I need a zoom ai assistant to help me run zoom meetings. All I see is insane feature sprawl.

Why @GeminiApp is not my top choice. This type of stuff happens all the time.

Next week, @gayathri_rg and I are hosting a free 1-hour workshop exclusively for B2B Product Managers. Join us 𝗧𝗵𝘂𝗿𝘀𝗱𝗮𝘆, 𝗝𝘂𝗻𝗲 𝟭𝟭𝘁𝗵 𝗮𝘁 𝟭𝟮𝗽𝗺 𝗣𝗗𝗧 for 𝗦𝗵𝗶𝗽𝗽𝗶𝗻𝗴 𝗔𝗜 𝘁𝗼 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗶𝗻 𝗕𝟮𝗕 🚀 We're doing this because we noticed that very little is built specifically around the constraints B2B PMs actually operate under. Dealing with regulated industries, slow cloud migrations, compliance reviews, forced users and skeptical buyers is different. From talking to a lot of PMs we learned that B2B PMs feel like they're falling behind. But the truth is that most B2B companies aren't shipping agents yet. The narrative is way ahead of reality. This session is a grounded playbook from people building AI in B2B production right now. We'll cover:   • What B2B AI PMs are actually working on in 2026   • Proprietary data as a moat   • Designing B2B AI for production: evals, drift, feedback We spent years leading AI products at Meta, Salesforce, and eBay. If you're a B2B PM trying to get into AI we'd love to see you there. P.S. If you know a PM who would benefit from this tag them below. 👇 maven.com/p/e85e77/b2b-produ…

Mt. Shasta over Memorial day weekend was incredible.

But why?

My parents are not Indian. Why did he drag Indians into this ?!!!

My immigrant parents didn't allow me to play sports. In retrospect they had a point.

True story -> me a Balkan woman being sent to HR at least once a month for "She's being mean to us" Mostly from men.

𝗧𝗵𝗲 𝗔𝗜 𝗪𝗮𝘃𝗲: 𝗪𝗵𝗮𝘁 𝗕𝟮𝗕 𝗣𝗠𝘀 𝗔𝗿𝗲 𝗦𝗵𝗶𝗽𝗽𝗶𝗻𝗴 A few years ago enterprise buyers thought that AI may be a fad. Today we’re seeing AI mandates straight from the CEO, healthy budgets, and an insatiable demand. Over the last month, I've interviewed PMs building AI for B2B products to understand what's shipping and where the challenges lie. The data is there with enterprises hoarding it for decades but it lives behind walls of compliance, access controls, and context that's hard to extract. For example, one company has the unstructured data of 70% of the Fortune 500 sitting in their product. Customers no longer need convincing and are showing up asking for the AI layer. 𝗪𝗵𝗮𝘁'𝘀 𝘀𝗵𝗶𝗽𝗽𝗶𝗻𝗴 there’s a wide spread in what shipping actually looks like   • On one end: a PM at a fast-moving enterprise vendor told me they rewrote their agent architecture three times in six months because the field moved underneath them.    • On the other end: PMs working in large enterprises are severely impaired by the tools they’re allowed to use. By the time they get approval from their internal team, things have changed. 𝗔 𝗳𝗲𝘄 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀 𝗰𝗮𝗺𝗲 𝘂𝗽: → 𝗠𝗼𝗱𝗲𝗹 𝗮𝗴𝗻𝗼𝘀𝘁𝗶𝗰𝗶𝘀𝗺 is a feature. Enterprises don't want to bet on one lab. They want optionality. FedRAMP, government, and regulated segments are locked out of specific providers for reasons that have nothing to do with model quality. → 𝗧𝗿𝘂𝘀𝘁 𝗰𝗼𝗺𝗽𝗼𝘂𝗻𝗱𝘀. A 20-year SOC2 track record beats a better model from a new vendor. Incumbents get "grandfathered" through legal review while startups start the compliance gauntlet from zero. → 𝗧𝗵𝗲 𝗱𝗮𝘁𝗮 𝗺𝗼𝗱𝗲𝗹 𝗳𝗶𝗴𝗵𝘁𝘀 𝘁𝗵𝗲 𝗔𝗜. Enterprise software is built in functional silos i.e. manufacturing here, inventory there, costing in another module. AI needs cross-functional correlation to truly deliver on a use cases. But the databases weren't built to support this. → 𝗡𝗼 𝘁𝗲𝗹𝗲𝗺𝗲𝘁𝗿𝘆, 𝗻𝗼 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗹𝗼𝗼𝗽. Enterprise users don't click thumbs-up. Slow adoption means slow signal. → 𝗘𝘃𝗮𝗹𝘀 are the most underserved problem in B2B agents. Defining what "good" looks like, generating realistic test data, running evals on production traffic, tracking drift over time. Every PM I talked to flagged this as the biggest unsolved gap. Overall, 𝗣𝗠𝘀 𝗮𝗿𝗲 𝗲𝘅𝗽𝗲𝗰𝘁𝗲𝗱 𝘁𝗼 𝘀𝗵𝗶𝗽 𝗔𝗜 𝗻𝗼𝘄, even when their stack, tooling, and data model are working against them. I'll be sharing everything I learned in a free Lightning Lesson on 𝗠𝗮𝘃𝗲𝗻 𝗼𝗻 𝗝𝘂𝗻𝗲 𝟭𝟭 𝗮𝘁 𝟭𝟮𝗽𝗺 𝗣𝗗𝗧. We'll trade notes, compare what's working in different stacks, and learn from one another. The best moments in my interviews came when PMs realized that others are facing the same challenges. I want to recreate that sense of camaraderie  in the room. If you're a B2B PM shipping (or trying to ship) AI to production, come join us. maven.com/p/e85e77/b2b-produ…

anxiety inducing

A lot of brilliant AI people back onto the market. If you've been sitting on an AI startup idea @amitpaka ☕️ (Founder/COO of @fiddler_ai , $100M raised) and I are running a 2-hour workshop on Maven. 🚀 𝗙𝗿𝗼𝗺 𝗔𝗜 𝗜𝗱𝗲𝗮 𝘁𝗼 𝗜𝗻𝘃𝗲𝘀𝘁𝗼𝗿-𝗥𝗲𝗮𝗱𝘆 𝗣𝗶𝘁𝗰𝗵 A 2-hour build workshop on Maven July 14, 10am-12pm PST 𝗬𝗼𝘂'𝗹𝗹 𝘄𝗮𝗹𝗸 𝗼𝘂𝘁 𝘄𝗶𝘁𝗵: → A sharpened pitch, pressure-tested live by a former VC and a founder who's raised $100M → A specific diagnosis of how to make your story land → The frameworks for the five artifacts VCs actually read, positioning thesis, long-form narrative, deck outline, one-page memo, target partner list → A 7-day punchlist exactly what to write, in what order, to be investor-ready → A take-home Claude skill to help you do the writing well, on your own time → Pattern-recognition from watching 14 other founders pitch and get critiqued Between us: $100M raised at Fiddler, 200 AI startups evaluated at Storm Ventures. 𝗘𝘃𝗲𝗿𝘆 𝗳𝗼𝘂𝗻𝗱𝗲𝗿 𝗽𝗶𝘁𝗰𝗵𝗲𝘀 𝘂𝘀 𝗹𝗶𝘃𝗲 𝗳𝗼𝗿 𝟲𝟬 𝘀𝗲𝗰𝗼𝗻𝗱𝘀 𝗮𝗻𝗱 𝗴𝗲𝘁𝘀 𝗿𝗲𝗰𝗼𝗿𝗱𝗲𝗱 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸. 𝗖𝗮𝗽𝗽𝗲𝗱 𝗮𝘁 𝟭𝟱 𝘀𝗼 𝘄𝗲 𝗰𝗮𝗻 𝗮𝗰𝗰𝗼𝗺𝗺𝗼𝗱𝗮𝘁𝗲 𝗲𝘃𝗲𝗿𝘆𝗼𝗻𝗲. Here's why we created this workshop: I evaluated 200 AI startups as a VC at Storm Ventures, and the recurring pattern was that smart founders with interesting ideas consistently showed up with pitches that were hard to follow. When the story doesn't hold together, it's hard to build conviction. As a potential champion when I can't quickly understand your company, than I can't advocate for you. And I get founders asking me for this advice all the time. Link to enroll 👇 maven.com/natalia/ai-idea-to…

I remind myself of this quite often.

An Italian town is being terrorized by peacocks. Other towns get rats. Ravenna gets peacocks. Even Italy's pests are gorgeous. Unfair.