Shaun Clowes

The effectiveness of an AI product is directly tied to the volume, quality, and recency of the data context provided to the model.

"LLMs can only be as good as the data they are given and how recent that data is. They're ultimately like information shredders. They are limitless information eaters. You can never have enough informa..."

AI product development is primarily a data management challenge rather than a modeling or prompting challenge.

"It's a data management problem. It's getting access to good data, getting access to high quality data, getting access to timely data and getting it to the LLM to get the LLM to make a smart decision...."

Treating a career as a 'bingo card' of diverse experiences across different business models and functions builds unique versatility and pattern-matching skills.

"My career has been a little bit like a bingo card. I've always been looking to fill in boxes I didn't have filled because I felt like that would make me a better professional. It's like if I didn't kn..."

Optimal career growth happens by taking roles that are 'adjacent' to your current skills but provide significant new challenges.

"It's to constantly be choosing things that are either outside that, not totally outside the lines. Don't jump out of a plane if you've never parachuted before. Obviously you want them to be in some wa..."

Growth teams succeed by navigating cross-functional boundaries and operationalizing experiments that sit between product, marketing, and sales.

"Growth organizations are in this interesting space, they're in between everybody else. They're in everybody else's sandpit in a little bit, in a little way, and they're kind of at the edge of everybod..."

The most resilient B2B businesses combine product-led growth and enterprise sales into a single, reinforcing flywheel.

"For really sophisticated companies, the people who really nail this, it's about making both motions work together. If you can get a PLG motion work to feed your sales team and a sales team motion work..."

The core value of a product manager is the ability to make timely, high-quality decisions that balance speed and information.

"We get paid in product management to make decisions, good decisions, paid to make good decisions that will deliver business benefit. And a decision with too little data is fatal. A decision that takes..."

Data should be used to validate or invalidate intuition rather than as a definitive roadmap for decision-making.

"Data is more like a compass than a GPS. If you look at data as a way of giving you the answer, you're always wrong. You're always wrong or you're slow. Wrong or slow or sometimes both, because mostly..."

Effective decision-making requires finding the 'sweet spot' of data—enough to be informed but not so much that you lose momentum.

"If you're making a decision with less than 30% of the available data, you're making a big mistake. If you're making a decision only after you have 70%... you have waited far too long."

Great product managers differentiate themselves by consistently grounding their work in external market and competitor realities rather than internal politics.

"In everything always talk from the customer's perspective, from the market's perspective, from the competitor's perspective, the very small number of PMs do that."

LLMs can be used to stress-test your strategy against competitor positioning to find gaps or areas where they might have a better fit.

"You can copy and paste one of your competitor's positioning documents into ChatGPT and say, 'Is this a better fit for what they have said than my thing?'"

True competitive advantage in SaaS comes from embedded business rules and workflows that create deep lock-in, which is harder to clone than simple UI or data models.

"It's the years and years and years of evolution of the underlying workflows of the product to support the customers, but also the customers evolving those workflows to make them work the way they do...."

Effective user research requires 'right-sizing' the number of interviews to reach the point of diminishing returns without wasting resources.

"Once you interview between 7 and 14 people, you stop learning new things. Less than 7, you don't learn enough, more than 14, you start learning anything new. And so if you interviewed two people, you..."

Leading questions invalidate user research by creating confirmation bias rather than genuine discovery.

"Then they go into these conversations asking leading questions, which really are designed to get the customer to say what they already want to be true, which is so they haven't done enough research or..."

Top PMs create systems to continuously immerse themselves in diverse streams of customer and market feedback.

"He used to call this concept a Feedback River, and he basically said that really smart product managers are constantly swimming at a Feedback River. They set out to surround themselves by Feedback Riv..."

Semantic analysis using LLMs allows for more accurate clustering and prioritization of high-volume customer feedback than keyword matching.

"We use LLMs to take in those asks to summarize what they're about, to find other asks that are like that one, really in a compelling way, a real way, like a semantic way, not other words, exactly the..."