Re:Show HN: An "Evidence Loop" for steering the agents what ...
by jkalichman on Tuesday August 11, 2026 @10:50AM
(#49259334)
Thanks so much for stopping here! This is a really great question.
Several factors contribute to this:
1/ We pin down the exact behaviour first: who does what, where, by when. That precise behaviour is the target everything serves.
2/ We interview doers and non-doers. That’s how we handle conflicting feedback: we don’t average it away, the gap between the two groups is the insight - what doers have that non-doers lack is exactly what to fix. We can also triangulate the behaviour with user's action they do in the product - for that we experiment with product analytics integrations, such as amplitude & posthog for now.
3/ We diagnose the real barrier by applying behavioral science framework - COM-B. Every interview is coded into six buckets: capability, opportunity, motivation.
4/ The barrier tells us what to build (e.g. what type of intervention works the best, based on behavioral science principles). Different barriers need different fixes: let's say, if people don’t know how, you teach them; if it’s too inconvenient, you remove friction. Behavioural science already maps each barrier to the type of solution that works for it, so the fix isn’t a guess. The barrier itself points to a specific, concrete thing to build.
5/ Finally, every recommendation traces back to real customer voice and interviews. The line from “customer said X” to “so we’re building Y” is fully visible, end to end.
Several factors contribute to this:
1/ We pin down the exact behaviour first: who does what, where, by when. That precise behaviour is the target everything serves.
2/ We interview doers and non-doers. That’s how we handle conflicting feedback: we don’t average it away, the gap between the two groups is the insight - what doers have that non-doers lack is exactly what to fix. We can also triangulate the behaviour with user's action they do in the product - for that we experiment with product analytics integrations, such as amplitude & posthog for now.
3/ We diagnose the real barrier by applying behavioral science framework - COM-B. Every interview is coded into six buckets: capability, opportunity, motivation.
4/ The barrier tells us what to build (e.g. what type of intervention works the best, based on behavioral science principles). Different barriers need different fixes: let's say, if people don’t know how, you teach them; if it’s too inconvenient, you remove friction. Behavioural science already maps each barrier to the type of solution that works for it, so the fix isn’t a guess. The barrier itself points to a specific, concrete thing to build.
5/ Finally, every recommendation traces back to real customer voice and interviews. The line from “customer said X” to “so we’re building Y” is fully visible, end to end.
We have a blog post on it here: https://www.dipio.ai/blog/behaviour-change-design
Plus, there is a great source for all-behavioral science, including COM-B model https://thedecisionlab.com/reference-guide/organizational-be...