Dan Sullivan

Just launched! 🚀 I started a new Substack for Strolid, Inc. this week called “The Conserver,” and I just dropped my first deep dive — about Disney’s massive opportunity with conversation intelligence. How deep? We’re talking about potentially $2 billion in hidden value. 15-20% churn reduction on streaming. 25% better guest satisfaction scores. $300-500 million in new upsell revenue. The secret sauce is vCon technology. It turns all those trapped conversations into secure, portable, analyzable intelligence (with consent!) that works across platforms. You already figured out this isn’t just a Disney story. How many companies are sitting on conversation goldmines they can’t access because everything’s siloed? Check out my complete analysis at https://lnkd.in/eKuRh9Ei. #AI #ConversationIntelligence #vCons

22

6 Comments

Two Silicon Valley veterans Biz Stone and @Evan Sharp have launched Tangle, a new “antidote” social app focused on intentional living rather than engagement metrics. Backed by $29m, it prompts users to share goals and reflect daily. Twitter co-founder Biz Stone said building healthier digital tools is “difficult work — but worth it,” reflecting tech leaders’ reckoning with social media’s harms.

7

1 Comment

DeepDivers, the company behind the custom sales CRM 'Trackit,' secured seed funding from Mashup Ventures. Trackit offers flexible, customizable CRM solutions for large enterprises, rapidly gaining major clients. https://lnkd.in/gkyJPp3Z

1

LLMs. LRMs. Autonomous agents. Prompt frameworks. Copilots. Gemini. OpenAI. Claude. “AI features” your vendor just launched. Cool. But none of that can actually run a nonprofit fundraising program. Not LLMs. Not autonomous agents. Not even with OpenClaw or another agent TBD wired into your stack. Because those systems generate language and automate workflows. They do not produce statistically validated predictions. And fundraising decisions require exactly that. They cannot reliably: • predict who will give • forecast campaign revenue before you spend • suppress mail without destroying net revenue • detect churn before donors lapse • calibrate probabilities on donor data • validate lift with holdout testing • orchestrate next-best actions across channels They can write the appeal. They cannot decide who should receive it. And that decision layer — targeting, suppression, channel selection, ask amount, revenue forecasting — is where millions of dollars in net fundraising performance actually live. Right now a lot of nonprofit “AI strategies” look like this: LLMs • agents • some automation Which basically equals: AI copywriting. What’s missing is predictive donor intelligence. That’s the layer between your donor file and your campaign decisions. We wrote a white paper explaining the gap because the confusion right now is massive. https://lnkd.in/eFzwNMQr Curious how many people in nonprofit tech disagree with this. #AI #FundraisingStrategy #PredictiveAI #NonprofitTech #DonorIntelligence

17

Veteran Podcast Launch Coach Jennie Bellinger Endorses DoneCast After Launching Latest Show on the Platform FOR IMMEDIATE RELEASE Glendale, CA — February 2026 — DoneCast, the innovative AI-driven podcast production platform, has received a glowing endorsement from esteemed podcast coach Jennie Bellinger. Known for her expertise in podcast monetization and launch, Bellinger utilized DoneCast's beta version to create and launch her latest show effortlessly. Jennie Bellinger, who began coaching podcast launches and monetization in March 2020, has a proven track record with over 200 successful podcast launches. She praised DoneCast for its simplicity and efficiency: "My most recent show creation and launch was completely done using the beta version of DoneCast. From idea to first episode recorded was under two hours, and everything was taken care of including title, show art, description, a trailer, and distribution to the major podcast apps. It was so simple and easy!" Bellinger plans to recommend DoneCast to her clients, citing its user-friendly platform as a game-changer in the podcasting industry. Scott Gerhardt, Founder of DoneCast, expressed his excitement over Bellinger's endorsement, stating that her support validates the efficacy of their platform. "Jennie is a savvy veteran of podcasts, both as a host and a coach. Her credentials are tremendous, and we are honored to be working with her!" About DoneCast DoneCast is a revolutionary platform that leverages AI to streamline the podcast production process, making it accessible to creators by automating tasks from recording to distribution. For more information, visit DoneCast.com. About Jennie Bellinger Jennie Bellinger is a renowned podcast monetization and launch coach. She is the host of the Badass Direct Sales Mastery podcast and has been instrumental in helping podcasters transform their shows into profitable ventures. Connect with Jennie Bellinger. Media Contact: Scott Gerhardt, CEO

2

Welcome Andrew Lau, Co-Founder & CEO and Chris Ward, CRO at Jellyfish on this episode of 🔥 The Lantern 🔥 Jellyfish is a Boston-based, high growth company helping enterprises drive Dev AI productivity with 700+ customers. 🔍 What happened at Jellyfish in 2025? 🔎 2025 was a big year of growth. Jellyfish went from helping companies drive engineering productivity to becoming the command center for Dev AI transformation. As companies went from using one vibe coding tool to juggling 5 or 6 (like Cursor, Windsurf, Copilot, Augment Code, etc.), they turned to Jellyfish to measure what's actually working. Like Salesforce for engineering leaders. The data Jellyfish publishes on how Dev AI adoption is changing the game has become must-read material for CTOs everywhere. 🤝 Why did Chris Ward recently join Jellyfish as CRO? 🤝 Chris had wrapped up an extremely successful run at Vercel, where he experienced 60x revenue growth over four years, as the company’s valuation climbed from $1.1B to $9.3B. He was supposed to take 6 months off...until he found out about this can’t miss opportunity at Jellyfish. When he saw the founding team came from the Endeca Mafia, he started back-channeling, and seeing the platform up close sealed it. Chris has spent his whole career watching CTOs and CPOs argue in boardrooms about what engineering teams are actually doing and Jellyfish solves this problem. Their newest AI Impact product helps engineering teams measure AI ROI, optimize tooling investments, and build AI enabled teams. 🗺️ What's critical for Jellyfish to thrive in this market in 2026? 🗺️ Andrew's message to builders is to be adaptive. The world is changing every three weeks. Operators, product, and GTM leaders all have to be willing to turn fast. The Dev AI transformation is creating a massive opportunity for companies that can help enterprises disambiguate what's working across their AI tooling stack.  Jellyfish is positioned right at that intersection! Chris witnessed this firsthand at Vercel, watching a large customer who bought 4 different vibe coding tools for 20,000 developers with zero insight into adoption, impact, or where the bottlenecks were. 🤔 How can we help Chris, Andrew & Jellyfish grow? 🤔 We need to lean into the Dev AI transformation together, especially here in Boston, to take advantage of this moment to educate each other, share techniques, and harness the wave together. As Jellyfish grows, Boston grows. If you’re building in the Dev AI space or navigating AI tool adoption across your engineering org, connect with Andrew & Chris and the Jellyfish team! The Lantern is brought to you by MGMT Boston, Rho, & Invest Northern Ireland – Americas this month

63

9 Comments

Here is another snippet from the AI Applied in Community presentation that Fabrice Jordan and I joined forces to deliver to the Congressional Black Caucus Foundation. We spun the wheel and vibe coded an app: Imagine trying on clothes without ever stepping into a fitting room. That's the idea behind a virtual try-on app. It works by allowing users to take pictures of themselves and of clothes, then virtually putting the clothes on their body. Integrating such tech with e-commerce stores can significantly enhance the shopping experience. This approach embodies the entrepreneurial spirit: identifying problems and developing AI-powered solutions. #AI #eCommerce #VirtualTryOn #Innovation #Entrepreneurship

2

Ride the fractious horse 🐎 Had a blast talking with Harrison Chase from LangChain the other day to a great group of founders, builders and investors about building agentic systems. One learning I shared: our team builds effective agentic systems by spending way more time doing than speculating. 🏇 In other words, we "ride the fractious horse": New models drop daily. New frameworks emerge constantly. Best practices get declared and discarded overnight. By the time you survey the landscape and theorized about how today's reasoning models can serve your system, both the landscape and capabilities have shifted. So we write playbooks instead of adopting them. The only way to develop those playbooks? Build and experiment at the fastest possible rate. ✈️ Wilbur Wright laid a great analogy back in 1901: He'd just realized that existing "standard" measurements of lift and drag were wrong, and that solving flight meant spending serious time actually trying to fly (previous "pilots" had logged minutes, at most, of cumulative airtime across all experiments). From his Chicago speech (this guy was such a clear writer btw): "There are two ways of learning how to ride a fractious horse: one is to get on him and learn by actual practice how each motion and trick may be best met; the other is to sit on a fence and watch the beast awhile, and then retire to the house and at leisure figure out the best way of overcoming his jumps and kicks." "The latter system is the safest; but the former, on the whole, turns out the larger proportion of good riders." As for planes: "It is very much the same in learning to ride a flying machine; if you are looking for perfect safety you will do well to sit on a fence and watch the birds; but if you really wish to learn you must mount a machine and become acquainted with its tricks by actual trial." We're not inventing flight, but constantly evolving LLMs and probabilistic workflows won't behave as you hope on first contact. If you want to figure out how to build effective products around those fractious beasts, get on the horse (keyboard) and start riding.

73

5 Comments

“Burn the Playbook” is “a book for everyone,” especially those wondering how AI will impact their careers and livelihoods. Author Joe Pulizzi spoke about the book at the Bay Area Content Marketing Meetup hosted by Rich Schwerin. Here is Rich’s introduction, complete with name-drops: Pam Pulizzi, The Orange Effect Foundation, Brian Piper, • Kyle Akerman

29

12 Comments

Collaborating with Patrick Burke and the Beyond Banyan team on The Enterprise Wall was one of the more enjoyable projects I've worked on. Most of what's in here didn't come from a framework — it came from months of client conversations and a lot of careful listening to what founders actually mean when they describe a deal that won't move. The five signs aren't theoretical. They're patterns we kept hearing, named precisely enough that founders can recognize themselves in the first two pages. If it describes where you are, the offer in the post is real. No agenda. Just a direct conversation about what's actually in the way.

14

Ads in Clay officially launches this Wednesday for enterprise customers. We're coming out of beta! This might be the most electric product-market fit we've seen for a new feature in a long time. I met with 8 prospects about Ads last week and they couldn't get enough. So, yesterday I sat down with the godfather of Ads, Clay engineer Alex Reznik, to share why we built Ads and how we used it to decrease our Cost-Per Qualified Lead by 80% with just one click. He is going to tell you the full Ads story. Where the idea came from (Bruno is claiming credit), how Alex went rogue to build it on his own, what the ads orchestration process actually looks like for growth marketers today (super painful and wasteful), and how we're already getting match rates of 90% on LinkedIn and 60%+ on Meta for customers like Slack, Anthropic, and Rippling. Plus, we share all of the coolest use cases and plays we're running internally at Clay (check out below) But that's not all! As part of our "How Clay Uses Clay" series, we’re hosting a LIVE workshop on Thursday, February 26th, to help YOU build these Ad use cases end-to-end. Our Head of Growth Davide Grieco will show you exactly how to build the entire Clay Ads flow in 30-40 minutes. You'll leave the session with an automated workflow, higher match rates and way better targeting. Sign up here: https://lnkd.in/eFa78RrD Here are two plays we're already using this for internally just to whet your appetite: PLG Exclusion: We have hundreds of thousands of people across our ecosystem - customers, users, competitors, employees, agencies. Showing ads to them was burning up to 20% of our budget. Dynamic exclusion lists now auto-refresh so that spend goes to net-new prospects. Full-Funnel ABM: Because audiences are dynamic and constantly updating, you cater content to funnel stage. Cold accounts get awareness ads. Medium engagement gets social proof - case studies, webinars. Hot accounts get leadgen ads direct to sales. All programmatic as engagement scores go up.

354

46 Comments

“Skip the PRD and go straight to the prototype.” A ton of great nuggets in this episode with Lenny Rachitsky and Amol Avasare.

3

1 Comment

Aways fun talking AI and Bio with Andrew Dunn from Endpoints News! We cover a lot of ground, but there's one persistent theme: 𝗔𝘀 𝗔𝗜 𝘁𝗶𝗺𝗲𝗹𝗶𝗻𝗲𝘀 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗲, 𝘁𝗵𝗲 𝗴𝗮𝗽 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗧𝗘𝗖𝗛𝗡𝗢𝗟𝗢𝗚𝗬 𝗮𝗻𝗱 𝗽𝗮𝘁𝗶𝗲𝗻𝘁 𝗜𝗠𝗣𝗔𝗖𝗧 𝘀𝗲𝗲𝗺𝘀 𝗼𝗻𝗹𝘆 𝘀𝗲𝗲𝗺𝘀 𝘁𝗼 𝗴𝗿𝗼𝘄. Some thoughts on what that means and what we can do about it…   𝗧𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗔𝗜 - There’s a mismatch between where AI is working well (early discovery, lead optimization) + the big drivers of risk/cost in drug discovery (target selection, toxicity, clinical, commercial) [1]. But that's changing with AI progress in target discovery [2], toxicology [3] and new AI tools for clinical development [4] and commercial pharma [5] 𝗦𝗵𝗶𝗳𝘁 𝗟𝗲𝗳𝘁 - As AI capabilities shift right, there's an opportunity to incorporate them earlier in the process as a filter for early discovery. We're already seeing protein models bake developability into sequence generation [1] and synthesizability-guided chemical design [2] - but the real unlock will come from stacking properties and integrating them more deeply into the models [3] 𝗧𝗵𝗲𝗿𝗮𝗽𝗲𝘂𝘁𝗶𝗰 𝗔𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁 - AI models trained on public literature over-index on academic targets and data from non-human model systems, hurting their performance on real-world discovery tasks. Aligning AI models to human biology and therapeutically relevant problems is a major challenge, but we're seeing progress across the stack -- from few-shot learning [1], in situ human data generation [2], therapeutic proxies [3] and even whole organ screening [4] 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 - Most promising drugs never see the clinic and many of those that do drop out for external/ macro reasons, creating a buyers market for in licensing. As AI gets better at predicting clinical risk [1], sizing commercial opportunities [2] and accelerating trials [3] we should see an rise of AI-native biotechs [4] rescuing, repositioning and purposing promising late-stage assets where they have differentiated insight and strategy. 𝗠𝗶𝘀𝗮𝗹𝗶𝗴𝗻𝗲𝗱 𝗘𝘅𝗽𝗲𝗰𝘁𝗮𝘁𝗶𝗼𝗻𝘀 - Lastly, we need to reposition AI as an enabling technology, not just a productivity tool. The original sin of TechBio was the promise of cheaper and faster drugs it would never be able to deliver. Instead we should focus on what new capabilities AI is enabling — expanding druggable targets [1], discovery novel biology [2], enabling new therapeutic strategies [3]. Even if this does nothing to improve the cost or speed of a drug approval (which I think it will) it will give us better drugs for more diseases and more patients, which in my book is even ore important! Curious what others are seeing + doing to close the translational gap? https://lnkd.in/daYXihS6

145

14 Comments

I’ve been seeing lots of vertical AI founders join the Everything Marketplaces community recently. It looks like many are exploring layering on or even pivoting to a marketplace model once they understand the importance of having a path to growth & defensibility.

7

I popped up in Authority Magazine this week. Still slightly surreal. Still very grateful. I shared five things founders actually need to build a highly successful startup. Not the 'vibes' or the hustle myths. The real stuff that shows up in the data. A few numbers worth grounding this in: • Around 90 percent of startups fail globally. • CB Insights shows 38 percent fail because they run out of cash, often driven by poor strategy and unclear positioning. • Only about 1 in 10 UK startups make it past 10 years, according to ONS data. Those odds improve when founders get clarity early. On context. On customers. On what problem is genuinely worth solving before burning time and capital. The piece reflects a lot of what we are building at SuperRise and why. Fewer guessy decisions. More informed ones. If you are building in B2B and want a grounded take, give it a read: https://lnkd.in/esheUh2h Curious what you would add to the list.

41

8 Comments

After a recent workshop with small business owners in Massachusetts, several founders reached out with a similar reflection. Not about the content itself. But about something else. Clarity. Not from more information. But from seeing how things actually connect. Because most founders are not lacking ideas. They’re not lacking effort either. What they’re missing is structure. Not more effort. Not more ideas. Revenue decisions, hiring, operations, growth… All moving, but not always in the same direction. Simple, but not easy to fix. That’s where most businesses get stuck. Not because they don’t know what to do. But because they don’t have a clear way to connect decisions over time. Most businesses don’t need more ideas. They need a way to make their decisions compound.

27

CMO Alliance San Francisco – and that’s a wrap! I had a blast sharing my hot takes on Gen AI’s next biggest evolution, agentic AI. For those not yet familiar, think of AI agents like instruments that your team play in an orchestra. 🎼 The magic doesn’t come from a bunch of soloists playing off separate sheets. Like with any high performing team, it happens when your entire team plays together in harmony. With agentic AI, this looks like a system of proactive, always-on agents that “talk” to each other. They allow you to extend your team's capacity by tackling the extraordinarily time-consuming analytic precision. Your team is then free to focus on the omni-channel strategies and creative expression that truly differentiates your brand! Next stop on our Siteimprove.ai roadshow: Content Marketing World San Diego. Stay tuned for more stories on how agentic content intelligence is changing the game. 

83

4 Comments

Amazing talk with Brian R Johnson, Co-founder of Deepm.AI With over $3.5 Billion in product sales lift on Amazon. Full episode live on https://lnkd.in/ePUqpp-6

3