Commitment Lab: AI Practice Room for Cross-Team Conflicts
A developer built Commitment Lab for a hackathon, using AI agents to simulate stakeholder conflicts between sales, engineering, and customers.

Stock photo for illustration only, not from the actual event
- Commitment Lab simulates ambiguous commitments that fall between team boundaries.
- It uses two AI agents acting as a stakeholder and a coach in a shared chat room.
- The system helps distinguish between internal targets and actual customer agreements.
- The AI coach reviews transcripts for debriefs, though human oversight remains essential.
When a customer expects an integration on Friday and sales wants an answer, engineering may state the work cannot ship by then. The hard part is often recognizing that multiple distinct statements are being treated as a single promise, including customer expectations, engineering targets, and unmade agreements.
To navigate this challenge, the creator built Commitment Lab for the Flip the Switch hackathon as a personal practice space. Learners work through a fictional stakeholder conflict alongside an engineering mentor and two AI agents in a shared Switch room, aiming to clarify what has been agreed upon versus what remains open.
Bridging the gap between commercial teams and engineering is a persistent organizational challenge. Simulating these negotiations with AI allows professionals to practice critical cross-functional communication safely without risking real client relationships.
The exercise centers on a fictional company named Acme and a Friday launch expectation, featuring four distinct roles within the lab. During the recorded session, a single operator simulated both the learner and the mentor, while the stakeholder and coach operated as Codex-backed agents inside a Switch and Mattermost environment.

Stock photo for illustration only, not from the actual event
During the scenario, the stakeholder inquired about the Friday launch commitment. The simulated learner asked engineering for feasibility, and the mentor responded that neither a CSV export nor the full integration could ship before May 22. Consequently, the stakeholder acknowledged that sales could not confirm the earlier launch date.
This distinction forms the core learning objective: an internal target is not a customer-approved commitment, and a promise to ask a question is not the customer's answer. The repository includes an importable Switch template, editable agent instructions, and scenario notes for other teams to inspect and use.
Source: Dev.to
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