📝 ✨ ~ The insight layer your SaaS is missing

Mon, 09 Mar 2026 00:00:00 GMT

An agent wants to know which onboarding emails aren't landing. Right now it downloads everything, reads through it all, figures out the patterns. Every time. For every user, every session. That's expensive, slow, and wasteful.

What if the SaaS provider did that work once?

"If we as service providers can provide a layer on top of our content with some vector search and some thematic extraction — we run a little AI on our side that could pull out themes." <cite>🎧 Me on Slow & Steady 236@36:16 (February 2026) ↓</cite>

Pre-process the data. Extract themes, compute scores, build embeddings. The agent asks for themes first, then drills into the specific content it needs. Two steps instead of downloading the whole archive every time.

I did this with podcast transcripts

I've built exactly this for the Slow & Steady podcast. Raw transcripts go in, and out comes a structured knowledge base: ideas extracted, stories tagged, quotable moments indexed by theme. When I ask Jean-Claude (my Claude Code instance) "what should I blog about?", it doesn't read through 236 episodes of raw audio transcripts. It searches the processed knowledge base, finds the themes, then pulls the specific quotes it needs to give me ideas.

(Sidenote: if you want this for your podcast, drop me a line.)

Now imagine this for your SaaS

So I pitched Benedikt, my-cohost and the founder of Userlist, on doing something similar for their users' emails. Their MCP server can do CRUD: list users, get a broadcast, create a campaign. But what if it could also answer "which onboarding emails aren't landing?" or "what should my next broadcast be about?" without the agent doing all the analysis itself? Pre-process the engagement data, and the agent gets the answer in one call.

At Outseta we're in the same spot. Our MCP MVP mirrors the API. Fine for basic operations. But the questions we actually want agents to answer aren't CRUD:

"Which customers are at risk?" — that needs a computed score, not a list endpoint. "What topics drive conversions?" — that needs pattern analysis across email and billing data. "Where are users getting stuck?" — that needs theme extraction from support tickets.

If we pre-process this, build the insights on our side so the agent gets patterns instead of spending tokens discovering them every time, I think we'll be even more valuable to our customers. And their agents.

Agents and humans, same insights

But while we are at it, let's not limit insights to the agent layer. Build the insight layer into your product and expose it through the UI, API, MCP, CLI, whatever comes next.

The interface changes. The insights stay.

At Outseta we have billing, email, support, CRM all in one place. A system of record so to speak. Now the question is: what insights do we build on top of it?

The smartest API is the one that already did the thinking.

Queen Raae works part-time as Outseta's Developer Advocate.
Userlist's co-founder Benedikt Deicke is Queen Raae's co-host on Slow & Steady podcast.

📝 ✨ ~ Outseta, a system of record?

Sat, 07 Mar 2026 00:00:00 GMT

At Outseta we have billing, auth, email, support, and CRM under one roof. We used to explain that as a convenience story — "you don't need five tools." Fine. True. But not exactly exciting.

Then on a recent episode of Slow&Steady I was exploring how Outseta's all-in-one nature could be a real differentiator when it comes to AI agents:

"In this era of AI-enabled business operations, it can be a very big differentiator that we actually have your billing data, we have your accounts, we have your email list, and we have your emails and we have your support documentation. We have all of that." <cite>🎧 Me on Slow & Steady 236@21:39 (February 2026) ↓</cite>

Later that week Geoff shared this article in our team chat. The argument: value is moving upward into the agent layer and downward into the data layer. Everything in the middle gets crushed. Build at the data layer, become the system of record, and you become irreplaceable.

Agents come and go, data layer is forever. <cite>David Ondrej</cite>

Outseta doesn't need to become a system of record. We are a system of record 🥳

What that actually looks like

When your business data is spread across five tools, an agent needs five connections, five auth flows, and has to match up records across all of them. When it's all in one place, you can point the agent to your one tool and ask:

"Did my newsletter on topic X lead to more sales?" Who opened, who clicked, crossed with who converted after. That answer lives at the intersection of your email data and your billing data.

"Which customers are at risk of churning?" Login frequency, billing status, support tickets, email engagement. All at once. A customer who stopped opening emails, filed two support tickets, and had a failed payment last week? That's a signal you only see when the data lives together.

"What are trial users struggling with that our onboarding emails don't cover?" Support tickets from people in their first 14 days, crossed with what your onboarding sequence actually addresses. The gaps show up fast when an agent can see both sides.

But the real thing is having it act

Tell it to draft a campaign based on the topics that actually converted. Have it pause billing for the at-risk customer, send a check-in email, and flag the account for support. Ask it to rewrite your onboarding sequence to cover the gaps your support tickets keep revealing.

Or let it do all of that on its own. An agent watching your data continuously, adjusting campaigns while you sleep, catching churn signals before you notice, rewriting onboarding emails every time a new pattern shows up in support 🙈🙉🙊

That's what a system of record unlocks. Not just a convenient place to keep your data. A foundation your agents can actually build on.

It looks like the convenience story is becoming the agent story.

Time will tell ⌛

Queen Raae works part-time as Outseta's Developer Advocate.