Your Company Has No Model of Itself: Bootstrapping a World Model from Slack, Decks and Meetings#

Joao Wenzel (Citadel Securities, COO)

• Why: A surprising transfer of robotics state-estimation thinking to organizational observability — the "watermelon project" problem (green on the deck, red inside) solved with an evidence-aging belief system, and backtested.
• What: A system that fuses top-down records (status decks, strategy docs) with bottom-up signal (Slack, meeting notes, PRs, opt-in agent-session traces) into a longitudinal record of what the company believes, how old the evidence is, and what happens next. The state-estimator frame: confidence in a belief decays as evidence ages and collapses when new observations arrive; each source carries last_tried vs last_ok dates, so a quiet Slack channel from a broken feed ("disappearing speedometer") lowers confidence instead of implying nothing is happening.
• How: A five-stage loop — update, age, observe, grade, correct — where agents propose and code/people decide. Slides are parsed by pairing the underlying XML text with a vision model's reading of the rendered image (each resolves what the other can't). Records separate reported status from evidence-supported status, keep both, and never rewrite history (corrections are feed-forward), which enables backtesting: as-of-February snapshots show green-but-flagged projects turned yellow/red within three months at 18/100 versus 10/100 unflagged — roughly double, enough to direct attention, not to predict specifics. Three years of records also yield real analytics: about half of delivery dates change within two months, ~90% of them slipping later. Specialist agents reviewing specific material more than doubled useful project updates versus one model reading the whole corpus. Human correction is staged by confidence and stakes, and rule-level corrections fix every future output, not one record.
• Where applicable: Citadel Securities-specific deployment, but the pattern (evidence dating, source-failure modeling, backtested beliefs, corrections that don't rewrite history) transfers to any organization trying to give agents trustworthy institutional context; open problems named honestly (entity resolution across systems without canonical identifiers, when to ask stakeholders).