vintage Investment Partners, one of our LPs and a leading fund of funds based out of Israel, just released its third video in its series for founders. Here I talk about Inception Investing, the race to be first, why first/seed is the most competitive area of the market and the only area where valuations increased from pre-COVID pricing, and how firms will win.

Enterprise Tech

#🤯 another AI LLM startup with massive, pre-launch funding has been kind of acquired (Geekwire)…is this the beginning of the end for all these broader LLMs? The money required to scale in this race can only eventually be supplied by the big 3 cloud providers. Look forward to hearing more about what value was received by investors, but I can probably bet it wasn’t a grand slam home run but more of let’s get out now and make some money before we get killed. Why else would the story release late Friday afternoon while the world focused on the Presidential debate.

Adept raised $350 million in March 2023 as part of a Series B round that reportedly valued the company at $1 billion. Its software is designed to help companies automate rudimentary tasks such as extracting information from documents, sending emails, processing applications, and more.

Adept was reportedly in talks with other tech giants in recent months about potential deals, including Meta and Microsoft, which previously invested in the startup.

The hiring of Adept’s leaders comes as tech behemoths look to partner with or acquire startups in a race to build out AI infrastructure and services. AI startups are also under pressure as they face large computing and labor costs without substantial revenue streams.

Amazon’s deal with Adept mirrors Microsoft’s recent hiring of Mustafa Suleyman, co-founder and former CEO of consumer chatbot startup Inflection AI, along with Inflection co-founder Karén Simonyan and other employee

In a blog post, Adept said that continuing the company’s plan to build “both useful general intelligence and an enterprise agent product would’ve required spending significant attention on fundraising for our foundation models, rather than bringing to life our agent vision.”

“Adept will now focus entirely on solutions that enable agentic AI, which will continue to be powered by a combination of our existing state-of-the-art in-house models, agentic data, web interaction software, and custom infrastructure,” the company said. “We look forward to continuing towards this vision and working with partners to bring agentic capabilities to their products and tools.”

#Consultants raking it in 💰 with AI (NY Times) - who’s going to create the next Scient or Viant or Sapient or even Cambridge Technology Partners, pure-play web consulting back in early days of dot.com boom

IBM, which has 160,000 consultants, has secured more than $1 billion in sales commitments related to generative A.I. for consulting work and its watsonx system, which can be used to build and maintain A.I. models. Accenture, which provides consulting and technology services, booked $300 million in sales last year. About 40 percent of McKinsey’s business this year will be generative A.I. related, and KPMG International, which has a global advisory division, went from making no money a year ago from generative-A.I.-related work to targeting more than $650 million in business opportunities in the United States tied to the technology over the past six months.

The demand for tech-related advice recalls the industry’s dot-com boom. Businesses stampeded consultants with requests for counsel in the 1990s. From 1992 to 2000, sales for Sapient, a digital consulting firm, went from $950,000 to $503 million. Subsequent technology shifts like the migration to mobile and cloud computing were less hurried, said Nigel Vaz, chief executive of the firm, which is now known as Publicis Sapient.

#FT on BCG AI consulting revenue - the numbers are 🤯

The chief executive of BCG has said the $12bn consulting firm expects to generate a fifth of its revenues in 2024 from helping corporations integrate artificial intelligence into their businesses, a share it projects will reach 40 per cent by 2026.

Christoph Schweizer told the Financial Times that AI and generative AI were “a huge boost” to revenues in the past year as companies move from experimenting with the technology to “at-scale deployment”.

BCG is working with global tech giants and AI companies — from Microsoft and Google to OpenAI and Anthropic — to integrate their technology into company operations and processes. It is also training board directors and executive teams who increasingly see it as a business priority.

“We have never seen a topic become relevant as rapidly as Gen AI,” said Schweizer, who added that he personally uses large language models to take minutes for meetings, write emails and summarise documents.

#Perplexity, the AI search engine, rumored to be raising at $3B valuation, triple its last round from a few months ago (Bloomberg)

SoftBank Group Corp.’s Vision Fund 2 is investing in US artificial intelligence startup Perplexity AI at a $3 billion valuation, Masayoshi Son’s latest bet on a sector he deems crucial to securing his legacy.

SoftBank will invest between $10 million and $20 million in the firm, which aims to use AI to compete with Alphabet Inc.’s Google search, according to people familiar with the matter. It’s investing as part of a larger $250 million funding round that triples Perplexity’s valuation and makes it one of the industry’s most highly valued companies.

#Goldman Sachs rolls out its own platform for generating code and also sees a 20% boost in productivity from Github Copilot (WSJ)

Goldman Sachs will finish rolling out its first generative artificial intelligence tool—for code generation—to thousands of developers across the company by the end of the month.

Chief Information Officer Marco Argenti said the company’s approach to generative AI involved centralizing all proprietary uses of the technology on an internal platform, and restricting them elsewhere. “It might have slowed us down initially, but then we definitely gained a lot of velocity afterwards,” Argenti said.

Goldman’s generative AI platform, known as the GS AI Platform, grew out of an existing machine-learning platform and is the single point of entry for all generative AI use at the company. Goldman’s approach also included tapping partnerships with OpenAI-backer Microsoft to use GPT-3.5 and GPT-4 models and Google for its Gemini model. The platform also uses open source models including Meta Platforms’ Llama. The ability to switch between models for different use cases is a key benefit of the approach, Argenti said. 

Critically, the internal platform also allows Goldman to fine-tune the models with its own internal data in a safe way and that complies with regulations. Argenti said controls are embedded to ensure that models aren’t serving up data to employees who shouldn’t have access to it, for example.

#what is DeepPhishing (Polyguard.ai) - the hackers have the advantage, easier to play offense than defense

The global wire transfer system processes roughly 45 million messages per day^3, moving well over $10 trillion dollars. Combined with other money transfer mechanisms, including crypto-currency payments, ACH, and country-specific platforms, it is easy to see how phishing attacks on financial transactions are one of the largest and fastest-growing criminal enterprises in the world. The use of real-time audio and video Deepfakes (what we are calling DeepPhishing) represents a dramatic escalation in this threat, one for which most financial professionals are unprepared.

In February of this year, Interpol announced that the Hong Kong offices of British design firm Arup were the victims of a $25.6 million dollar DeepPhishing attack. These attacks have increased by 3,000% in the past year, and are a major driver in the increasing cybercrime losses reported globally. And the Arup attack is a textbook example of the new playbook for AI-powered financial fraud.

#Figma launches a bunch of AI tools and it’s 🔥 - saw so many front-end startups trying to do picture to wireframe to code, they’re all dead! Incumbents which include later stage startups are going to kill a bunch of these thin wrapper point product startups.

RIP product designers? Figma just dropped a groundbreaking new AI update today. The 10 most amazing new Figma AI features:

View here:

#AI accelerates software development to breakneck speeds, but measuring that is tricky (Joe McKendrick - ZDNet) - key takeaways from Gitlab developer survey released this past week

How AI is used in development

Code generation and code suggestion/completion, 47%
Explanations of how a piece of code works, 40%
Summaries of code changes, 38%
Chatbots that allow users to ask questions in documentation using natural language, 35%
Summaries of code reviews, 35%
What IT pros and managers want to see in AI

Forecasting productivity metrics and identifying anomalies across the software development lifecycle, 38%
Explanations of how a vulnerability can be exploited and how to remediate it, 37%
Chatbots that allow users to ask questions in documentation using natural language, 36%  
Suggestions for who can review code change, 34%
Fixing failed pipeline jobs, 31%

#this is the future 🤯

but this was not a one shot process - from CNN

“Everything you see was created with text but some shots came together quicker than others; some took more iterations,” he said. “The blocking, the way the character looks, what they’re wearing, the emotion, the background – it has to be a perfect dance. Sometimes you would create something that was almost right and other times not so right.”

Miller said there was also a lot of gut checking and human involvement throughout the process.

“Sometimes it would check a box, but maybe a reaction wouldn’t be on time with what was going on,” she said. “It was a lot of learning and a lot of back and forth. It was an educational process.”

#How are enterprises using AI?

#Jeremy Allaire, founder of USDC stablecoin Circle, on why he’s pumped about the future of blockchain - worth a read

“There is a massive, thriving and growing competitive and innovative community of dozens of major blockchain network ecosystems, all around the world, that are constantly improving and innovating in the fundamental technology of these networks including in data availability, compute, security, privacy, transaction throughput, and so much more.”

Another deep-dive from my earlier post:  
I’m more bullish than I have ever been about crypto.  

One of the things that is often overlooked when most of one looks at the world of crypto is the incredible velocity that we’re seeing new innovations in blockchain network technology.  As I noted in yesterday’s post about my mental model of blockchain networks as internet operating systems, when one zooms out from where we started 10+ years ago until today, the capabilities of these networks have expanded pretty dramatically.

A central tenet of all of this has been that the blockchain ecosystem has been fueled by a deep commitment to openness, transparency and community-driven development and governance.

I can’t tell you how many times I’ve been in meetings with central bankers or teams of leaders at major financial institutions where one of their primary retorts has been that this infrastructure is not controlled, that it can’t be trusted the same way that the servers and data centers that they control can be.  This POV pretty deeply misses the point.

The MOST secure systems in the world are the ones that are built out in the open – where literally every piece of code, every facet, every function are available for the entire world to inspect.  Open software is probably more secure than closed systems, time and time again.

Why wouldn’t we want our internet operating systems to be open and secure in this manner?  Even more so, the operation and functioning of these systems is also provably secure, obviously with varying trust and assurance assumptions depending on the security model of the blockchain network.

So, we’ve seen 10+ years of continuous innovation and iteration, where every innovation is made available as public intellectual property, and people can fork, improve, and further develop the infrastructure.  The velocity of this is astounding, and if anyone thinks that any central government or corporation (Cathedral’s) is going to be able to out innovate the open blockchain ecosystem (The Bazaar), they are sorely mistaken.

The other key point that I’m trying to land with the quote above is specifically about the ecosystems themselves.  As a technologist, it’s a marvel to see the thousands of projects that are spawning around the world to advance features of blockchain networks.  Even as someone who’s been deeply in this space for over a decade, I consider myself a novice in terms of understanding, because the surface area is so broad and each topic very deep.  I’m a 1%’er.  I only truly understand about 1% of the technology innovation that’s happening in this community right now...

More here...

Markets

#awesome quarterly deck from Ram Parameswaran of Octahedron summarizing the past quarter, 155 slides on multiples, the economy, consumer spending, tech cap x, AI, along with select quotes from earnings calls. Here’s a quote from Goldman Sachs on the IPO markets…

Re: the timing of a broader reopening of the Capital
Markets. 

I've said before that the historically depressed levels of activity wouldn't last forever. CEOs need to make strategic decisions for their firms, companies of all sizes need to raise capital, and financial sponsors need to transact to generate returns for their investors. Where we stand today, it's clear that we're in the early stages of a reopening of the Capital Markets, with the first few months of 2024 seen a reinvigoration in new issue market access.”

Goldman Sachs

#Asana beatdown - 5 learnings from Jason Lemkin SaaStr - NRR down from 115% to 102% today is brutal

Asana has been hit the hardest by the B2B2B downturn

- At $600m ARR, it was growing 34%
- Today, at $700m ARR, it’s growing just 19%
- And next year … it projects growth of < 10%

5 Interesting Learnings:

Read 🧵