Nov 13, 2019 · 39m · mad
Fireside Chat: Mike Volpi, General Partner, Index Ventures (FirstMark's Data Driven NYC)
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In this Data Driven NYC fireside chat hosted by Matt Turck, Index Ventures General Partner Mike Volpi shares deep insights on open source monetization, enterprise data infrastructure, machine learning commercialization, and venture capital decision-making. Volpi reflects on his extensive career, offering tactical advice for founders building early-stage data platforms and navigating investor partnerships.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 15.3% of the talking time here. How this is scored →
Matt as informed peer 2.6 Guest teaching 3.8 Guest disagreement 0.6 Matt pushing back 0.1
speaking balance: gold is Matt, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 14:01 Mild dissent on multi-product trend
Mike politely disagrees with Matt's premise regarding emerging multi-product startup trends, insisting that early companies must focus on building repeatable traction with a single product first.
Hardest push from Matt ▶ 13:26 Challenging single-product orthodoxyMatt pushes back against standard VC guidance by citing hot multi-product companies like GitLab and HashiCorp as counter-examples.
Biggest teaching moment ▶ 22:13 Reframing autonomous vehicle expectationsMike corrects the popular perception that autonomous driving is primarily about passenger city taxis, demonstrating why goods delivery and freeway trucking will adopt the technology far sooner.
Matt holds his own ▶ 9:26 Citing licensing shifts and cloud competitionMatt displays deep sector intelligence by raising CockroachDB's recent license change and AWS's distribution of Elasticsearch without needing explanation from the guest.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Matt as informed peer | Guest teaching | Guest disagreement | Matt pushing back | Why |
|---|---|---|---|---|---|---|
| Opening Title and Event Welcome | 3 | 2 | 1 | 0 | Matt opens with detailed background facts about Mike's IPOs and Cisco acquisition history. Mike playfully brushes off the Midas list title and shares the thesis behind investing across enterprise and consumer companies. | |
| The Three Generations of Open Source Software Models | 3 | 4 | 0 | 0 | Matt prompts Mike to walk through the three generations of open source software models. Mike provides a clear breakdown from support-only to open core to managed cloud services. | |
| Open Source Licensing Strategy and Countering Cloud Providers | 4 | 4 | 1 | 0 | Matt displays specific industry knowledge citing CockroachDB's recent license revision and AWS's Elasticsearch distribution. Mike details how open source vendors use licensing tactics like BSL and SSPL to defend against cloud providers. | |
| The Evolving Role of Developer Communities | 4 | 4 | 2 | 1 | Matt brings up popular multi-product startups like GitLab and HashiCorp to question the conventional single-product rule. Mike politely dissents, maintaining that early-stage startups should focus on doing one thing well first. | |
| Data Insights, Machine Learning, and Enterprise Competitive Advantage | 3 | 4 | 0 | 0 | Matt asks if innovation in core data infrastructure is nearing completion. Mike delivers an enterprise thesis on how competitive advantage shifted from physical scale to deriving insights from data. | |
| Solving Machine Learning Infrastructure and Data Labeling Bottlenecks | 2 | 5 | 0 | 0 | Matt asks about exciting subsectors in infrastructure. Mike breaks down human resource bottlenecks in machine learning and explains Scale AI's data annotation and global labor dynamics. | |
| Commercial Horizons and Use Cases for Autonomous Driving | 2 | 5 | 1 | 0 | Matt asks where autonomous driving stands on the spectrum between science fiction and reality. Mike reframes the narrative away from consumer robo-taxis toward long-haul freeway freight trucking. | |
| Strategic Guidance for AI Founders and Emerging Deep Learning Trends | 3 | 4 | 0 | 0 | Matt distinguishes between structured and unstructured data opportunities for founders. Mike advises founders to pursue practical tabular data models for quick wins, or deep learning for long-term technical value. | |
| Evaluating Founder Qualities in Technical Data Startups | 3 | 3 | 0 | 0 | Matt prompts Mike on founder traits and how startups should evaluate venture capital partners. Mike highlights founders who felt operational pain firsthand and stresses calling VC reference checks on failed investments. | |
| Q&A: Public Cloud Dynamics and the JEDI Defense Contract | 1 | 3 | 1 | 0 | An audience member asks about the $10B JEDI cloud contract awarded to Azure over AWS. Mike addresses developer market share statistics and candidly evaluates venture capital diversity challenges. | |
| Q&A: Data Ethics, Privacy Regulation, and Regional Governance | 1 | 4 | 1 | 0 | An audience member asks about data ethics and conscious investing. Mike explains cross-border regulatory nuances, comparing European GDPR and US First Amendment rights. |
Statements from this episode (20)
Volpi: Index Ventures invested in Elasticsearch one month after discovering it
“The next day I called Elasticsearch. We ended up investing in the company a month later, and then it went public.”
Volpi: Consumer investments help VCs discover winning enterprise infrastructure tools
“So by being in consumer companies, you learn how infrastructural tools get used. And you often find the good ones, and so that's super relevant, and oftentimes whether they're using good or bad tools can also be an indicator of whether they're going to be a su…”
Volpi: Enterprise software is sold by developers, not executive slideware
“Whereas software was once sold through slideware to executives, software is now sold by developers who self-discover and evangelize that software.”
Volpi: Index Ventures made 5x return on Hortonworks investment
“We invested in Hortonworks, The company did go public. We made five times our money on the investment”
Volpi: Open-source startups must build proprietary features to survive
“Big lesson there, definitely have proprietary software, and understand where that boundary condition should be between free and commercial.”
Volpi: AWS launched DocumentDB to bypass MongoDB's SSPL license
“Mongo took an interesting similar approach. They have something called SSPL. In that case, it says you can take it, but any software that you build around it to run it, you have to open source it. So Amazon will have to open source its entire software base use…”
Volpi: Google and Azure partner with OSS creators to counter AWS
“And then the other thing that you do As a business is you partner with Google and Azure who, because they're pretty far behind Amazon, they're more than happy to have the original item and to pay you something for the privilege of running your version.”
Volpi: Employees write 95% of code in open source startups
“Nowadays, most of these open source companies, you know, 95% of the code is written by employees, and the five percent are like patches or connectors or something like that that the community is building.”
Volpi: Open source communities replace product management, not engineering
“So the community is still very important, but it's gone from basically substituting for your engineering org to substituting for your product management organization.”
Volpi: Traditional enterprises remain clueless about extracting value from data
“There are millions of businesses out there, even the big ones that I just cited, like somebody like American Airlines or Marriott Hotels, and I hope I don't insult anybody in the room, are clueless on how to get insights out of their data.”
Volpi: Machine learning infrastructure faces a critical human resources shortage
“I think one of the big challenges that we face in industry right now is there are Not enough people that know how to build, stand up, operate machine learning infrastructure. So you can provide a lot of people tools, but right now the actual problem is a human…”
Volpi: Self-driving trucks will operate on freeways within 18 months
“And if you ask me, like, for those use cases, I think you're going to see self-driving trucks on freeways within the next 18 months.”
Volpi: Practical AI startups should focus on simple ML on tabular data
“So if you want to be really practical in modern use cases, focus on tabular data with schemas that do really simple machine learning, like do fraud detection, do inventory forecasting do simple, straightforward predictions, and just about every business in the…”
Volpi: Machine learning experience over a decade old is mostly obsolete
“A lot of people will say they did machine learning, but if they did it more than 10 years ago, they did it in a pretty obsolete way.”
Volpi: AWS holds an estimated 85% to 90% market share among developers
“If you actually pulled engineers on the street, you'd probably get 85, 90% market share with Amazon. So in my mind, no matter what the government decides on whether they use the Azure cloud or Amazon cloud, Amazon is stratospherically dominant amongst develope…”
Volpi: Index Ventures' portfolio has roughly 20% female CEOs
“My firm has probably about 20% of its CEOs that are women.”
Volpi: VC industry and Index Ventures have failed on diversity
“I think the industry at large, and our firm included in this, has not done a good job at all Funding against diversity or including diversity in our own firms?”
Volpi: Younger VCs ignore diversity and fund people who look like them
“Younger VCs will tend to ignore all those issues and just say, how do I get my hands on the best company? I don't care. Like, and generally they tend to fund people that look like them. I think generally more experienced VCs will have a little more open-minded…”
Volpi: Female partners at Index Ventures find more women entrepreneurs
“Now that we have eight partners at Index, two are women now, and I will say they find more women entrepreneurs.”
Volpi: Index Ventures prefers investing in data producers over data collectors
“We tend to invest in businesses that produce data as opposed to collect data, but there are businesses that collect data for sure, and as long as they're compliant with the law and are not doing egregious stuff around it, we will tend to fund them.”