For business leaders, staying competitive long-term requires constantly rethinking your products and services for the current era.

Consider the cell phone. Today’s smartphones operate on a completely different playing field than the flip phones of the early aughts. For hardware companies, succeeding in the internet age required rethinking the entire product. That explains the leap from pocket-sized Nokias to the iPhone 17.

I launched my company two decades ago, back when AI still sounded like something out of the future. In the same vein, I often imagine how I would rebuild my startup today—what would I do differently in the AI era? I think all leaders should be asking themselves the same question because it creates an important shift in thinking: from incorporating new technologies piecemeal to rethinking systems from the ground up.

In the AI era, the most effective founders aren’t treating artificial intelligence as simply a productivity boost. They’re designing companies (or redesigning their existing companies) around the assumption that human-AI collaboration will touch nearly every function. In other words, they’re designing AI-native startups. Here are five ways founders can start doing the same from day one.

If I had to choose a phrase to describe the early days of my startup, I’d say “trial and error.” I was a solo founder and a bootstrapper. Though I’d built a small venture during college, I had minimal experience managing other people. In retrospect, it’s no wonder I held onto my day job for a while. About a year after launching, when I could finally hire some help, I slowly discovered the answers to a million small questions, one at a time, about running a business—from developing onboarding and training to setting up benefits.

AI has leveled the playing field around who can launch a startup or build a product, notes Anthropic in its newly published playbook for building an AI-native startup . It also accelerates the on-ramp. Nowadays, founders can tap LLMs like ChatGPT and Claude to find instant answers to the same questions that I faced as a first-time entrepreneur.

For example, they can research the market and competition, draft and edit documents sharing information with stakeholders, and bounce ideas off an objective sounding board. By leveraging these tools from day one, they’re embedding AI-assisted thinking and workflows into the company’s DNA, rather than weaving them in later.

Design Workflows, Not Just Jobs

Designing a company around AI means reimagining how you conceptualize work—from creating jobs to creating workflows. If designing job roles is like adding more lanes to a highway, designing workflows is like building a railway network. One adds capacity incrementally; the other changes how work moves altogether.

AI-native startups don’t think primarily in terms of hiring people to execute X, Y, or Z tasks. They think about building systems that support recurring workflows. That shift also changes what founders look for in employees: adaptable people who can evolve along workflows as the company scales.

What’s more, every organization has logistical, repetitive tasks to execute—answering routine HR questions, onboarding employees, documenting processes, or fielding internal requests. These functions don’t require constant human oversight. By embedding AI into these workflows early, founders can slash logistical busywork for themselves and other leaders as the company grows.

For example, an AI agent trained on organizational policies can field recurring payroll or benefits questions. Whether the company has five employees or 500, the workflow is reliable and scalable. Instead of repeatedly solving the same operational problems, founders can focus on higher-level decisions that move the needle for the business.

Make Every Employee A Multi-Disciplinary Operator

As a leader of a SaaS company, I’ve seen how hiring trends have changed over the past two decades. Just five years ago, companies were still prioritizing specialists. But the AI era has ushered in a seismic shift. In a world where people are increasingly tackling tasks across business areas and managing tools and AI platforms to handle busywork, generalists will thrive.

For leaders of AI-native companies, hiring generalists should be top of mind. Look for candidates with wide-ranging interests, curiosity about exploring the latest tools, and the communication skills needed to guide those tools and gather insights from their output. But leaders should also focus on equipping every employee with the tools they need to succeed. Give them the training, experimentation time, and guidance to become multidisciplinary operators.

At Jotform, working in cross-functional teams helps employees learn how AI tools apply across different domains. We also encourage employees to share their recent experiments—both successes and failures—with teams across the company during our weekly demo days. It’s surprising how often one group’s AI strategy inspires another team working on a completely different project.

Another effective strategy is rotating employees through short-term AI initiatives outside their primary roles. Hands-on training with different workflows helps employees think more holistically about the business and realize new ways that AI can speed up busywork and collaboration.

Compress The Distance Between Idea And Execution

An idea for a brilliant product or service is only part of building a business. The other side of the coin is execution. With the introduction of AI, the steps from point A to point B are still largely the same: ideation, prototyping, testing, launching. What’s changed is the speed of the process.

AI tools can automate and accelerate each step along the way. For example, experimentation and listening to user feedback are still crucial. But AI tools empower businesses to do these things without having to be part of a global conglomerate with a massive budget. AI renders sophisticated business processes more accessible to all companies, including scrappy startups.

With this mindset—a compressed distance between idea and execution—AI-native startup founders are more nimble. They can move faster and adapt more quickly to evolving markets and tech landscapes, which is a strong competitive edge. Pivoting, for example, doesn’t feel like as much of a sink-or-swim situation, but instead like an insightful, remediable experiment.

Keep Humans Focused On Judgment And Relationships

There has never been a bigger premium on soft skills—or as they’ve been rebranded, “ power skills ”—than there is right now. Soft skills are that cluster of non-technical skills like empathy, communication, leadership, and judgment. In a time when school-aged children can design a website with vibe coding, the qualities that make professionals shine will be the ones that AI can’t imitate.

The way I see it, the most successful AI-native startups and AI-forward companies will be those that promote the continual development of those soft skills—through practices like mentorship, empathy exercises, active listening training, and more. They’ll encourage employees to automate as much as possible to leave more time for tasks requiring empathy, relationship building, and judgment—the kind only humans can do. In other words, as AI handles more of the execution, human value will lie in how well we think, relate, and decide.