Platform of Platforms
As always, these posts are more of a brain dump of “what I’m thinking” about…And lately I have been thinking a lot about “legacy SaaS",” systems of record, etc. I wanted to write another post today in a similar vein.
When I think about how people and companies interact with software today (and for this post when I say software I’m talking about legacy SaaS systems of record) the pattern is generally pretty simple. The system of record is a single, organized place where a human goes to look something up, understand the state of the world, and then take some sort of action based on the information they gathered from the system of record.
Like opening Salesforce to check pipeline before updating a forecast, or pulling up NetSuite to reconcile numbers before approving a close. And more often than not, there are workflows that can be defined and automated around these systems of record - quote-to-cash, opportunity management, rev ops stuff, etc.
One observation I’ve had is that generally the workflows around current systems of record have two properties (not only two, but two stand out to me):
The workflows tend to be a bit more “rigid.” They are very deterministic, and have to follow a certain flow
The workflows can be completed end to end in that one system
As the SaaS market matured, if you wanted to create workflows that spanned multiple SaaS systems, you worked with an IPaaS provider (or other type in integration platform) like a Workato, Mulesoft, Zapier, etc. These were essentially API connections between SaaS applications that enabled bi-directional information sharing (ie read/write). You generally had to define the flow. Define the edge cases, error handling, etc. So there was a level of “rigidity” to them.
When I look at AI agents today - one of the things they do very well is work across systems. They grab information from System A and B, use it to update System C, then create some output or take some action. They’re working across systems and systems of record. That’s usually the work humans did!
Humans were the connective tissue between systems of record. They knew where to go, what information to grab, and then what to do with it (and at the same time when to do it). All of that either context or intuitional logic lived in people’s head or some company wiki page. But now, we have agents to do that work.
The key insight for me - agents are working across systems of record. When we ask the question “why can or can’t legacy systems of record just add AI” one important part of the answer is asking the question “well can System of Record A really build a product that works in / on top of other systems?” The existing systems of record work great in their own domain. They have control over their own domain. But as soon as you leave that domain, either their product stops or it doesn’t have access. Agents however are a “layer” that sits on top.
I think this could be a limitation that makes it difficult for legacy SaaS systems of record to build successful AI experiences. Not to say they can’t - some certainly will. But it will be hard. It will require building experiences that span beyond their typical domain expertise. Some structurally may not even be able to.
The user for SaaS was humans - Adding context and providing connective tissue between systems. The users of software in the future will be AI Agents. They will be creating value, taking actions, and defining workflows across systems. The question for legacy SaaS vendors - will they be reduced to a simple store of information for Agents or will they capture the new layer on top? (I wrote about this the other week in my “front door” post, but this is partially what Satya means when he says SaaS will be reduced to a dumb CRUD database). Will the SaaS vendors be reduced as a new abstraction layer enters on top of them? Time will tell!
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