In conversation with Anthony Brown, Former Head of Data and AI at Procurement Sciences, now Senior Strategic Account Director at Salesforce.

"AI is democratizing software creation, allowing people who aren’t developers to build solutions for their own specific needs."

The new builders of software aren’t developers

Software is no longer just built by engineers. In today’s AI-native landscape, product managers, project leads, salespeople — even homeowners — are becoming builders, solving problems with tools they couldn’t have touched a year ago.

Anthony Brown, former Head of Data and AI at Procurement Sciences and now a Senior Strategic Account Director at Salesforce, sees this shift playing out both at work and in daily life. In a recent conversation, he shared a personal story that captured the moment we’re living through — where AI is enabling people to build customized tools without touching code.

A real-world use case: The image converter side project

“We recently listed our house for sale, and the photographer provided all the image files in a project format that wasn’t JPG or PNG — it was something like AVIF format.”

Faced with an unusual and unsupported file type, Anthony did what many of us do — he started searching online for a quick fix. What he found were limited solutions and paywalled tools.

“Instead of wasting time or paying for a service, I was able to build exactly what I needed in 15 minutes.”

With the help of AI tooling, he created a file converter where users could upload AVIF images and convert them to formats like PNG on the fly.

“I was able to make a converter here where you just upload a file, select the output format — like PNG — and it converts instantly.”

This wasn’t part of a startup. It wasn’t a commercial tool. It was a solo project, solving a very specific problem, powered entirely by no-code AI capabilities.

PMs as builders: From spec writers to prototype creators

This trend isn’t limited to side projects. Inside organizations, non-technical roles are increasingly participating in software creation, thanks to tools like v0.dev and prompt-based UI generators.

“Product managers, project managers, and business leaders are becoming direct contributors to software development, rather than just being the people who write requirements and hand them off to engineers.”

Instead of sending rough wireframes to dev teams and hoping for alignment, people are now generating high-fidelity mockups in real time — testing feasibility before the first ticket is even created.

“I can talk with an AI model, generate a real UI, and immediately see the flaws. . . Our product manager had a similar experience — just seeing it built helped clarify why it wouldn’t work.”

The result? Faster product cycles, fewer wasted dev hours, and clearer handoffs between idea and implementation.

AI as a prototyping partner

“A lot of these AI-generated solutions are built on development-level architectures. . . You couldn’t just scale them up to 100+ users. . . But what it does allow is rapid idea validation.”

These no-code builds aren’t always production-ready, and that’s OK. Their power lies in testing ideas. A tool that solves a problem for one person or one team might not need to scale. Or, if it does, the learnings from the prototype can inform a real build later.

In Anthony’s words, it’s about short-term, personalized AI use cases — tools created to solve specific needs at the moment they arise.

The org-level shift: What tech leaders need to know

This wave of democratized software creation is already changing how companies structure their teams and workflows.

Traditional hierarchies — where engineers build and everyone else makes requests — are being flattened. AI tooling is enabling cross-functional contributors to test ideas independently, generate artifacts quickly, and remove unnecessary iterations from the product cycle.

For tech leaders, that raises important questions:

• How do you support and guide this new generation of builders?
• What guardrails do you need to ensure quality and security?
• How do you rethink delivery pipelines when prototypes can be built by anyone?

Key takeaways for tech leaders

1. Non-developers are building real tools: Product managers, analysts, and salespeople are using AI to build working solutions without engineers.
2. Rapid prototyping is faster and cheaper than ever: Use cases can be validated in hours, not weeks, by generating mockups, tools, or scripts via AI.
3. Proximity to the problem = Better software: People closest to the problem can now build the solution, without a long translation process.
4. These tools aren’t ready for scale, but they’re ready for truth: Even if AI-built tools aren’t production-grade, they’re perfect for learning what works.
5. Org structures need to evolve: Support, educate, and empower these emerging builders. Your next MVP might not come from engineering — it might come from someone in sales.