The biggest fear around AI is simple: If two people with AI can do the work of ten people, what happens to the other eight?
It is a valid concern. AI will automate tasks. Some teams will shrink. Some skills will lose value.
But almost every discussion about AI replacing jobs makes one major assumption:
The amount of software the world wants to build will remain constant.
I don't think it will.
When building becomes dramatically cheaper, we don't just build the same things with fewer people. We build more things.
Imagine that building a software company previously required ten people. Today, AI coding agents, cloud platforms, automation, and AI-powered support might allow two or three people to build the same product.
The obvious conclusion is: eight jobs disappeared.
But consider another possibility. What if the founder who could previously afford to build one startup can now launch four products in parallel?
The individual companies became smaller, but the number of companies, products, and experiments increased.
We are already seeing early signs of this. In 2026, the startup JustPaid reportedly created a team of seven AI coding agents using OpenClaw and Claude Code. In one month, those agents built 10 major features.
Instead of eliminating every human role, the company redirected people toward higher-priority customer work and even hired a new developer who was trained largely by the AI agents.
AI doesn't only reduce the number of people required to build something. It increases the number of things people can afford to build.
Before cloud computing, companies needed people to buy and install servers, manage operating systems, configure networks, maintain storage and backups, provision infrastructure, and operate physical data centers.
Cloud computing automated or eliminated many of these responsibilities.
But the technology industry did not disappear. Instead, we created new careers:
Cloud computing removed work, but it also made technology cheaper and accessible to millions of additional companies.
AI could create the same transformation—much faster.
We are moving from AI systems that answer questions to AI agents that take actions.
Agents can deploy infrastructure, modify production systems, process customer requests, approve transactions, access company data, and create cloud resources.
Now imagine an AI cloud agent making the wrong decision. It could delete production infrastructure or create millions of dollars in cloud costs.
Or imagine a support agent processing one million tickets with a 2% serious error rate. That is 20,000 incorrect decisions.
Someone still has to answer critical questions:
The more autonomous AI becomes, the more valuable human judgment becomes.
Traditional software testing will not be enough. AI systems are probabilistic, and agents increasingly have access to real tools, money, infrastructure, and data.
We will need people and platforms focused on:
Cloud computing created cloud security. APIs created API security. Containers created container security. AI agents will create entirely new security, governance, and operational problems.
Automation does not eliminate responsibility. It increases the scale at which mistakes can happen.
Solving these problems will create companies, products, and careers that barely exist today.
AI is moving incredibly fast. Skills that are valuable today may become automated tomorrow.
That creates an unusual opportunity because nobody has twenty years of experience building production AI agents, agent observability platforms, AI evaluation systems, or AI-native software companies.
The playing field has partially reset.
Young professionals can enter emerging fields before established career paths exist. Experienced professionals can combine decades of engineering and business judgment with powerful AI tools.
The advantage will not automatically belong to the youngest or most experienced person.
It will belong to the person willing to keep learning.
If AI becomes excellent at generating repetitive code, don't build your entire career around writing repetitive code. Move one level higher. Learn how to:
The most valuable technology professional of the AI era may not be the person who writes the most code.
It may be the person who knows:
What should we build? How can AI help us build it? How do we know it actually works? And how do we operate it safely at scale?
AI will eliminate some jobs. But it will also make thousands of new products economically possible.
Those products will need to be built, integrated, evaluated, secured, monitored, governed, improved, and turned into businesses.
The amount of opportunity in the world is not fixed.
AI is expanding what individuals and small teams can attempt to build. The biggest opportunity is not in competing with the tool.
It is in becoming exceptionally good at using it.
The best way to prepare for the AI era is to start building, experimenting, and learning how these systems actually work.
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