The Future of Work with AI: What Will Software Developers Do?
AI in software development

The Future of Work with AI: What Will Software Developers Do?

This is the first article in the series of co-written articles, where Marjut Sadeharju and I explore how AI is reshaping the role of developers. We discuss how human-centric skills—such as business consulting, communication, and problem-solving—will define the next generation of developers.

From coders to strategic advisors

What will the future job description of a software developer look like in an era where AI can boost their productivity by weeks, even months?

The answer lies in human-centric skills: understanding business needs, consulting, and effectively communicating solutions. Many companies struggle because developers and business leaders speak different languages. A common frustration is that business stakeholders define a feature one way, while developers interpret it differently, leading to inefficiencies.

For years, a major challenge in software development has been bridging the gap between technical and business perspectives. Traditionally, it could take months before an idea materialized into something tangible. AI accelerates this process dramatically. But even with AI, the real value of a developer lies in their ability to interpret business needs correctly and collaborate effectively.

A developer’s value will increasingly come from their ability to listen, ask the right questions, and act as a strategic partner—not just someone who writes code. AI will handle execution; humans will provide insight.

Case study: rapid prototyping with AI

"I built an entire SaaS system in just 20 hours using AI-assisted development. The first working version was out in a matter of hours, and we continuously iterated based on user feedback. Traditionally, this would have taken weeks, if not months. The key here was not just the speed of AI-powered coding but the ability to rapidly validate the idea with stakeholders and refine it in real-time."

This represents a fundamental shift in how we build software. Instead of lengthy specification documents and misaligned expectations, we can now rapidly produce working prototypes, allowing businesses to see and interact with their ideas almost instantly.

The ability to quickly test and iterate solutions—instead of getting stuck in lengthy planning phases—creates better alignment between business needs and technical execution.

AI as a personalized productivity and leadership coach

Right now, most AI discussions focus on boosting technical productivity—how AI helps us write code faster. But what if we used AI to strengthen other essential business skills, such as negotiation, teamwork, communication, and creating environments for experimentation?

These are the real differentiators in a world where AI can generate perfect code in seconds.

What if AI wasn’t just a tool, but a mentor that helps professionals improve their work habits, leadership skills, and communication?

Imagine an AI assistant integrated into your workday:

  • It analyzes your emails and tells you whether your tone is persuasive, consultative, or unclear.
  • It tracks recurring mistakes in your coding and suggests learning materials tailored to your weaknesses.
  • It listens to your meetings and provides feedback on whether your explanations were clear to a non-technical audience.

AI could help business leaders, developers, and knowledge workers reflect on their strengths and weaknesses, much like a personal coach. This would allow people to become better communicators, problem-solvers, and decision-makers—skills that are invaluable in every industry.

The AI era challenges traditional client partnerships

In the past, businesses hired software developers to build solutions from scratch—a process that could take months before delivering real value. Now, AI allows anyone to become ultra-productive by learning how to use the right tools efficiently.

This raises a crucial question:

What is the role of developers if business users can now generate working solutions themselves?

We need to stop seeing development as just writing code and instead focus on enabling business innovation. Developers will become facilitators who guide companies in leveraging AI tools to create solutions faster and more effectively.

Rather than a traditional vendor-client relationship, the new AI-driven approach enables efficient co-creation—where developers and businesses iterate together, experimenting and refining solutions in real-time.

The ability to understand the client’s true needs and translate them into effective AI-assisted implementations will be the new core competency.

The human-AI partnership: from execution to insight

The future of AI is not about whether it will replace developers—it’s about how developers will choose to integrate AI into their professional and personal growth.

Instead of spending weeks coding a feature, a developer’s role will shift to:

? Advising businesses on AI-driven solutions.

? Guiding AI systems to ensure alignment with real-world needs.

? Acting as strategic consultants who help organizations navigate AI adoption.

AI assistants could evolve into personalized mentors that enhance productivity, decision-making, and leadership skills.

The real question is not whether AI will change our work—it already has. The question is: How effectively are we partnered with it?


Excellent insights! I have been thinking about this more in general and I think we are heading to this direction with all of the occupations., not just coding. In other words, as AI takes over repetitive tasks, we’ll see a bigger divide between people whose jobs are almost exclusively around “thinking” and those who do hands-on tasks that AI can’t yet handle (at least until robotics matures). One critical thing is how mentally draining it can be if our roles shift more toward sustained “deep thinking.” I notice this in my own work. I used to spend a lot of time on simpler tasks, like looking things up online or finding the right person to help me. Now AI speeds up that kind of searching and filtering, so I end up doing more high-level reasoning or creative problem-solving—which is more exhausting. We already know that few people can maintain full mental intensity for eight hours straight, so as AI accelerates the easy tasks, we may need to consciously limit or schedule our hardest thinking intervals to avoid burnout.

Manuel Furlotti

Sales I SaaS I Business Development

1 个月

In Ottia we believe that especially product teams are transforming to prioritize strategic activities, insights, and user-driven innovation in response to evolving market and technological demands. As traditional development roles shift, the focus is increasingly on driving strategic value and innovation. ( gathering more customer insights for ex.)

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