Jun 8, 2018 · 1h 5m · mad
Fireside Chat: Chris Dixon, General Partner at Andreessen Horowitz (FirstMark's Data Driven)
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
In this fireside chat hosted by Matt Turck at DataDrivenNYC, Andreessen Horowitz General Partner Chris Dixon shares insights on emerging computing platform cycles, AI startup strategies, frontier hardware, and the transformative potential of decentralized Web3 networks.
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 17.8% of the talking time here. How this is scored →
Matt as informed peer 4.5 Guest teaching 4.5 Guest disagreement 1.2 Matt pushing back 0.9
speaking balance: gold is Matt, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 37:40 Challenging Skepticism on CryptoKitties and Toys
Dixon forcefully counters mainstream skepticism around CryptoKitties by pointing out that real-world mainstream games like Fortnite make hundreds of millions per month selling purely cosmetic virtual goods.
Hardest push from Matt ▶ 9:13 Challenging Big Tech Data SuperiorityMatt pushes back on common VC narratives by explicitly questioning Dixon on whether Google's overwhelming data advantage makes early-stage AI investing fundamentally unviable.
Biggest teaching moment ▶ 7:04 Deconstructing Venture Strategy in Big Tech AI EraDixon delivers a comprehensive breakdown of why infrastructure-level AI startup investments are non-viable due to Big Tech loss-leader strategies, reframing the VC opportunity around verticalized domain integration.
Matt holds his own ▶ 21:27 Detailed Drone Portfolio KnowledgeMatt demonstrates sharp domain knowledge and interview preparation by citing specific commercial drone portfolio investments (Airware, Skydio, Zipline) to focus the discussion on sector-specific execution.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Matt as informed peer | Guest teaching | Guest disagreement | Matt pushing back | Why |
|---|---|---|---|---|---|---|
| Chris Dixon's Entrepreneurial Journey and Early AI | 5 | 3 | 1 | 1 | Matt demonstrates clear familiarity with Dixon's career and blogging history, prompting him on his early startups and broad views on computing cycles. Dixon provides a friendly overview of technology waves and early AI acquisitions. | |
| AI Investment Dynamics and Big Tech Dominance | 5 | 5 | 1 | 2 | Matt asks about AI investment dynamics following early acquisitions like Wit.ai. Dixon explains how Big Tech commoditizes AI infrastructure through open algorithms and cloud loss-leaders, shifting venture opportunities to vertical applications. | |
| Data Advantages and Navigating the Idea Maze | 6 | 5 | 2 | 2 | Matt raises questions about Google's data moats and references Dixon's post on the Idea Maze. Dixon politely corrects that Balaji Srinivasan created the Idea Maze concept and details how founders iteratively explore problem spaces. | |
| Machine Learning Execution and the 80/20 Dilemma | 6 | 4 | 1 | 1 | Matt introduces the technical dilemma where machine learning models reach 80% accuracy quickly but struggle with the final 20%. Dixon details execution strategies like fault-tolerant user interfaces versus zero-tolerance safety domains. | |
| The Future of Virtual and Augmented Reality | 4 | 4 | 2 | 1 | Matt guides the conversation toward VR/AR adoption hurdles and price points. Dixon outlines hardware technical requirements and takes a contrarian stance favoring full VR immersion over mainstream AR hype. | |
| Internet of Things and Commercial Drone Ecosystems | 5 | 4 | 1 | 1 | Matt references several specific companies in Dixon's drone portfolio including Airware and Zipline. Dixon outlines regulatory barriers in the US alongside commercial adoption in mining and African medical delivery. | |
| Decentralization as Public Digital Infrastructure | 6 | 5 | 1 | 1 | Matt highlights Dixon's framing of decentralization as public infrastructure rather than political ideology. Dixon traces the evolution from open-source software to crypto, warning against developer platform risk on centralized networks. | |
| Developer Migration and Historical Tech Parallels | 5 | 6 | 1 | 1 | Matt questions how unpolished crypto applications can win against incumbent tech products. Dixon responds with historical analogies comparing early crypto to Wikipedia competing against Encarta and early web encryption controversies. | |
| Token Incentives, Bootstrapping, and Stablecoins | 6 | 5 | 1 | 1 | Matt raises token economics and cold-start problems in marketplace networks. Dixon breaks down how native tokens align early user incentives to solve the bootstrapping challenge and explains stablecoin mechanisms. | |
| Decentralized Apps, NFTs, and Digital Ownership | 6 | 5 | 2 | 1 | Matt brings up dApps and CryptoKitties in relation to Dixon's post on innovations looking like toys. Dixon vigorously defends NFTs by pointing to massive virtual goods revenues in gaming and digital ownership models for creators. | |
| Disruption Theory, ICO Dynamics, and Crypto Regulation | 6 | 5 | 1 | 1 | Matt inquires about ICO market noise, regulatory friction, and a16z's shift toward direct token investments. Dixon invokes Clay Christensen's disruption theory, identifies developer energy as his core signal, and discusses regulatory frameworks. | |
| Venture Capital Disruption and Tech Convergence | 6 | 5 | 1 | 1 | Matt asks whether ICOs could disrupt traditional venture capital and how emerging technologies intersect. Dixon explains accredited investor rules and draws parallels to how mobile, social, and cloud mutually reinforced each other. | |
| Audience Q&A: Enterprise Data Monetization and AI | 0 | 4 | 1 | 0 | In an audience Q&A segment, an attendee asks about monetizing enterprise data assets. Dixon clarifies that successful tech firms build services on top of data rather than selling raw data directly. | |
| Audience Q&A: Competing with Incumbent Bundlers | 0 | 4 | 1 | 0 | An audience member asks about competing against major cloud bundlers. Dixon draws on the historical Quicken versus Microsoft Money battle and reflects candidly on timing lessons from his former startup Hunch. | |
| Audience Q&A: Blockchain Governance and Experimentation | 1 | 4 | 1 | 0 | An audience member asks about blockchain governance and standards fragmentation. Dixon breaks down on-chain versus off-chain governance and characterizes the current ecosystem as an open-source Darwinian evolutionary process. |
Statements from this episode (28)
Dixon says bank report listed Hunch as the decade's first AI acquisition
“I saw a an investment bank put out a report recently, and it was, like, AI acquisitions over the last decade, and we were, like, the very first one”
Dixon: High-end VR headset prices fell 80% over three years
“The price of a high-end VR headset has gone down, I think, like, 80% over the last three years”
Dixon: Tech advances in 10 to 15 year platform cycles
“If you just look at the history of technology, It tends to go in these sort of 10 to 15 year cycles, right? So you had the mainframe computers, you had PCs, you had the internet, you had smartphones. Like, we're due for another kind of wave, I think, in the ne…”
Dixon: Cost of Wi-Fi Linux computers will fall to $1
“You can get a five dollar, you know, Linux It's a computer now with Wi-Fi. It's Wi-Fi enabled. That's going to go to a dollar.”
Dixon: Over half of Andreessen Horowitz's bio fund involves deep learning
“More than half Of those companies in that fund involved sort of deep learning in some way.”
Dixon: Non-tech giants will find speech recognition AI very tough
“I think for some applications, like speech, you know speech is going to be, I think, very tough for non, you know, I mean, like Google and Amazon with their, you know, with their, and Apple with their phones and the, you know, the Alexa's and things like that.…”
Dixon: AI winners will be determined by data, not algorithms
“Is who kind of wins in AI, and I think that will probably come down to who has the best data, because the algorithms are, you know, all published and out there, and the frameworks are out there, and so it's not really, that's not really gonna be a differentiat…”
Dixon: 80% accurate ML models take a weekend; the rest takes decades
“You can sort of, like, you know, you can download TensorFlow, download some data sets, and over the weekend, probably come up with, you know, if you're a good programmer, come up with something that can do, like, 80% accuracy of whatever, let's say OCR or some…”
Dixon: Ten Google results act as a fault-tolerant UI for AI
“In some ways, you can think of Google results. They give you 10 results, right? They're sort of, you know, like in an ideal world, they give you one result, but they give you 10 results, because they let the human figure out the last 20%, right? So that's sort…”
Chris Dixon: Mass VR adoption requires a $200 untethered 6DOF headset
“I think you need a 200 dollar, some sort of consumer price point device which has sort of a high-end feature, so like, and that means like six degrees of freedom, head tracking, I don't know if people follow this stuff, hand tracking you have to get rid of the…”
Chris Dixon remains bullish on VR over AR for full immersion
“I'm still very bullish on, I know it's sort of fashionable to be like AR, not VR. I think AR is very cool, but I think VR. I mean, I think VR, I don't know, I just think of it as like, you want to, do you want to go partially into the matrix or fully into the …”
Dixon: Top mobile apps were all created between 2009 and 2011
“If you just go look at all the top apps, they were all created between 2009 and 11 basically.”
Dixon: U.S. ban on beyond line of sight drones holds back commercial applications
“A lot of it's regulation in the U.S. It's there's, like, beyond line of sight drones, for example, are not legal. Which is a big issue for a lot of applications.”
Dixon: Crypto networks are community-owned digital services, not corporate ones
“The way I think of crypto networks, as I call them, is, is they are digital services, and that's, I mean, in the broadest sense of any kind of digital service that are owned and operated by communities as opposed to being owned and operated by companies.”
Dixon: Centralized platforms predictably turn hostile to third-party developers over time
“What tends to happen with these big platforms is they start off being very open to, kind of, third parties to startups. Like, if you look at Facebook early on, they embraced Zynga, and they embraced media companies and things like this, and then as they got bi…”
Chris Dixon meets weekly with three teams leaving Google or Facebook
“I have three of these meetings a week where it's team coming out of Google or Facebook or someplace like that”
Chris Dixon: The best VC strategy is following smart developers
“The thing that's worked for me as an investor is to not try to outsmart, ah, really smart developers. Just sort of let them show me where to go and follow them.”
Chris Dixon: Netscape was hauled before regulators over SSL encryption
“Netscape created SSL in the nineties, which is the, you know, the encryption protocol of the internet. They were like hauled in front of, you know, regulators and things, because The thought at the time was, who would want to encrypt it except for criminals?”
Dixon: Blockchains without native tokens lack an essential operational funding model
“I think the idea of trying to build, like, a blockchain system without a cryptocurrency associated with it, you're losing this essential aspect, which is this funding model, essentially which funds both the operation of the network, but also the development, t…”
Chris Dixon: 99% of network effect startups fail before achieving scale
“99%, probably, of network effect businesses die before they kind of get to network effects, to real network effects.”
Dixon expected major crypto user applications within one to two years
“I hope and I expect over the next year or two we're going to see some really interesting applications.”
Dixon: League of Legends made $2.5B selling cosmetic items
“So like League of Legends, two and a half billion in revenue last year, selling literally cosmetic items only.”
Dixon: Musicians will make money selling digital virtual goods
“And so I think you're going to see musicians who now make money by selling digital virtual goods as an example, which is not a model today, and that's like a very interesting new model as an example.”
Dixon: Betting against Ethereum means betting against top developer talent
“If you want to bet against Ethereum as an example, like you're effectively betting against, you know, I don't know, like a lot of really, really smart engineers, and I just, I think it's a, You know, I'll take the other side of the bed.”
a16z expanded into direct token investments around late 2016
“We've since, about a year and a half ago, kind of crossed over to doing also direct investment in coins and tokens”
Chris Dixon: Startups facing bundlers need order-of-magnitude better technology
“The key is to, you just, you need, you just really need, like, an order of magnitude, kind of better technology and product, like, it just really raises the bar, right, because it's essentially an old problem in startups, which is you're competing against bund…”
Dixon: Top crypto infrastructure projects will eventually consolidate talent
“I think over time, I think we're in an early phase, and over time, you'll start to see, kind of, like, some of the more, like, successful infrastructure projects, kind of, ah, separate themselves from the others, and it will become clear that it's better to wo…”
Dixon: Developer momentum will solve blockchain scaling challenges
“Ethereum has, they have a lot of really interesting stuff going on that they're doing to improve scaling, and there's Plasma, I think. There's Plasma, there's sharding, you know, proof of stake, Wasm like there's all this layer two stuff so it's like state cha…”