Dee Johns

I’d add that the most important skill PMMs need to double down on in an AI-heavy world is judgement. AI is great at spotting patterns and drafting first passes. Where PMMs stay relevant is deciding what matters, what to trust, and what to ignore. That shows up in a few places: • Signal vs noise – AI can surface a lot of inputs fast. PMMs need to interpret them in context and decide which insights are worth acting on.• Framing and storytelling – AI can draft content, but it can’t truly decide wha ...Read More

For me, “AI-first” in PMM means redesigning our function around what AI agents can do – gathering and summarising data, generating content, and automating repetitive tasks – so humans focus on where we add unique value – strategy, judgment, and messaging that resonates. This differs from simply using AI to augment workflows – which just speeds up existing tasks. In an AI-first PMM function: Competitive intelligence – AI agents monitor competitor websites, news, social posts, and sales call trans ...Read More

I love this question. The longer I’ve been in Product Marketing, the more I’ve realised the craft is table stakes. The real shift happens when you build skills that shape direction, not just execution. A few that have mattered most for me: Commercial judgmentAt senior level, it’s about knowing where to spend energy. Not every launch or initiative deserves the same attention. Understanding how the business actually makes money – what drives pipeline, what improves win rates, what impacts retentio ...Read More

I’ve seen a few versions work, depending on company size and how complex the product and sales motion are. In most teams I’ve worked in, product marketers are aligned to a product area or portfolio. That keeps ownership clear and helps PMMs stay close to product managers and customer problems, rather than spreading too thin. Release and launch communications usually sit within product marketing, especially in small to mid-sized teams. As things scale, it can make sense to have more dedicated foc ...Read More

I think about AI as a way for PMMs to show up more consistently for the GTM org, not as a new mandate. At its best, AI helps PMMs: Stay close to real customer and market signals without heavy manual lift Respond faster as patterns shift Spend more time on judgement and decisions, less time gathering inputs Where I’ve seen the most value is in four areas: 1. Continuous signal miningAI is powerful for scanning sales calls, win/loss notes, support tickets, and feedback to surface themes that would ...Read More

For me, great messaging usually comes down to a few fundamentals done really well. First, be ruthless about clarity. If someone can’t quickly explain what the product does, who it’s for, and why it matters, the messaging isn’t finished yet. Most weak messaging isn’t wrong – it’s just trying to say too much at once. Second, stay close to real conversations. The best messaging I’ve worked on has been shaped by what sales and customers are actually saying, not just what sounds good in a doc. If the ...Read More

I don’t think roadmap influence comes down to choosing the right channels as much as using them at the right moments. Formal forums like planning cycles, roadmap reviews, and QBRs matter, but they’re rarely where influence starts. By the time those meetings happen, most decisions are already forming. In practice, the most effective channels are often informal and continuous: regular 1:1s with product partners where context is shared early, not as a surprise ad hoc conversations when new signals ...Read More

I don’t think the question is whether PMM creates a roadmap deck, but how that roadmap shows up in real customer conversations. In practice, the roadmap itself matters far less than how confident sales and success feel talking about it. Yes, product marketing usually creates a customer-facing roadmap view, but I’m careful not to treat it as a static asset that just gets handed over. The goal isn’t to show everything that’s coming, or to lock teams into dates. It’s to help teams tell a clear, cre ...Read More

What I've found is that the most impactful feedback loops aren’t defined by the channel, but by how clearly they connect customer pain to product decisions. Direct customer conversations are always the strongest input, especially when product teams can hear them firsthand. Sitting in on customer calls, post-implementation check-ins, or win and loss conversations together creates shared context that’s hard to ignore later. That said, what really moves the roadmap is synthesis. Patterns matter mor ...Read More

When everything is “AI-powered”, I try to treat AI as a means, not the message. In practice, that means: Starting with the problem that already exists without AI. If you remove the word “AI” and the message falls apart, it’s not ready yet. Being clear about where AI shows up in the workflow and where it doesn’t. Buyers are sceptical now – vague claims create more friction than excitement. Talking about outcomes people recognise from their day-to-day work, not abstract intelligence. Less “powered ...Read More