Personalization Is All You Need: How AI Can Unlock Enterprise Markets

I’ve referred to my role/scenario AI design principle a couple of times now and briefly touched on personalization, but it’s much more of an important component than you might think. Personalization is the afterburner that accelerates the capabilities of your intelligent architecture, Especially for small teams and startups, when you design AI applications to perform a job function—using policies, procedures, and personalized note-taking—you unlock capabilities that were once impossible for small players. Suddenly, anyone can build scalable products that adapt, capable of working for everyone from individual users to enterprise-scale customers.

Unlimited Custom Fields

If we continue the analogy that your AI application works like an intern hired to do a job, it has the tools, the job description, and a notepad for learning how to do the job better each day. This approach allows your AI to adapt in real-time to the unique ways each customer or user works—absorbing their feedback and building a custom approach for each. Compare that to the typical enterprise software approach: sprawling settings, toggles, and fields designed to meet every possible business process. Enterprises often have byzantine, bizarre business needs that vary wildly not just between companies, but even across teams within the same company.

Instead of designing bloated, one-size-fits-all suites, we can now build AIs that customize themselves. The flexibility isn't hard-coded through toggles and switches—it comes from how the AI remembers and learns, adapting knowledge and processes based on each customer's quirks.

Infinite Custom Integrations

This flexibility extends to integrations. Give your AI app the power to write custom code, and suddenly you've unlocked valuable new capabilities. One of the toughest parts of enterprise sales is working around legacy tech or custom tools. You might find yourself dealing with random spreadsheets, non-conforming data, or a custom API nobody ever documented. A goal-driven AI app can intelligently write code to solve these problems: cleaning data, connecting to old mainframes, or even just managing esoteric FTP file drops. And yes, it could even send faxes if that’s what it takes.

During a demo for a food industry conglomerate (for Zucca, pre-launch), the prospect stopped us, warning us that most software couldn’t handle their complex ingredient data—like ingredients in pounds and kilograms and strange minimum order sizes. I simply told the copilot about the constraints on the fly, and it wrote the necessary Python code in real-time, adapting to their needs and opening the door to a second meeting.

Unforseen Creative Solutions

Personalization also means more creative problem-solving. When demoing Clara AI, a prototype companion app for seniors that helps with medications, someone asked, "What if you tell her you don’t want to take your pills?" I tried it out. Clara thoughtfully suggested: "Why don’t we make it fun? Next time you take your dog Max for a walk, when you come back you can take your meds and each get a treat." Clara remembered the user's dog from an earlier conversation and turned the situation into a positive moment. The same principle could let Zucca come up with creative production plans or custom formulas based on available equipment or labor—personalizing not just communications but actual solutions.

Invaluable Institutional Memory

Personalization even captures institutional memory. An AI engine used by expert users can retain the knowledge it gathers through interaction. It learns standards from senior team members and keeps that knowledge around even when those people retire or move on. With Glue, a product for developing hardware manufacturing test plans, senior engineers work using the standards they care about, and over time, junior engineers can be assured their work will conform appropriately, knowing the AI will catch the things the veterans would have spotted. This is a new kind of efficiency through reduction of lost experience, especially in industries where senior expertise is irreplaceable.

This quickly creates a substantial switching cost hurdle for moving to competitors. Investors are always asking about moats and switching costs and “how is this different than ChatGPT?” A thoughtful implementation of personalization in an AI application can go a long way toward addressing those questions.

Unlimited Future Possibilities

An architecture that applies custom interpretations of business rules is also future-proof, built to evolve alongside new foundation models. As these models improve, their capabilities plug right into our personalized, goal-oriented framework, allowing for smarter, better solutions without the need to design for every use case up front. The intelligence can simply learn and adapt—maybe in ways that we can’t really imagine today.

We're not just building tools; we're building the foundation for intelligence that can tailor itself to every need, making the possibilities of deeply personal and creative AI a reality, even for the smallest startups or solo founders.