If you look at how software was built over the last ten years, the most striking feature is the sheer number of people in the room who didn’t actually build the software.
We created a massive, highly paid layer of translators. We hired product managers to translate business requirements into Jira tickets. We hired marketers to translate product features into campaigns. We hired engineering managers to translate architecture into manageable two-week sprints.
We did this for a good reason. Systems were incredibly brittle, the tooling was heavy, and the cost of making a mistake in production was high. The space between having an idea and shipping it required a crowded room of people to manage the complexity.
I've seen that room emptying out recently.
I predict that next year we are fully entering the "Doer Economy". AI has fundamentally collapsed the distance between a vision and its execution. When the cost of writing code, drafting copy, and generating boilerplate drops to near zero, the value of pure execution drops right alongside it.
If your primary professional skill is completing a highly specific task that someone else defined for you, you are now competing with a machine that does it instantly.
The people who win this next era will be the ones who can hold a vision in their head and execute it themselves.
We are already seeing this shift at the top. CEOs and founders are moving much closer to the product. Previously, a founder would eventually have to step away from the code to manage the people managing the people writing the code. They needed a deep hierarchy to test a single hypothesis. Today, a founder with technical context can sketch the architecture, have an AI generate the scaffold, and validate the idea directly in an afternoon. The companies that survive the next few years will have fewer people doing significantly more work, simply because the organizational drag of coordination has vanished.
This shift completely changes the software we buy, too.
SaaS companies are realizing that their core value is no longer a massive, complicated dashboard that requires a certification to use. Smart SaaS providers are shifting their focus away from the UI and toward developer primitives. They are shipping robust SDKs, incredibly clean APIs, and documentation specifically written to be digested by language models.
When you are building in the Doer Economy, you do not want to spend three weeks configuring a backend. You want to point your local AI agent at a service like Vercel, Supabase, or Contentstack, have it read the API documentation, generate the boilerplate, and hand you a fully connected system before your coffee gets cold.
The SaaS platform handles the plumbing. The AI handles the syntax. You focus entirely on the business logic and the user experience. You get to build the actual product.
This is a brutal paradigm shift for anyone entering the industry right now, and the standard advice they receive is terribly outdated.
For years, the playbook was to learn a narrow technical skill, keep your head down, and slot yourself into a large corporate machine. You learned how to take a ticket, write a React component, and pass it to QA.
That machine is shrinking. The new baseline expectation is shipping. You need to learn how to do more with vision, rather than executing isolated tasks without questioning the whole product. The code itself is no longer the hard part. Figuring out what the user actually wants, how the system holds together, and why the product matters, that is where the value lives now.
If you are starting out, stop waiting for a perfect roadmap. Stop waiting for a Jira ticket to give you permission to build. Start shipping what is in your head, throw it away when it breaks, and build it again until you hit something useful for someone else.
The future belongs to the people who can build it. The people who only know how to manage the builders are going to struggle.
Frequently asked questions
What is the Doer Economy described in the article?
The Doer Economy is a shift toward a world where the people who succeed are those who can both hold a product vision and execute it themselves, largely by leveraging AI and modern SaaS platforms. Instead of relying on layers of managers and specialists to translate ideas into tasks, individuals use AI to generate code, boilerplate, and content, dramatically reducing coordination overhead. In this model, value moves away from narrowly defined executional roles and toward end-to-end builders who understand users, systems, and business impact.
How does AI change the structure of software teams and companies?
AI reduces the cost and time required to write code, draft copy, and generate boilerplate, which in turn shrinks the need for large, hierarchical teams dedicated to coordination and translation. Founders and leaders with technical context can now design architecture, have AI generate scaffolding, and validate ideas directly, often in a single afternoon. This leads to smaller organizations where fewer people do more impactful work, and where the emphasis is on product understanding and shipping rather than managing complex processes and ticket flows.
What skills should someone entering the software industry focus on now?
New entrants should focus less on narrow, ticket-driven skills and more on becoming end-to-end builders. That means learning how to ship complete products, understand user needs, design coherent systems, and articulate why a product matters. Practically, this involves using AI and SaaS primitives—clean APIs, robust SDKs, and platforms like Vercel or Supabase—to offload boilerplate and infrastructure. The key skills are product thinking, rapid iteration, and ownership of outcomes, rather than simply completing predefined tasks in a large corporate machine.
