Alon rosenberg ✊

@zachtratar @ivanhzhao Yes for new meetings. I am using Notion to record every meeting I have (mostly external ones) and it’s really annoying to have to reopen the last tab I worked on before all over again.

@alonrozenberg @ivanhzhao Does holding command and then clicking work? This is for a new meeting right? We could also potentially change the default behavior. It has been discussed but is also hotly debated. :)

Our retention on Notion AI Meeting Notes just hit a crazy high number. Growing like crazy as people switch from Granola and Fireflies. ONE top customer = 2500 hours per week. People are loving it! 😍 And we have a couple more features coming soon... then we can exit beta.

@Kazanjy One thought- in the world of AI and amazing note takers, why do you need 15 minutes post call action items.

Founders: Block your calendar like this for demos: 15min pre-call prep 45min demo 15min post-call action time 15min buffer Result: 90min total block Never back-to-back demos. You're burning $500+ of marketing spend per demo. Give yourself space to execute.

@fendien That’s why it should seat in the platforms you already work in rather then your browser with another dashboard to access.

The modern GTM stack is incredible. CRM + enrichment + AI + intent data + browser extensions. The only downside is my browser now runs at 1998 AOL dial-up speeds😢

@thinkshiv Calling a GTM agent an AI CMO, already indicate what it’s not-a CMO.

You wanna AI CMO, ye got it 👇👇👇

@ivanhzhao Yes please

LMK if you want early access (and can provide ample feedback in exchange)

@JJEnglert GTM guide

I built the ultimate GTM Engineer AI Toolkit that handles prospect research, outreach writing, meeting prep, and more in minutes. This is a beginner-friendly walkthrough that shows you exactly how to set it up, use it at work, and personalize it to your business. It can: - Research real prospects and companies - Score accounts against your ICP - Write personalized cold outreach sequences - Generate meeting prep briefs before calls - Help you build a repeatable prospecting pipeline - All using a free toolkit + Claude Code / Codex. This is for SDRs, founders, marketers, and GTM operators who want to use AI to do more at work without buying another expensive tool. I break down the full workflow step by step in the video. 👇 Comment "GTM GUIDE" and I’ll send you the full toolkit. (make sure you're following me so I can DM you)

@cjc Looking really great and clean. The only point I will make, is with agents and AI, why still use a form to talk to your team.

New Linear homepage: Designed for the AI era

@HarryStebbings @illscience It’s a mix of experiance and chat- it means that once you experiance something and develop emotions then you can turn intent to chat and then the UI should be in the familiar place like messaging apps.

Why Chat-Based UI Won't Last and Browser-Based Will Prevail: @illscience " Most people don't want to save time. They want to spend time. The products are designed by the most high agency people in the world, like Sam and Elon. For them, the optimal UI is a chatbox where you say exactly what you want. But for many people, they're again looking to waste time, spend time. They want browse based interface. They're not quite sure what they want. They can't always articulate it. The future of intent-based is chat makes me a little skeptical." How does the UI paradigm change in the next 12-36 months? Remain chat or change? @ekuyda @scottbelsky @gorkem @luclevesque?

@codyschneider The main issue is that Notion recording doesn’t open by itself like Granola and similar tools. This mean that there is a human in the loop that needs to activate it.

GTM Engineering today sales call ends notion was recording the whole time notion URL given to Claude code pulls transcript and: enriches HubSpot lead writes Gmail email draft with: - their pain points - outcomes they wish they could get - and next steps this all happens in minutes before next back-to-back sales call hey claude code, build this

@codyschneider @howcanbobhelp +1 on that. We have done the same and it’s works well.

@howcanbobhelp map the CRM data model before and provide it prompt, found it solved this problem for me

@lizwessel Thanks for that, great and simple.

@kushalbyatnal Totally aligned. It’s none stop hassling. I would add that it’s also making every one of these customers feel like a VIP doesn’t matter how much they paid.

@startupandrew Congrats! Big fan of shortwave and for sure this story made me want to try out tasklet

@TheSalesBull1 Indeed and adding a line “chat GPT” style isn’t helping.

So many websites are terrible So many landing pages are worse So many opportunities

@anothercohen ARR on the floor.

> vibe code a CRM > charge your own company a hefty subscription of $500k/year > pay the invoice > claim the $500k as net new ARR > do this monthly > after 4 months you're at $2m ARR > raise a large Series A Why is no one doing this??

@jjen_abel As a founder this clicked as I have seen it first hand with champions asking for guidance when the want to build the business case.

most people have no idea what they are doing in enterprise sales … selling a problem is too small thinking problems are often obvious, there’s no ah-ha in that most market speaking to same “pain” - so fast way to be commoditized and then paired with an unauditable big number that feels sales-y the magic is in naming the problem BUT selling executive alpha — something they can share with their c-suite and they say “look at this, how they flipped Y, and what it will do outperform X (ie measured metric) …”

Nothing beats the human connection you can get from messaging apps.

@salesxsaas And that’s why for now, we need a human in the loop.

Most GTM tools suck because the lack true context (true context = between the lines/gray areas) LinkedIn gives you background but no intent Emails hold deal velocity & intent but miss org dynamics Gong gives raw calls but can’t read non verbal cues or tone Press releases give you roadmap details but no real pain points Org charts give team structures but hide politics Tech stacks show you what tools they own but not how they’re connected or utilized Ultimately only YOU (the seller) can fill those gaps

@tuhinone @camillericketts Congrats!

Baseten’s day 0 bet was that inference was the technology that would enable the best user experiences AI could deliver–fast, smart, reliable, secure. And that those experiences would rely not only on a handful of giant general intelligence models, but millions of specialized models built by companies for their specific customers and use cases. Whether you’re a doctor, developer, lawyer, mechanic, researcher, construction worker, marketer, etc, you’re accelerated by specialized tools worthy of your craft. To me, this is one of the most meaningful promises AI can deliver on. We’re starting to see it now. Many of the main-character AI companies on the application layer are built on highly-specialized models for highly-specialized workflows–Abridge, Clay, Cursor, OpenEvidence, Hebbia, Mercor, Notion–these businesses are booming because customers love specialized tools. There are probably hundreds of custom models in production today. Soon, there will be thousands and then millions. All enabled by a high-performing inference layer. Inference has emerged as one of the hardest problems in modern AI systems. Delivering reliable, low-latency experiences requires deep coordination across distributed infrastructure, kernel-level performance, and software ergonomics—even world-class teams struggle to do this well. As a result, as consumers and developers, we’ve grown to accept sluggish performance, frequent downtime, and inconsistent quality across both application companies and model providers. Meanwhile, the demands on inference are accelerating: AI adoption is trending towards ubiquity with reasoning models that are orders of magnitude more compute-intensive. This will only increase as more companies catch on to the virtues of owning their end-to-end IP rather than relying on black-box model APIs on shared infrastructure. Whether we can realize the impact of this generational shift will depend on our ability to serve these models reliably at scale. We knew we could make the technology work, but the biggest delight of it all has been seeing what our customers do with it. The (many-model) future is bright.