Meetings are the Dark Matter of Enterprise Cybernetics

We are going through is a transition period - from human reasoning to machine reasoning; given the previous revolution from human computing to artificial computing, I guess you could just say that the broad ~100 year arc is from human intelligence to artificial intelligence and just call it an AI revolution [1].

As such, I've been thinking a lot about how to use AI in the context of an existing business to streamline internal operations.

And while pieces of the business feel tractable based on applying AI to existing systems of record or operational processes, automating large swaths of a business feels too hard. Too much reasoning is illegible to machines - because it happens during meetings.

Meetings are the dark matter of the enterprise - the vast majority of "context" about what's happening at a business is transmitted verbally, and needs to be represented digitally. So a key part of transforming between the analog business to the digital business is about making meetings legible to machines.

That's why I think Granola.ai is going to be the Killer App™ for the next generation of enterprise operating systems - I'm only testing it out right now in a personal capacity (it's currently quite limited from a security perspective and not enterprise-ready), but it's the first application I've used that really feels like a step-change for personal productivity. Chat apps are nice for search, and I think they will continue to be useful. But they still feel like work - the experience for most LLM chat apps is still relatively similar to a better search engine (you swivel chair to it, do stuff, then swivel back). Granola is the first app I've used that's non-zero sum with my time; it inhabits the same time as I do, and makes that time more productive. I can't explain it exactly, but using Granola feels like - oh yeah, this is going to be ubiquitous in 5 years. Maybe it doesn't win the category (will be a battle), but this category is going to be the first non-chat Category of LLM-powered apps.

The problem is that in its current form, it's just a tool. It's going to be picked up ubiquitously and let people do better meetings - what it's NOT going to do is automate away meetings or massively accelerate operational productivity.

That's where the Ontology comes in - because right now, Granola is just a generic application. The opportunity is to use the Ontology to turn it into a Platform. Today, Granola has a basic templating system with generic out-of-the-box templates for specific meeting types. By applying a decision-centric data model to it, you could map meeting types to object types, and then include functions and actions in the UI where it currently provides some generic out-of-the-box actions (send email, list action items).

So now you've created a virtuous cycle - you use Granola to capture meetings, those meetings become data about the actual reasoning and decision-making in the enterprise, and then the meetings can be automated, orchestrated, agentified...ontologized.

Today, there's a feature in Granola that creates "action items" - imagine if each of these action items corresponded with an Ontology Action Type - with the right ontology, the Action Items from a partnership kickoff call could all be invokable Ontology Actions - one to create a Jira ticket for reviewing API docs, one for initiating a Legal ticket to get a partnership set up, one for scheduling a kickoff meeting, and one that automagically created a Slack channel. And they don't need to be actions yet - just having the Meeting <> Action Item mapping for all meetings of a given type lets you begin mining the plaintext action items to create semantic action types (and an Action Type <> Prompt Hint mapping so that future Action Items could be translated into invokable Ontology Actions via semantic search).

At this point, the UI would transform the text into a clickable bullet automatically orchestrating an entire system of action which could be kept in sync as more meetings occur and actions move through a Markov chain of semi-formalized state changes - "okay, you decided to transfer Phil to the Mobile team - let's kick off the process of talking to Phil, confirming the transfer, and then registering this."

To automate decisions, they need to be formalized and given that most decisions happen in meetings, this means that automating decision-making will require making the meeting context accessible to machines. Over time, this will enable us to progressively titrate decision-making authority from the human to the machine as humans shift from being decision-makers themselves to being the makers of decision-making machines.

[1] It's only tangentially related, but I do think that this Eric Schmidt talk was an interesting read about the steam to electricity transformation, which might be a good historical analogue to consider.