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Bringing AI in at Headway

Surface ranking failures before another week of patient search drop-off

You’re the product manager. Your team is in the room. Printed Oct 14, 2026.

Ranking evidence moves slowly while patient search failures demand a clear next question.

Faster synthesis protects the time to act, while source-level review protects the judgment behind a ranking bet.

Who you’d be doing this for

“I opened so many profiles, then gave up because none of them felt like a real fit.”

Hugo Bernard · Therapy-Seeking Patient

An insured patient using search to find an in-network therapist with availability that fits their needs.

What is at stake

Ranking reviews take four days to turn conflicting feedback and metrics into a usable brief. You must weigh faster evidence synthesis against the review needed before a PM acts on it.

Why it isn’t already fixed

Every obvious fix costs something else. That’s the part you’d have to decide.

  • faster evidence synthesis vs. PM problem framing
  • patient feedback volume vs. source-level verification
  • ranking learning speed vs. clinical escalation safeguards
  • drafted narratives vs. contradictory experiment signals

Why Headway

The matching system determines whether insured patients find an in-network clinician and remain in outpatient care.

Written with these in mind

embedded AI systems builderproduct-minded forward deployed engineerevaluation-focused AI practitioner

Not your kind of problem? 34 more at Headway, or browse every organization.

This is the setup. The work is inside.

Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.