ProductSense Automates the Evidence, Not the DecisionProductSense Automates the Evidence, Not the DecisionProductSense Automates the Evidence, Not the DecisionProductSense Automates the Evidence, Not the Decision

The incumbent product tools started adding AI on top of what they already had. Arto Tolonen spent a decade in product at Smartly.io — ending as CPO while the company scaled past $100M ARR — and saw what that looked like from the inside. ProductSense is his bet that building from the ground up, with AI at the core, produces a different product entirely: a knowledge graph that ingests sales and support transcripts, customer discussions, market signals and product analytics, then structures all of it for product decision-making.

The hard line he drew is that the system gathers the evidence, the human still makes the call. In B2B, product decisions are business decisions, and he does not think you should hand those to an AI anytime soon. Every insight traces back to the raw transcript so teams can audit the insight layer — and product marketing can borrow the customer's exact words.

What we cover

• AI as the centerpiece, not a layer. Building from the ground up with AI at the core is a different product entirely from bolting it onto what already exists.
• A knowledge graph of customer reality. ProductSense ingests sales and support transcripts, customer discussions, market signals and product analytics, then structures all of it for product decision-making.
• Nobody commits past three weeks. Mid-sized companies with real customer bases now tell him they will not commit to anything further out than three weeks, because agentic engineering made building that fast.
• The two kinds of product leader. The hands-on builders are having the time of their lives. Arto's hunch is that there will be fewer roles for the ones who went into product mainly to become managers.
• Evidence one click from the source. Every insight traces back to the raw transcript, so teams can audit the insight layer, and product marketing can borrow the customer's exact words.
• When your own pitch becomes the insight. Their first analysis surfaced their own sales pitch as customer demand, which is why every prompt is now framed for product decisions instead of sales topics.
• Scored signals, not vote counts. Conversations get rated on whether the problem, the trigger and the frequency were actually understood, plus a confidence score and a read on where you are blind.
• Why he refuses voting boards. Votes only tell you who to talk to. An open submission board just floats the thing you should not build to the top of the list.
• The decision stays human. In B2B, product decisions are business decisions, and Arto does not think you should hand those to an AI anytime soon.
• Back to UIs. MCP adoption moved fast among technical product builders, but he expects interfaces to matter again, because natural language is a poor way to configure anything.