Is software going obsolete? By 2028, will SaaS be dead, and everything agentified?
To answer this question, we should start by looking at the total investment in AI compared to the other largest economic drivers in history:
- WW2: 35-40% of GDP, or $6 trillion accounted for inflation
- US/UK trains: 10% of GDP, or $500 billion, accounted for inflation
- AI: 1-2% of GDP, or $5 trillion, current day
Jevon’s Paradox reads that an increased efficiency in a resource makes it cheaper, ultimately leading to higher total consumption rather than lower. This contradicts the assumption that efficiency reduces demand.
In the age of AI, why is this important?
Well first, let’s put it to practice. In the 1800s, William Stanley Jevons noticed that when steam engines became more efficient (using less coal to do the same work), people didn’t use less coal. They actually used more coal because steam engines suddenly became profitable for thousands of new uses.
Extrapolating this out to AI, we have to look at ways people seek competitive advantages.
Instead of proprietary code, we have proprietary workflows.
Instead of cloud-based token usage, we have self-hosted agents that incur less costs (and: how to set that up, how to maintain them, how to create guardrails, how to guide their evolution… all jobs). Then, we figure out how to create cheat code prompts that enable agents to work faster and smarter while consuming less, or doing so on cheaper models.
Instead of paying for bloated SaaS licenses, organizations will build it themselves or look to lower-cost, industry-specific solutions that might play nicely with the organizations internal agents.
And so on.
Software/SaaS will no longer just be a product. It will become the actual fabric of our society. In doing so, the app/email/website layer will become the baseline, and building agentic systems, implementation, and maintenance will be the next level after that – with huge rewards for those who start preparing now.
What else it means: Meta, or any larger company, might be able to find huge efficiencies by cutting staff. They’ve already operationalized the base layer, so they need to find cutting-edge talent that already uses AI efficiently.
But the local service company that has four franchise locations? Or, the average dental practice, landscaping company, or small legal team?
They will reap huge returns from investing more into tech – both into their current team and hiring.
While secretaries and executive assistants today may be been among the first to go, according the Financial Times, the role itself is not obsolete. It will take time, but the next iteration will be responsible for agentic implementation and maintenance.
Like all things though, it will take time. The next generation of workers need to be agentic-proficient; the problem is, company leadership is both slow to adopt and does not really know what this new reality will look like.
Many small businesses have a few people who vaguely understand tech but still get caught up with their emails, and they outsource part of their base layer – like their website – to another company. However, now, they need to quickly get past this first layer in order to start achieving real results with the second layer.
AI increases the surface area that a brick and mortar business needs to be tech literate. I
Tech efficiency has always been a way to create a competitive advantage (and it still is – look at your average restaurant website today). Now it will be the floor. Base layer one. Which means more of everyone investing into the tech side of their business.
AI is making tech more pervasive. To compete and win, small and mid-sized businesses will not only need to increase the breadth of their digital aptitude, but their depth as well.
Next time you’re in public, look at how many people are on their phones. That’s the surface area. Attention = $. Build something to win it. Or help someone else build it.