VC @NEA | Spend my time nerding out about USC/Saints football, Star Wars, RTS games, and obscure facets of the US economy

Joined June 2020
18 Photos and videos
Everything is a wrapper
In more good news for Amazon, Snowflake signs $6B deal with AWS for AI CPU chips techcrunch.com/2026/05/27/in…
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Excited to be a small supporter of Trajectory! Today, most production agents for serious enterprise use cases require a deterministic harness that encodes edge cases or company-specific business processes. In this paradigm, to make agents better, companies make their deterministic tree / policy graph bigger and bigger since models can’t learn on their own. Trajectory re-writes this paradigm. Their platform helps models learn from a company’s own product usage data, building the rails for specialized AGI. And they hiring fast, DM if interested!
Today, @MichaelElabd, @QuantumArjun, and I are excited to announce Trajectory. We are a research lab and product company building the platform for Continual Learning. Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. @trajectorylabs We’ve raised $15M from @Conviction, @BessemerVP, @radicalvcfund, @jeffdean, @drfeifei and more. We’re partnering with some of the best AI-native companies: @ClayRunHQ @Harvey, @DecagonAI, @mercor_ai, @RogoAI to power their agentic systems, some of which we are already in production with. We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma. AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.
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Excited to partner with Hilmar and the Fenris Games team as they become an independent game studio. And pumped for their new partnership with @GoogleDeepMind, who will be investing with us. As someone who’s played thousands of lifetime hours of strategy games, this has been special!
Great to be partnering again!
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Similar to looking at lines of code written, token spend isn’t necessarily indicative of productivity, but if the number is 0, you’re probably doing something wrong
Ranking engineers by token spend is like me ranking my marketing team by who spent the most money. We may not have hit our KPIs, but Joe spent $200k on a branded blimp that only flies over his own house, so he’s getting promoted to VP! Don't mistake a high burn rate for a high success rate.
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Appreciate the way Neo helps high slope young teams. Excited to meet the new group!
Feb 20
Today we unveiled Neo Residency, a new program for startups and high-agency student teams. 🎉 We’re replacing our best-known program, Neo Accelerator, with something even better and more selective. 🧵
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With the median cop in SF getting paid $289k, that’s a $145M unspent labor budget just in SF. Departments across the country are facing a labor shortage and are looking to technology to supplement.
The San Francisco city government hasn’t gotten enough credit for the improvements in public safety last year — including a 125% clearance rate by the Homicide Unit. Incredible results in any context, but also interesting to note that this was achieved despite ongoing labor shortages in law enforcement. I remember seeing something at the end of last year suggesting SFPD was short around 500 officers.
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FCF continues to elude large model companies because: -The threat of distillation forces Anthropic to keep running on the hamster wheel and disrupting themselves in short cycles (FCF comes the longer they are able to harvest the fruits of their previous model before they have to invest in the next one) -The move to RL democratizes the frontier, which was previously a capital intensive game Companies that own the user (the application layer) are best positioned since their usage data can be used for RL in this new paradigm At the same time, while their LLM API may not be profitable, it may be a low margin loss leader to sell other high margin software products (Claude Code/Codex, enterprise deployments, etc). This is the playbook profitable supposedly “commodity” API businesses like Stripe and ElevenLabs have leveraged
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Fascinating data on the challenges growth areas of gaming: It's harder than ever for new games to compete, with older/entrenched games holding or growing share of playtime across all platforms Roblox dominates with kids and accounted for 2/3 of the entire industry's net new non-China growth... …but once kids get old enough, spending shifts to social media and gambling (iGaming, sports betting, prediction markets, crypto)
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Congrats to @elevenlabs on their $500M fundraise. @matiii has a rare combination of humility and obsessiveness, and it sets a culture that attracts and retains the best. It’s why they’ve shipped product at lightspeed even as they’ve grown and have consistently beat even our “optimistic case” when we first invested in the Series C in 2024. Congrats team!
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Privates markets love a non-profit with a strong consumer brand like OpenAI and Utah: Some ideas for what’s next: -The College Board (~$1B revenue) -Goodwill ($6B revenue) -Habitat for Humanity ($350M revenue)
In a groundbreaking endeavor, the University of Utah athletics is entering into what could be a $500M equity partnership with Otro Capital featuring the creation and shared ownership of a for-profit entity to operate athletics, sources tell @YahooSports. bit.ly/44hUcZJ
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Complaints against VC king-making miss the whole point. It’s not about VC $ crowning the winner. The market is pricing in the value of market leadership. For a long time, "value investing" (backing the #2 player at a cheaper price) has lost to paying high prices for the winner. This logic taken to the extreme means investing in companies ahead of knowing if they'll be market leaders since the prize is so great if you're right.
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Calling BS here 2 reasons: -Just because a product looks good in a demo doesn’t mean it performs well in a real-world environment with the required integrations -Industry-specific GTM matters a lot. And winning the customer with a useful but not defensible agent can be a wedge to something bigger
Terrifying Reality of 2025 Financial sponsor built a prototype in 2 weeks during diligence on an AI-healthcare company. Prototype outperformed the target’s core product in clinician testing. Deal killed.
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James Kaplan retweeted
15 Oct 2025
We've raised $7M to help companies build AI agents that actually learn and work. @Osmosis_AI is a platform for companies to fine-tune models that outperform foundation models with reinforcement learning. Better, faster, and cheaper.
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Most AI generated videos looks fake, but that’s the wrong question to ask since the world only cares about the top 1% of content anyways
1 Oct 2025
❓ Can AI-generated videos always fool people? 👉 Nope -- we catch them in 94% of cases 😅 🎥 With DeeptraceReward (deeptracereward.github.io), we teach MLLMs to detect human-perceived fake traces in AI-generated videos — and release both training data & model! 🔥 Benchmark: - 4.3K human annotations on 3.3K AI-generated videos 3.3K real videos - Pinpoints visually & temporally grounded traces that reveal "fakeness" 🤖 A 7B reward model trained on this data outperforms GPT-5 by 34.7% at detecting, grounding & explaining deepfake traces. 🧠 Key insight: saying “this is fake” is easy; locating where & when is far harder. 📄 Paper: arxiv.org/abs/2509.22646 This work is done with amazing collaborators at Penn, Princeton, and Stanford! @liusiyi64198 @yinuoxu @lupantech @guangqiusehu @tianboyang @tarananatasagar @christophershen @yikaimao @yuanzheliu @keyushshah @chungunlee @YejinChoinka @james_y_zou @DanRothNLP @ccb 🙌 A huge shoutout to everyone! #AI #Deepfakes #Multimodal #ComputerVision #MachineLearning #LLM #TrustworthyAI
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We're very proud to partner with @MaxKeenan3, James Liu, and the Aurelian team to lead their Series A and support their mission to disrupt public safety. Aurelian is building an AI platform that empowers understaffed 911 centers, starting by automating non-emergency calls that represent 60-80% of total call volume. They're hiring for most roles (engineering, marketing, chief of staff, head of talent, sales), so if you're mission-driven and interested, please reach out!
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Kalshi’s new liquidity incentives allows anyone to become a market maker, which is a smart way for them to build liquidity. Liquidity is a core network effect for prediction markets. More liquidity in more markets = more users = less cost of liquidity since spreads are tighter = plow more money into liquidity for even more/diverse markets. It’s a virtuous cycle and it’s why Kalshi is happy to work with Robinhood, WeBull, and Fanatics to power prediction markets for their users. The types of markets that prediction markets offer are so diverse and niche that some level of community-led liquidity makes sense. Hard for a large quant firm to justify resources to spin up a team just to analyze Taylor Swift markets, but a few Swiftie superfans could be market makers in just these markets. Awesome stuff @mansourtarek_
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Although Kalshi could probably do a better job marketing this new program!!! Don’t think many people know about it
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