Lillian 🚀 Fractional CMO for tech startups

What’s the magic word? #GenAI #LLMs or just plain #Ai? Image credit: @ElenaVerna

@aslimilan @noahkagan I agree with this statement wholeheartedly cc: @noahkagan

@noahkagan Ideally you should take Meta to court. This is happening to millions of businesses. You need to stand up. Meta takes millions in revenue from business and banning or restricting access has serious life changing consequences.

Last Saturday night, 2:55 AM started the worst week of the year for me. Facebook restricted our ad account out of nowhere. Fifteen years of running Facebook ads. Over $20M spent cumulatively. I personally helped build Facebook Ads in the early days. And on a random Saturday night, an email landed saying our account was restricted, no reason given. 😞 I figured it would resolve itself. Our ads are straightforward comparison ads for products we promote on AppSumo. I called Facebook (you can actually call them), and the rep said they'd review it and have it cleared in 24 to 48 hours. I looked at the recent ads. Two had been rejected, both AI software ads. Nothing that should take down a whole account. Context: my last startup got permanently banned by Facebook. That ban killed our revenue from $150K a day down to $15K a day overnight. That's a story for another time. But sitting there at 2:55 AM, all of that fear came rushing back. 48 hours later, Monday morning. Still restricted. I called again. They said it looked positive and we'd get an email when it cleared. I started checking email obsessively. Nothing. So I went into Hail Mary mode. I reached out to Naomi, a VP of product. To the COO. To the CTO. To old account managers. To friends who work there. I even found a guy whose entire business is getting people's Facebook accounts unbanned. (Ours wasn't technically banned, just restricted, but yolo.) Every night that week, my family would go to sleep and I'd go upstairs and call Facebook ad support. I was depressed. I was frustrated. The thought running through my head was that 16 years of work was about to get erased because some intern or agency we'd worked with did something stupid I didn't know about. Thursday, 1 AM. I'm in the account again, scrolling through the restriction page, and I notice something I hadn't seen before. A line that says "data sources restricted." I click into it. It says: you're sending traffic from an adult site. WHAT!?! I sat there staring at it. That is not possible. I started digging to figure out wtf. It turns out there's a thing called pixel bombing. Pixels are public. Someone can grab your pixel and intentionally place it on bad sites to get you banned. I didn't know this existed until that moment. Maybe it was this? Then I dug deeper and realized years ago we'd built a product, and someone had taken our AppSumo Facebook tracking pixel and put it on that product. A random user of that product put it on a adult site. Facebook saw traffic from an adult site coming into our pixel and flagged the whole account. I removed the pixel from the product. Blocked the offending sites in Facebook's settings. Submitted a new review request. The next morning, the account was unlocked. Poof. A few lessons for others: - Audit your pixels. Know where they are placed. - Have a separate ad account running as a backup so if something happens you are not dead in the water. - Get an account rep account support set up before you need it. Or find an agency who has direct Facebook contacts. - And if you're a smaller company doing 50% or 75% of your revenue on one channel, build a hedge. The day Facebook decides you don't exist, you don't. One thing that was a quiet positive in the middle of all this: our ads were dark for 48 hours and the revenue impact was smaller than I expected. Facebook ads are 5-10% of our business. Worth knowing what each channel actually contributes when it goes to zero. That was the worst week of my life in the past years! And it came down to a pixel I forgot we had, on a product I forgot we built, on a site I never visited.

@LeilaHormozi Congratulations!! So happy for you :)

Surprise 😇

"Lillian, this all sounds great in theory, but how do you know if our go-to-market strategy will actually work before we spend months building funnels and scaling paid ads?" I get this question three times a week. Here's my answer. You don't validate with research. You validate with revenue. Here's the 3-step test I use with every client. I call it the 5-Day Market Reality Check. Step 1: Run a 2-week competitive analysis You're looking for momentum signals, not a comprehensive picture. Is the market growing or stagnating? That's the only question you need answered at this stage. Step 2: Set up a simple paywall test No complex funnel. A basic gate that requires a small payment to access your core value. That's your truth test. Step 3: Watch the wallets, not the words Surveys lie. Focus groups lie. Actual payments don't. Two to four weeks of real buying behavior tells you everything that six months of market research would obscure. I used this with Morgan, who had two built marketplaces and needed to choose between them fast. Tech hiring (saturated) vs. remote jobs (emerging). We ran the test. The data was unambiguous. Morgan pivoted, generated first revenue in weeks, and avoided six months of building in the wrong direction. I keep a running spreadsheet of these tests across industries. The pattern holds every time. Follow me if you want the actual framework templates. I share the working systems, not just the case studies. #GoToMarket #StartupStrategy #MarketValidation

Most "AI-native" marketing teams aren't AI-native at all. They're just 5 people using ChatGPT separately. ... Same tools. ... Different prompts. ... Zero shared memory. It looks sophisticated from the outside. Under the hood, it's still human-to-AI, one person at a time. The difference between "using AI" and becoming AI-native comes down to architecture. Here's how I think about the 4 levels: 𝗟𝗲𝘃𝗲𝗹 𝟭: 𝗔𝗜 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝗰𝗲 You → ChatGPT or Claude. Research. Writing. Summaries. Meeting notes. Useful. It's also where most teams stay because the gains are individual. Nothing compounds. 𝗟𝗲𝘃𝗲𝗹 𝟮: 𝗥𝗼𝗹𝗲-𝗧𝘂𝗻𝗲𝗱 𝗔𝗴𝗲𝗻𝘁𝘀 Content agent. SEO agent. Paid media agent. Outbound agent. Sales-call agent. Each agent owns a workflow, not a task. The question shifts from: "What can AI do?" to "What should this agent own?" 𝗟𝗲𝘃𝗲𝗹 𝟯: 𝗧𝗵𝗲 𝗖𝗼𝗺𝗽𝗮𝗻𝘆 𝗕𝗿𝗮𝗶𝗻 Agents stop working from isolated prompts. Instead, they pull from shared context: • Customer calls • ICP research • Winning campaigns • Brand guidelines • Objections • SOPs • Case studies This is where AI starts compounding. One insight becomes available to every agent. 𝗟𝗲𝘃𝗲𝗹 𝟰: 𝗖𝗹𝗼𝘀𝗲𝗱-𝗟𝗼𝗼𝗽 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗦𝘆𝘀𝘁𝗲𝗺 Sales calls create content angles. Content generates leads. Leads improve outbound. Outbound updates the ICP. The ICP updates the company brain. The company brain improves the agents. The marketing team stops behaving like a collection of specialists. It starts behaving like an operating system. We're at Level 4 at Data-Mania. 𝗪𝗵𝗮𝘁 𝗜'𝘃𝗲 𝗹𝗲𝗮𝗿𝗻𝗲𝗱 𝘀𝗼 𝗳𝗮𝗿: - The bottleneck is better knowledge architecture. - Most teams are still experimenting with basic prompts. - The teams that win build systems that learn autonomously. Which level is your team at today? 1, 2, 3, or 4?

I'm not gonna lie, the @Meta layoffs are some of the most dystopian I've ever seen. They got told to work from home, they were sent the emails at 4AM in the morning. Those who weren't impacted have software on their computer that tracks their every move, preparing AI to take their job as well. They're literally training the AI that will eliminate their position as well. Meanwhile, Meta is raking in RECORD PROFITS. I am a massive, unapologetic AI enthusiast. Yet, this is NOT the future I had in mind. I wish for Meta to crash and burn. This is not the way. Literally nobody benefits from this.

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

@LouiseDSadeleer @TellaHQ That’s great! Congrats 🎈

my biggest flex is that this was my first month on YouTube with @TellaHQ wanna know how I did this?

@LouiseDSadeleer @Remotion Also all those subs cause way more than descript

In 6 months, only insane people will be editing their videos manually. Here's how Claude edits my videos: - Rough cut (silences, filler words, mistakes) - Add images or video memes (Claude finds in home dir) - Create motion graphics with @Remotion - Add sound effects (YouTube or @ElevenLabs) - Cuts long to short video for socials (9:16) - Bonus: Tella MCP for screen recs Watch my full demo on agentic video editing 🎥

@LouiseDSadeleer @Remotion Honest opinion - too much work. Better to hire an editor

If AI can mistake a Reddit joke for advice, it can misunderstand your website too. It copied a joke from Reddit. Funny. But it exposes a serious problem for business owners. AI tools like ChatGPT, Perplexity, and Gemini only recommend websites they can clearly understand. We ran our site through Framer’s free AEO Scanner. Score: 88/100. But it flagged one issue I completely overlooked: Not enough contextual internal links. I assumed navigation and footer links were enough. They’re not. AI uses in-content links to understand: ➤ Which pages matter most ➤ How topics connect ➤ Which page is the source of truth If your blog posts don’t link to related services, pricing pages, and core landing pages, AI may struggle to understand your business. And if AI doesn’t understand your business, it won’t recommend it. Framer’s AEO Scanner found this issue in under 10 seconds. It shows: ➤ How AI-readable your site is ➤ What’s hurting visibility ➤ What to fix first The tool is free and works on any website. If your site generates leads, I’d check your score today: framer.com/aeo --- #framerpartner image credit: @petergyang

How to know if something is written with AI: it spends nine paragraphs telling you what it isn't.

This is INSANE!! We literally just replaced four ad dashboards with one chat window. If you manage paid ads across multiple platforms, you're probably wasting hours every week on dashboard switching. Case in point, running Google, Meta, LinkedIn, and TikTok in one sprint would mean juggling: ➤ 4 dashboards ➤ 4 billing systems ➤ 4 completely different mental models That overhead slows testing velocity more than budget constraints ever could. We recently added Synter to our stack, and - poof, overnight we’re able to replace all four ad dashboards with one chat window. Unbelievable (but true). Here’s how it works: It runs all four platforms from a single interface, and because it works with Claude and MCP clients, we’re able to manage everything from the same workflow we’re already using. Imagine prompting: … "Shift budget from Meta to LinkedIn." … "Launch a retargeting campaign for this segment." … "Generate three ad variations." ✅ Just one prompt and DONE. The good news is that if you're running paid for a lean team or solo across multiple channels, the setup is super straightforward. Check it out here today: syntermedia.ai/?utm_source=in… #SynterPartner

@ryangerritsen Lay off the AI dude

Here we have an excellent summary of what is happening between The U.S., Europe, the London banking system, Canada and other Countries. We are watching a dismantling of the old system, one that central banker Carney would have preferred to continue but is now as we watch him fly around the world is desperately trying to help create a system or what he likes to say a “new world order” What’s diabolical is he’s willing to sacrifice Canadians jobs to do it.

8 GTM truths most startup teams learn too late. Your growth team shouldn’t look like an ad agency. → It should look like your engineering team. You don’t need more campaigns. → You need one system that compounds. “Let’s try this tactic” is not a strategy. → “Let’s test this hypothesis with clear success metrics” is. Attribution isn’t a nice-to-have. → It’s the foundation of every decision. Repeatable > Remarkable. If your marketing team can’t explain the conversion math, → You hired the wrong team. Most “marketing problems” are actually systems problems. If you can’t connect a dollar spent to a dollar earned, → Stop spending until you can. Follow me for practical frameworks on building AI-native GTM systems that scale.

@manujagro 💯

@Strategy_Gal The shift from campaigns to systems thinking is probably one of the biggest changes happening in modern GTM right now.

Most B2B companies don’t need more marketers. They need GTM engineers. Having built AI-native GTM systems for Fortune 500 teams, the distinction is obvious. Marketers ask: “What campaign should we run next?” GTM engineers ask: “What system are we building?” Marketers optimize: Ad copy, landing pages, email subject lines GTM engineers optimize: Conversion architecture, attribution models, and feedback loops Marketers celebrate: Engagement rates and follower growth GTM engineers celebrate: Pipeline velocity, CAC payback, and repeatable acquisition systems Marketers say: “Let’s try this tactic.” GTM engineers say: “Let’s instrument this before we scale it.” The companies that scale fastest treat go-to-market like engineering. With rigor. With measurement. With repeatability. That’s GTM engineering. If you don’t know the difference, you can lose 6–12 months chasing tactics that never turn into a repeatable growth system. Follow me for practical frameworks on building AI-native GTM systems that scale.

The fractional CMO market is splitting into two camps, and most founders don't fully understand their options. Camp 1: Advisors. They show up two to four times a month, give you strategic recommendations, validate your ideas, maybe review your campaigns. then they leave your team to execute, with a small bit of daily async advisory support. This works if you already have a strong team and just need senior-level perspective. Camp 2: System engineers. They embed with your team, build your measurement infrastructure, align everyone to KPIs, implement the framework, and hand you a repeatable playbook. They treat GTM like an engineering discipline: diagnose the problem, design the solution, build the system, measure the output, iterate. Here's how to tell the difference in 90 days: Advisors give you crucial on-demand strategic support and training for your team, but generally don't hand over any deliverables. System engineers leave you with dashboards, attribution models, and a team that knows how to execute without them. Most $1-6M ARR technical companies think they'll save money with a junior team + an advisor (Camp 1), but what actually generates the highest ROI are AI-native systems that can run on their own (Camp 2). At Data-Mania, I offer both advisory and GTM engineering. I don't just tell you what to do. I can also build the measurement framework, implement the KPI structure, train your team, and make sure you can run it after I step back. Which camp does your company actually need right now?

I never even started it a paid subscription with clay because it made no sense against what I could do with Claude code and N8N. When I hear go to market people saying they could never get rid of clay and was very confused…. Thinking they must use it for something that I never did because otherwise duh.

I finally cancelled my Clay subscription. (And before the "how do you live" comments start: I’m officially on the Free Plan now. Screenshot attached.) I haven’t stopped using it. I just stopped paying for it. A year ago, this wouldn’t make sense. Now? Claude Code can handle a big chunk of what people were using Clay for. → Lead sourcing → Enrichment → Filtering → Basic workflows All doable without paying for Clay. Which raises a slightly uncomfortable question: How many people are paying for Clay… out of habit? And not necessity. Because if you’re running things yourself… You probably don’t need a paid plan anymore. You can offload way more than you’d expect. Things like: → lead sourcing, enrichment & qualification → personalization of messages → campaign top-ups into your sequencer of choice Which means you’re not burning credits on every step. That said… This doesn’t mean Clay is “dead”. It just means the role is changing. Something that I Slacked Mohamed Chahin about this weekend. So, I recorded a video explaining: → what the tech stack for 2026 looks like → where Clay can be replaced by Claude Code → where Clay cannot be replaced → how to decide if you need to explore the new tools like Claude Code This is exactly how I’m running things right now. If you want in: Comment “STACK” and I’ll send it over.

10,000 MQLs in 10 months. $5 per lead. No ad spend. Same content. Different architecture. This is what I mean when I say the CAC problem is an architecture problem, not a budget problem. Full breakdown: youtube.com/watch?v=C39ymR…

80% of leads fall into the gap between marketing and sales and… are never followed up on. Unified teams: 30%+ MQL conversion. Siloed teams: 13%. The MQL wall is a systems problem, not a people problem. Full video: youtube.com/watch?v=C39ymR…