Introducing the One-Man Show Model in Software Development

We recently ran an in-house experiment, and the results were eye-opening, to say the least.

Here’s the rundown.

• Test subject: Someone with no formal software engineering background
  
• Tools: AI agents and modern coding platforms
  
• Goal: Deliver production-ready software

The experiment played out in two distinct ways.

• For simple tasks, like basic CRUD applications, integrations, or prototypes, the output was surprisingly solid. AI compensated for the lack of technical expertise, producing code that worked and passed initial checks.
  
• For complex tasks like enterprise-scale integrations, security-heavy solutions, or architecture-sensitive builds, the results collapsed. The code had to be redone from scratch because the test subject lacked core software engineering concepts like scalability, maintainability, and design patterns.

So while AI can democratize coding for small businesses, the risks are real when applied to enterprise-grade solutions.

The one-man show in music vs software

Despite the experiment’s split results, we reached an interesting conclusion: the future of engineering will heavily rely on the one-man show model.

This model is inspired by the music industry, where today a single artist can write, compose, produce, and distribute their music with the help of virtual studio technology and digital tools. So, a single person can do the job of an entire production house.

In software, this translates to:

• A software orchestrator with deep domain expertise and strong architectural understanding will lead.
  
• That same person will not write every line of code but will run, guide, and coordinate multiple AI agents to generate, test, and refine software.
  
• Supporting the orchestrator will be a small core team (e.g., 1–2 senior full-stack engineers) to handle the most critical and nuanced tasks.

Instead of a team of ten engineers, we might end up with one orchestrator and two seniors running the entire show.

Specialization reversed: generalist in code, specialist in domain

In addition to reducing team size, the one-man show model is also changing what kind of expertise will be most valuable in the future.

• Coding specialization → generalization
  Traditional distinctions (front-end vs. back-end vs. mobile) will blur. Orchestrators will need broad, generalist software knowledge across the stack since AI agents can generate in multiple languages and frameworks simultaneously.
  
• Domain knowledge → specialization
  On the other hand, domain expertise is becoming more specialized than ever. A software architect with deep knowledge of healthcare, retail, or financial systems offers greater value than one with just generic industry exposure. Why? Because orchestrating AI agents requires knowing the exact problems, rules, and outcomes of a given sector.

Risks and opportunities

For enterprises, handing over complex builds to non-engineers with AI is a recipe for rework, hidden vulnerabilities, and unstable architectures. Yet for small businesses, the same democratization lowers barriers and commoditizes simple software.

The sweet spot lies in the one-man show model, where the orchestrator becomes the new engineer-musician, performing with a band of AI agents and backed by a small but highly skilled team.

Wrapping up

Contrary to popular belief, the future of software engineering isn’t about replacing people with AI. It’s really about reshaping the craft. Large teams of narrowly specialized developers will give way to leaner setups led by orchestrators with deep domain expertise, augmented by AI agents.

In other words:

• Generalized coding knowledge, specialized domain expertise

• Smaller teams

• Bigger orchestration