A year ago I had no idea what "GTM" even stood for properly. This week marks a full year in this space, and I want to be honest about how it actually went. It wasn't a straight line up. I made mistakes I'm still learning from, got rejected more times than I'd like to admit (including ones where I thought I had it locked in), sent outreach that probably annoyed people, and definitely overcomplicated things that didn't need complicating. But somewhere in that mess, I also got a lot right. Helped generate hundreds of meetings for the teams I worked with. Built systems that saved real money instead of just looking good on a slide. Got to mentor people who were where I was a year ago. Cracked opportunities I didn't think I was ready for. And met genuinely sharp, generous people who taught me more in a DM than most courses ever could. I also want to be upfront about something else. Some of what I posted here before was AI-slop. Generic clickbait content that sounded like everyone else's, because I was more focused on posting than on actually saying something true. I regret that, and I'm done doing it. So starting today, I'm going to actually document this. The mistakes, the stuff that didn't work, how I'm thinking about GTM as it keeps shifting under all of us, what I'd do differently, what's actually working right now. Not polished takes. Just what I'm seeing and learning, as it happens. If you're building in GTM, or just figuring out this unique intersection of sales and taste and AI, stick around. Would love to hear what you're seeing too.

When you come back from holidays… And Leexi has released so many cool features 👀 The one I'm most excited about: meeting → notes → action items → your task manager. All your to do from your meetings directly in Google Tasks or Microsoft To Do, automatically. Most AI notetakers stop at the summary. The summary is not the job. The follow-up is the job. Curious what else landed while I was away 😅

The one skill that matters in the age of AI And 90% of professionals are still not using it This is not AI engineering It is not vibe coding your next app Or even forward-deployed engineering It is so simple a high schooler can do it Here is how one Google AI Product Manager is using it to: - Create daily content for 350,000 product managers - Run a 115,000-star GitHub repo - Manage a FAANG job This is skill is becoming a manager of AI agents See the video for a preview Comment Agents to get the complimentary workshop AI Makerspace, Innovation DuPage, College of DuPage DeVry University, Polsky Center at the University of Chicago IEEE, IEEE Women in Engineering, Society of Women Engineers #IBMChampions Are you using it: Scott Hubbard, Maham Aftab, Ph.D, Umar Jamshed?

This is the hottest skill in AI 90% of managers are not yet using it It does not matter: • How many AI certifications you collect • How many impressive demos you watch • How many AI tools you test None of these automatically prepares you for the future of work. A Google Product Manager is already using this exact skill to: - run a 115K-star open-source project - publish a newsletter to 100k #productmangagers - manage a FAANG role This is the skill every manager needs to learn next. Comment AGENTS to get access to the session.

One skill will define who thrives in the future of work. And 90% of professionals are not learning it yet. A Google Product Manager is already using this skill to: • Run a 115K-star open-source project • Maintain a demanding full-time role • Avoid 18-hour workdays • Accomplish more without building a massive team This is not another AI tool or productivity hack. It is a new way of working, and one skill we will all need to learn. Watch the video to discover what it is. Comment AGENTS for access to Skilium’s complimentary 30-minute session. #FutureOfWork #AIAgents #ArtificialIntelligence #Skilium

🧠 Thinking Like a Noogler | Day 7 7 days into this journey, one lesson stands out. I started this series to understand how Google builds products. Instead, I’ve started changing how I think. Whenever I come across a problem now, I ask myself: “Would this solution still work if a billion people used it?” That one question changes everything. If answer is NO, then I am probably solving a symptom, not a problem. Now I’ve shifted my focus from fixing a problem to solving it at scale. Whether it was building an AI solution to manage communication for 400+ guests or imagining Google as a Decision Engine, the thought process was the same: Start with the problem. Build for scale. Keep it simple. To me, that’s what Googleyness is all about. 🧠 Noogler Mindset #7 Don’t just solve today’s problem. Build a solution that still works tomorrow, for everyone. What’s one problem you’ve solved that could help thousands more? #ThinkingLikeANoogler #Googleyness #ProductThinking #Innovation #BuildInPublic #Strategy

Agree or disagree?.... The digital marketer of 2026 isn't a marketer anymore. Tools got easy. Anyone can launch a Meta campaign in 15 minutes now. AI writes the copy, picks the audience and optimises the bids. The technical skill that was used to define this job is worth almost nothing today. Companies noticed. That's why Microsoft, Meta and Cisco have laid off employees this year. Not because AI is smarter than people. Because AI is good enough at the entry-level work that used to justify those salaries. Here's what I think is actually happening. The job is splitting into two paths. One path is running the tools. That path is shrinking fast and it's not coming back. The other path is understanding the business behind the ads. "Why isn't this converting? Where is the real leak? What's the actual math on this offer?" That path is growing because no algorithm can walk into a founder's office and have that conversation yet. I'm choosing the second path. Not because the first one is beneath me, I built my foundation there. But because tools change every year and business fundamentals don't. If you're in this field, the question worth asking yourself isn't "which platform should I learn next?" It's "am I becoming a strategist or staying a technician."

‘I work in tech at Linkedin’ Just read this. Immediately thought ‘well that’s an easy job’. The tech on this site is dire. Has been for years, and never changes, except to enshittify it even more - note the new inability to copy any text. Which is infuriating when you want to quote someone. Presumably because their tech is too stupid to identify when a bot is mass copying. So just make it worse for every user. Yeah, that’s the spirit. Like dealing with an old school, communist state. And as for the algorithm. Oh my. The failure to surface or distribute quality content is world class. So ‘work in tech at LinkedIn’ is 🤮 But indicative of the legions of BS jobs that AI will wipe out. This is the elephant in the room - just how many people are doing worthless work? You only have to look at the stats at ‘engagement at work’ to answer that. Maybe at ‘winners’ like LinkedIn you can kid yourself your product is good. But that’s not how it works. A lot of winners are terrible products. It’s time we tried harder to remedy this.

The AI outbound messages people are sending me are embarrassing. Wrong first name. Wrong company. Random em dashes everywhere. And the same tired opening line: "I hope this message finds you well as you continue to drive impactful growth at [Company]." Nobody talks like that. Nobody. If you want to do outbound the right way and land more meetings with your prospects, follow these tips: → Do the research. Read their LinkedIn. Look at their recent posts. Understand what they care about before you hit send. → Find common ground. Same school. A post they wrote. A hire their team just made. Use it as your opener. → Write like a human. Short. Casual. Direct. If it reads like a robot, delete it and start over. → Skip the pitch. Your first message shouldn't be about your product. It should be about them. → Take your time. 500 lazy DMs a day gets you 0 replies. 10 thoughtful ones get you meetings. The reps winning at outbound care about every message they send.