The First Time Business Intelligence Felt Intelligent

Business Intelligence never delivered intelligence - it delivered retrospection with charts. Yesterday with frosting. It was always aspirational.

But I witnessed something today that I think qualifies. It's like when someone goes Bigfoot searching as a hobby - they never actually EXPECT to see it, it becomes about the camping, hiking, nature. An aspiration dominated by the material artifacts that surround it, as opposed to the thing itself. Yet if they unzipped their tent one morning and Sasquatch was standing there they'd likely be speechless.

For months now I've been building my RVBBIT postgreSQL extension system (6+ years if you include all the direct experiments and ancestors) and I have it running at a client's site in prod for a month or so. A recent addition gave RVBBIT an "assistant substrate" - governed access to the company’s data, definitions, documents, dashboards, operational tools, and the history of the work it has performed. The same assistant appears through multiple interfaces, but its memory and understanding accumulate in one place.This assistant, "Calliope", became a sleeper hit for a handful of people. People can get query results, build metrics, cubes, entire HTML dashboards and publish them to RVBBIT.

People who would have never opened Tableau or used SQL were now making beautiful "just in time" dashboards as needed. No matter if they were in Claude Cowork, Google Chat, or using Data Rabbit's "Data Desktop" interface. Same Calliope, same brain, same memories - accumulating. Awash with organizational breadcrumbs - and with enough agency to actually be useful.Exciting. Adoption is always good. People getting stuff done because of it is even better.At this point Callie had been chatting with people and building things for about 2-3 weeks, not everyone used it - but some went deep, others were just dipping their toes in. This morning I was debugging another issue and decided to do an experiment in the background. I opened Google Chat, brought her up and sent:

"Use your memory skill and go through all the things that people have been asking you to do - queries, dashboards, etc - and based on all of that history, lets come up with some things that you think would be good to build for the business - basically synthesizing the current workload that you've been seeing. Take your time, there is likely lots of data to look at."

(note: all within the client’s governed environment, using authorized business interactions and audit-able artifacts - not by silently scraping private employee conversations or anything like that)Honestly, I didn't think much of it. Figured I would get some dashboard ideas back, maybe a callback to some pressing issue. An echo at best. I just wanted to be reassured that recall was working. She though for about 10 minutes - and when she responded, it was an entire project plan introduced with this:

What people are repeatedly trying to accomplish:

The requests are not really “show me another chart.” They repeatedly ask:

• What happened this week?
• Where should budget move?
• Which locations need attention?
• Are ads actually on or off right now?
• Are leads converting into enrollments?
• Which channel produced a specific enrollment?
• Why do Google, Salesforce, and the warehouse disagree?
• Are enrollment dashboards current and correctly scoped?
• Can the weekly report be completed without manually reconciling everything?
• Can campaign targeting, budgets, copy, and creative be recommended together?
• Can someone smoke-test the dashboard when the numbers look wrong?

The dashboard inventory confirms the fragmentation. Five frequently touched products—[REDACTED dashboard names] accumulated 77 published versions. That is a maintenance signal, not just healthy iteration.

My strongest conclusion

We should not build another isolated dashboard first. We should build a governed operating system around the [REDACTED] decision.

I read it all and just kind of sat there bewildered. "Oh".

Bigfoot was in the tent.

This was not "intelligence" because the answer was verbose, polished, or fancy. It was intelligence because no one (including me) had explicitly supplied the conclusion. It emerged from the accumulated record of what people repeatedly tried to accomplish, what they built, what broke, what they corrected, and what they cared enough to revisit (and likely also what threads they abandoned).You see, many of us have been doing this a long time - and will tell you that if you have meetings talking about a new project idea, bring everyone together and start trying to hash out some semblance of functional requirements skeleton - you will get a lot of noise (to put it kindly).

Requirements meetings capture what people are prepared to say in a room. A meeting group or a project interview is a sociological experiment.In a "Recursive Knowledge" style system - where it takes things in, stores them, enriches them, and they sends them back around again as needed little is wasted. Like a turbo charger spinning up on the exhaust to get a boost for the next intake, but just enough. Not too much to over-boost or overfit. Evidence, receipts, conversations, queries extracted from dashboards, the business SOPs, tickets, meeting transcripts, etc.

Unlike in meetings, in private, no one is going to "perform" for a "chatbot".

They just want something. And if its wrong they want it fixed. And often they even point to where things are. Delivering handmade breadcrumbs to the curated set of derived ones. Bit by bit they steer and nudge and eventually get what they want. What does the agent get? Institutional knowledge from the connection of edges, positive / negative prompts, and the sentiment about what actually matters.

Sample by sample. Implied, explicit, & derived.

That distilled knowledge down to it's parts / objectives / SQL evidence can often surface what people need in ways that maybe they didn't even know to ask for.The "intelligence" emerged from the exhaust of useful work. It's usable boost pressure. Not from the aether, someones "great prompt hack", or a process consultant who's pants don't quite fit.This only works when all the exhaust lands in one place. Managed. Cultivated. Every conversation, query, dashboard version, and correction has to be able to meet the others - you can't weld silos into a commons - and a leaky exhaust lacks back pressure.Steve Jobs famously said that "customers don't know what they want until you show it to them", and that's half true - because if you're not Steve Jobs you need to do a bit more legwork. What people tell you that they want is often anchored by what they think is possible and further chained to the ground by what they've done and seen.

They present what they think are solutions, not problems.

What you really want is the problems, the data, and objective view - and the ability to reason about it from first principals and not just adjacency.This was not proof that an agent could run the business, and it was not an oracle discovering objective truth. But it was the first time I had seen a "BI system" infer a coherent operating need from the accumulated evidence of actual work.

It wasn't a gauge going too far left or a KPI slowly curdling.

We build systems. We think in systems. We imagine tangible pieces and how they fit together, where they break, areas where they rub together too much, abstract "material stress". That's the deliverable. That's the product. Shape rotators gonna shape rotate.Sometimes you discover that the REAL product is the side-effects."Calliope".
My first squatch sighting. Nearly dropped my camping thermos.