An AI conundrum: Products or Partnerships

In building and selling software, there are two main ways to do it: Sales-led, or Self-serve. There is no ‘one right way’, but over the last 15 years of Saas, the pros and cons of each became very clear. The question we face now is: which one is better for building AI products? Or is there a new way that is better than both?

We’ve been deep in this now for 2 years, let’s step through it.

Self-serve means that customers do everything themselves: learn about the product, sign up, explore the product, and succeed or fail based on whether they could get set up well, and see enough value to continue. Successful self-serve requires an excellent product experience, excellent new user experience, and excellent in-product onboarding. Self-serve is product first. Everything you experience is real running code. The big risk here is that great potential customers never get set up properly, and conclude that the product is poor (even when it isn’t!). Worst case, the customer puts something live that doesn’t work properly and they damage something: their customer engagement, their data systems, their brand.

Sales-led means that customers get help from a Sales team who are trained to help them understand the product, sign-up, get activated, see success, and continue to expand their usage. Products with a sales-led motion tend to be complex, and even confusing, but the sales team will help explain everything. Sales-led is partnership first. But because you’re not directly interacting with running code, sometimes the product is a promise more than it is real. Worst case it is jazz hands and vapourware.

Startups and naive product people (yes this was once me) have a tendency to shit on sales-led motions because they aren’t product first. But that’s myopic. Some of the best customer experiences are sales-led and partnership first. In its best form, this partnership is a deep collaboration on understanding a customer’s problems, and configuring the product to best meet their needs. Hmm, understand problem > configure solution, that sounds like product development…?

Many businesses start with a simple product, but as they add customers, those customers have feature requests, and as they add the features, the product becomes more powerful and more complex. It becomes harder to maintain a great user experience, harder for people to learn it all by themselves. This battle to scale a great user experience has tortured me for years. So many businesses start self-serve, but by necessity add Sales later.

So, how do you approach AI products?

The difference between Saas products and AI products is that Saas is predictable and AI is not. Saas products are direct manipulation, CRUD apps, where users click UI and by doing so, they create/read/update/delete data in a database. Designed well, they are easy and predictable to use because we’re all using the same components: text fields, dropdowns, buttons, etc. You don’t write an email or Slack message, hit the send button and wonder what will happen next. Even when complex, we can teach people what to do.

In contrast, AI products are unpredictable. We do wonder what will happen next when we ask Claude a hard question, or give Cursor a task. When the feedback comes, we do wonder how it worked.

In Saas, the unpredictability is with the humans involved. Are people following our policies? Are they applying their training? Can I trust my team to do a good job?

In AI products, the unpredictability has been moved to the AI layer. Is the AI following our policies? Is the AI applying its training? Can I trust AI to do a good job?

Because the unpredictability is in the AI layer, all companies building AI Agents for Customer Service have a heavy Sales-led motion. And not just Sales, but a team of people working in deep partnership with the customer and building bespoke new software together.

This is what we’re doing with Fin (our AI Agent). As well as Sales and Success, we have PMs, Designers, Data Scientists, Engineers, all building directly with customers to understand their customer data, their customer conversations, their knowledge and systems, and building a solution that works for that customer. Often we’re really changing their perceptions, they start by having a go themselves, concluding it doesn’t work very well, but then we get involved to help and advise and every metric improves.

We’re doing this with many individual customers and then using what we learn to design a product that is valuable much more generally to lots of other businesses. We’ll expand on this another time, but this deep builder partnership model is a new way to build software. Because of the unpredictable nature of AI products, and the complexity in any one business’ customer data and systems, deep partnership is required to get customers to resolution rates that match the technology’s potential: 80%+ customer queries excellently resolved by AI.

And yet. Intercom’s history was self-serve. We deeply believe in only ever marketing and selling real product. Real running code. No bullshit, no vapourware. Like many others, we added Sales-led later. In fact, during the boom years we went too hard on Sales-led, and had to rediscover our roots as a passionate product company building a product that anyone can try, anytime, without having to talk to anyone.

So Intercom has self-serve flows for everything. And we have 1000s of customers who have been using Intercom for human support successfully adding Fin without any human help from us. Despite the unpredictability, many are working it out themselves. They are getting 50%+ resolution rates through their own perseverance.

So this week we went a step further. We shipped the ability to sign-up for Fin on our competitor platforms all by yourself.

This is risky. What if many new customers try it, don’t get activated, don’t see the value, and think the product doesn’t work? What if they tell their peers? What if it damages Fin’s reputation? None of our competitors let people do this.

But we believe in the power of open software that anyone can try. We believe that people want to play with new things. And there is great energy, excitement, and value in that.

So please go have fun 🙂