Ayan Barua

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@ayanb

Co-Founder @ ampersand.ai - previously founded Siftery and led engineering at G2.

Relentlessly positive sum.

San Francisco, CA ampersand.ai Joined September 2008

200 Following 772 Followers 882 Posts

Latest posts 5

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Ayan Barua @ayanb Oct 6

Your AI is vaporware without deep integrations with your customers’ systems of record.

Introducing @WithAmpersand: integration infrastructure for enterprise agents.

We power 11x, Orb, and Square's ability to take agentic action in systems of record like Salesforce, SAP, NetSuite, and Workday.

Ask anyone serious about building AI and they’ll tell you:

- The SaaSpocalypse didn’t happen. The world depends on CRMs, ERPs, HRISs, and ITSMs.
- Your customers customized their deployments beyond recognition.
- Systems of record companies are basically monopolies. They never had to make their APIs and MCPs user-friendly.
- Docs don't explain half the weird edge cases you'll hit.
- One bad write can blow up your pilot or renewal.
- Once you finally get it working, someone changes a field and it breaks again.

The world's data lives in structured databases. AI needs a translation layer to work with it.

So, for your AI to truly transform the way enterprises work, you'll need deep integrations built for:
- scoped permissions
- bi-directional actions
- real-time speed for agents
- custom objects, fields, and workflows for each of your customers

We built Ampersand to power the future of software.

AI didn't trivialize writing integrations. It made them the critical path.

I believe that deeply, so I didn't make a launch video about Ampersand.

Instead, it's the best builders I know explaining just how big of a challenge this is.

5:00

Ayan Barua @ayanb 6d

Every customer action with your agent will move at the speed of agents.

If your MCP, agent, whatever it is, consumes from their systems-of-record, you'll be updating their systems-of-record at the speed of agents. 1000x-10000x the speed of humans.

Can your infra keep up with that? Will your customers trust you?

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Hiten Shah Verified account @hnshah Oct 21

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Ayan Barua @ayanb 6d

System of Records like NetSuite are terrified of startups building Systems of Action.

0:46

Ayan Barua @ayanb Nov 1

This is exactly why Salesforce is still around. Its UI is so bad, but people keep using it. Agents need access to Salesforce too, and they don't care about UI.

Salesforce's years of not investing in design paid off (LOL)!

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Jason ✨👾SaaStr.Ai✨ Lemkin Verified account @jasonlk Oct 16

"Running Salesforce agentically inside of Claudeforce, Replit or Lovable is 10x-100x better than logging into the 'native' Salesforce.

I'm not sure why anyone would ever log into Salesforce again in fact once Claudeforce is GA."

We demo them all to you LIVE with our real data on this week's The Agents!

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Ayan Barua @ayanb Oct 31

Vertical AI and niches 📈

We see this all the time, supporting agent integrations for a long tail of CRMs in every industry. Those CRMs are getting much stronger, they're not being eaten by the models.

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Aaron Levie Verified account @levie Oct 20

The big bitter lesson question in the applied AI layer is that as models get better and better, what is the best way to diffuse that intelligence into an enterprise.

Ironically, I’d argue that as models are getting more capable, and can handle longer running tasks and better tool use, the ability to differentiate on a domain by domain basis goes up instead of down.

When models were quite limited in what they could do, ironically all you could be literally was a “wrapper” because you were effectively delivering tokens back to the user with a custom prompt or some limited RAG.

But in a world of agents using tools, tasks that run on for hours or days, workflows that kick off agents, agent swarms that need to be coordinated against a goal, data sources that are domain specific, model routing that requires domain-specific routing, implementation that requires real change management of the workflow instead of “just type into this chat box”, it’s very very possible that specialization of these systems goes up more.

Obviously this doesn’t apply to everything - the closer you are to the labs core use-cases the tougher this play gets, but I’d argue we’re going to see autonomous systems for a wide range of job functions that weren’t practical to build out before. We’ll see this in security, life sciences, healthcare, finance, manufacturing, and many other fields. Either way going to be a fun and wild couple of years.
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