Agenda conflicts are the classic event-management failure: they are trivially detectable, invisible to the person building the schedule one form at a time, and mortifying when an attendee finds them first. A programme manager adding the fourteenth session has no way of remembering that the keynote speaker is already on stage in Hall B at 14:00.
EventfullyManaged treats this as a computation the platform owes you, not a checklist item. When you open a session form, the platform reads every session on that event with its time window and room, plus every speaker-to-session assignment, and runs the overlap scan itself: two sessions sharing a non-empty room whose time windows intersect are a venue clash; one speaker assigned to two intersecting sessions is a speaker clash. Each clash comes back with both session titles and a readable message — "Opening Keynote and Platform Deep Dive overlap in the same venue" — rather than a bare error code.
On the session form the clashes are filtered to the one you are editing, so you see the conflicts you just created rather than a wall of every problem on the event. When you are adding a new session, the full list is shown, because that context is what tells you where the free slots are. The whole thing is read-only: nothing is written, nothing is auto-moved, and the scan runs against sessions already scoped to your workspace, so an agenda in another workspace can never leak into your results.
This is the honest shape of a lot of useful event intelligence — it is arithmetic over a connected data model, not a model call, and it is better for being deterministic: it never misses a clash and never invents one. It also becomes the substrate for the layer above it. Once the platform can reason about the whole schedule, the next step is proposing the fix — move this talk to the 15:30 slot in Hall C, or split the oversubscribed track — with the organizer approving each change.
That resolution and optimisation layer is on the roadmap, not in the product. Conflict detection is live; suggested resolutions, track balancing, and popularity-aware scheduling are still being built.
Illustrative scenario. Conflict detection as described is implemented; the suggestion layer above it is roadmap.
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