Pre-engagement interviews
We interview your people and construct a crisis scenario from your actual organizational context — the real silos, hand-offs and pressure points.
Team LFS is a live, AI-driven simulation that drops your leadership team into a shared crisis built from your real organization. People play themselves. Every decision — and every silence — is captured and turned into coaching intelligence you can act on. Not a personality quiz. Not self-reported feedback. What your team actually does under pressure.
Surveys and 360s capture intentions and impressions. Team LFS captures behavior under ambiguity — the decisions, hand-offs and silences that actually determine whether a team holds together when it matters.
No role-play, no personas. Each person faces the crisis as themselves, so what surfaces is how they actually lead.
The scenario is constructed from pre-engagement interviews, so the pressure points are your team’s actual pressure points — not a generic case study.
Every action and inaction is captured and timestamped — who was contacted, who was left in the dark, what was said and what never got said.
It maps how individual patterns interact to produce collective breakdown — hard to argue with, because it’s about the team, together.
One facilitator, one retreat, one connected experience — designed and run end to end.
We interview your people and construct a crisis scenario from your actual organizational context — the real silos, hand-offs and pressure points.
Each participant works from their own interface, receiving events across message, email, live voice call and presence. A facilitator drives the run from a live console, firing scenario beats and watching every seat in real time. Each role faces the consequences of the others’ choices — no two people experience the same simulation.
Immediately after, the captured session powers a three-part debrief — the room view, the team view, and each person’s individual game-film — where every claim is traceable to what actually happened.

The value is realized in the debrief — a single connected experience built over one session’s captured behavior.
Every participant leaves with evidence-based individual coaching, the team leaves with a shared picture of how it really operates under pressure, and the profile persists — so the same people can be challenged again over time and you can track the trajectory.

A real-time, multi-participant AI simulation that drops a leadership team into a shared crisis built from their actual organizational context. Participants play themselves across message, email, live voice and presence; their choices — and their silences — are captured and turned into diagnostically valid coaching intelligence, not self-reported feedback.
It measures behavior under ambiguity, not self-assessment or peer rating. The scenario is built from your own interview data, participants don’t know the specific hypothesis being tested, and the team report maps how individual patterns interact to produce collective breakdown — undeniable because it’s about the team, together.
Both. Each role in the scenario is a seat; a human is assigned to a seat, and any seat with no human is played by AI. The same engine runs a full seven-person team, a single executive against six AI colleagues, or anything in between — set at session setup.
Individual coaching reports with behavioral evidence from the actual session, a team dynamics report mapping coordination and failure patterns, the interactive debrief suite, 30-day commitments per participant, and a persistent behavioral profile that compounds across repeat engagements.
Retreat-based with one facilitator. The core scenario runs 90–120 minutes with the debrief immediately after. Pre-engagement interviews are required to build the scenario. Extended multi-week and season-length formats are available, along with premium modules such as live actors and physical artifacts.
Team LFS is delivered by application and briefing. Tell us about your leadership team and the challenge you're facing, and we'll walk you through a fit.