Insights, updates, and deep dives into AI-native product development and how we’re building the future of PM tools.
The generalist PM is becoming the hardest role to hire for — because the job is splitting. The specialize-vs-AI-generalist fork, the four flavors of "AI PM," and the one career question that now matters most.
Practical guides, product frameworks, and Specky updates — sent when it’s worth your time.
Customers don't want your product — they hire it to get a job done, and fire it when something does the job better. Here's how Jobs to Be Done reframes discovery, prioritization, and messaging.
Most teams do discovery in bursts, then build on stale assumptions for months. Continuous discovery — small, weekly customer touchpoints — keeps you close to reality. Here's how to make the habit stick without it eating your roadmap.
Most teams pick a North Star Metric that's easy to move — and easy metrics don't predict survival. Here's how to choose one that measures value, break it into inputs you control, and connect it to evidence you can trust.
The feature roadmap optimises for delivery, not impact. Here's how to switch to an outcome-based roadmap — Now-Next-Later, outcomes over outputs, and a roadmap that works as a decision system instead of a list of dated promises.
Shipping AI features without evals is how 95% of pilots fail. Here is how product managers define "good" for probabilistic features — and ship with evidence instead of hope.
A technical spec is a thinking tool, not a formality. Here is how to write one that engineers actually read, focused on the risky decisions instead of completeness.
Signups are vanity; activation is survival. Find your aha moment, run the activation loop, and connect signals to decisions so the work compounds.
A product strategy that does not fit on one page is not guiding decisions. The strategy canvas distills diagnosis, bet, and tradeoffs into something a team can actually remember.