Tiffany Luck

Partner @NEA investing in enterprise & vertical AI. Previously, @GGVCapital, @MorganStanley, BD/Mktg @amazon @Lot18 @Forbes. Golfer ⛳️. And best of all - mom ✨.

[Tiffany Luck @lucktm]

Very excited to join the team @NEA and continue to partner with amazing founders across B2B SaaS, APIs & AI! 💥

[NEA @NEA]

🎉 We're thrilled to announce that Tiffany Luck has joined NEA as a Partner on the Technology Investing Team.

Welcome, @lucktm!

📰 https://t.co/iEjIi67IdF

[Tiffany Luck @lucktm]

@blennon_ Exciting! Would love to try Ollie

[Tiffany Luck @lucktm]

@annbordetsky @felixhhaas @PatrickHaede Love this! Serendipity ftw

[Tiffany Luck @lucktm]

@FDavidsonT Would love to try!!

[Tiffany Luck @lucktm]

@maddiehfaulkner @matanSF @FactoryAI @NEA Miss you already!

[Shensi Ding @shensi]

https://t.co/00IA0GAR8F

[Tiffany Luck @lucktm]

Had a really fun conversation with @bayareawriter @crunchbasenews about what makes vertical AI companies fly and what we're seeing @NEA.

the tldr: there's real opportunity in the last mile!

https://t.co/TXNoDtSZaO

[Tiffany Luck @lucktm]

@RMB I wish we were closer to SF weather today. Way too cold!

[Perplexity @perplexity_ai]

Today we're announcing the Billion Dollar Build.

An 8-week competition where teams will use Perplexity Computer to build a company with a path to $1B.

Finalists have the opportunity to secure up to $1M in investment from the Perplexity Fund and up to $1M in Computer credits.

[Tiffany Luck @lucktm]

Excited for another great HumanX conference!! This time in SF.

[NEA @NEA]

📢 NEA's @lucktm will be featured at Human X next month to discuss 'Where Early Stage AI Money Is Going Now' https://t.co/8EAoWW5TyA

Use code HX26_TLUCK to save $150 on your ticket: https://t.co/7r9GBeTXoZ

[Tiffany Luck @lucktm]

@mandrusko1 💯coffee & walk as soon as real spring is here!

[Maithra Raghu @maithra_raghu]

https://t.co/xaBoeAENzv

[Maithra Raghu @maithra_raghu]

Seeing a lot of mixed takes on what LLMs do to vertical software moats. Most are framed as if the biggest threat to software is "an LLM in a chat window." But the real threat is the north star: "AI Agents working with 100% reliability, enterprise context, and at institutional scale" that is slowly becoming reality. Some quick thoughts on the biggest misses I'm seeing:

Business logic and institutional context are THE most important value add. Firms want expert vertical AI Agents not because they want another chatbot, but because they want something that can deliver outcomes with deep, firm-specific context. Similarly, software companies that are deeply embedded in business context have a meaningful moat. But AI's advantage is that it can be built to adapt to different types of business logic while using a shared platform.

Thoughtful UI matters. UI alone is not a moat. But assuming that sophisticated AI Agents can be reduced to a chat box is a huge oversight. Users need to understand how to build Agents that best represent their workflows, how to collaborate and provide feedback, how to get them to reliably interface with other tools. Overloading all of that into a chat box just doesn't work — our lived experience at Samaya — and the need for guided, structured interaction is real.

Strong engineering is still not "trivially accessible." While AI coding tools offer a real increase in productivity, building reliable, fast, scalable, and secure systems — the foundation for enterprise-grade AI Agents — is still a substantial lift. And that's not even mentioning model training work that requires deep technical understanding. AI and software teams that maintain a bar for technical excellence continue to have an important edge. With the coding tools, it's technical excellence coupled with focus and velocity. (See e.g. https://t.co/VGwSZLnx5Z from @ibab )

Nailing the "long heavy tail." When I was at Google, I spent a lot of time training models to be accurate on the "long heavy tail" — a large set of less common but important use cases. Fast forward to now: what's in the long heavy tail has changed, but not its existence. We consistently find small errors in our AI systems (e.g., company tickers, mixing up metrics) that have to be corrected with urgency so they don't compound as the Agent executes. I expect we will always have a changing "long heavy tail" that needs custom development.

Proprietary data is not necessarily a moat. On the surface, proprietary data seems like a strong moat, especially for software incumbents. But in practice, a lot of proprietary data is not truly proprietary. It may be a data product with revenues and pressures tied to licensing it out, aggregated across different primary sources — now easier with AI — or tied to other third parties. I expect we'll see a trend towards data becoming more broadly accessible as the value accrues to what you do with the data.

[Tiffany Luck @lucktm]

@caitlinbolnick1 Totally agree! Investment + life decisions more broadly I’ve found. The body somehow knows.

[Tiffany Luck @lucktm]

Exciting news @samaya_AI — building the future of AI for finance! 🪄

[Maithra Raghu @maithra_raghu]

Thrilled to share two big milestones for @Samaya_AI: the launch of the Agent Control Plane (ACP) and new investment from NVentures (@nvidia VC arm) and @databricks Ventures!

1) The Agent Control Plane (ACP) is a new architecture for personalized, long-horizon AI Agents that execute autonomously for hours, embedding your institutional context and your thesis into every decision. (Like a supercharged Agent harness built for investment decision making.)

2) New investment from NVentures (NVIDIA's VC arm) and Databricks Ventures to support ACP development and the shared belief that verticalization is the key unlock for AI Agents in finance.

The hardest challenge for AI in finance is going beyond regressing to the mean. AI must have sophisticated cause-and-effect reasoning, grounded in what's unique to each investor — to translate global information into personalized investment conviction.

[Tiffany Luck @lucktm]

@bksun Amazing!! Huge congrats!

[Tiffany Luck @lucktm]

@ditzikow @southpkcommons Huge congrats Dylan!!

[Tiffany Luck @lucktm]

@JasonrShuman @mymeltingpoint Amazing! Congrats!!

[TwelveLabs (twelvelabs.io) @twelve_labs]

This week our co-founder Soyoung Lee took the stage at the #Under30Summit 🎤
She demoed how TwelveLabs makes video as searchable as text, helping creators + studios instantly:
🔎 Find exact scenes
📝 Generate metadata
⚡️ Go from raw footage → finished story faster
Thanks @Forbes + @zoyahasansoomro for having us!
#VideoAI #TwelveLabs

[Tiffany Luck @lucktm]

Huge congrats to @maithra_raghu!! Technically brilliant, amazing leader, and a great human all around. We @NEA are beyond lucky to work with you and everyone on team @samaya_AI!

[Maithra Raghu @maithra_raghu]

Surprised and delighted to be on the @TIME 100 AI list! (And in very good company!)

It’s especially meaningful to have this recognition this year, which has been one of incredible growth and milestones for Samaya. We closed our Series A led by NEA, and with other stellar investors earlier this year.

But most importantly, we went from a smaller set of initial users at the start of the year, to being live, globally, with thousands of users that rely on Samaya every minute of every day to help them navigate the financial information ecosystem.

Building a company is an exercise in sheer grit. There are many times you want to quit. The will to keep going comes from the real, measurable impact Samaya is having on our users, the trust and love our customers have for the product, and working with such a brilliant and talented team.

Thank you for your faith in us, and we’re excited to build towards the vision of a new type of financial ecosystem, where humans and AIs collaborate seamlessly on high-stakes investment workflows. Much more to come!