Where is the AI revolution at?

Source: Dev.to

Introduction

For several years we have been promised revolutions: “Everyone can be a programmer,” “Apps for everything,” “No need for SaaS anymore.” AI is said to be revolutionising our daily lives—managing calendars, emails, business trips, holidays, and every aspect of existence.

But where is this revolution really at? It is not AGI, which is a completely different concept used mainly for narrative purposes. We still haven’t solved poverty, we don’t have energy from a nuclear‑fusion reactor, we aren’t writing code on a quantum computer, and cancer remains a dangerous, often lethal disease. So, what exactly is AI revolutionising?

The Current State of AI

• Tools we already use – I use AI myself.
• Email assistants – Claude Cowork can manage your emails, yet many of us still rely on traditional email.
• Data dashboards – Perplexity Computer can create KPI dashboards, assuming the underlying data is correct.

There are over two million apps on the market. Instead of a few high‑quality health apps, we see hundreds of mediocre copies. Meetings are not reduced; they are automated with AI note‑takers that talk to each other. Hiring processes are increasingly filtered by AI‑generated CVs evaluated by AI HR systems on “human parameters.”

What we mostly see is the automation of repetitive, “monkey” work. Automation itself is valuable—human evolution has always been driven by it. I still type these words by hand, complete with errors, to illustrate that not everything is automated yet.

Today’s so‑called “AI revolution” is largely about scaling transformers, statistical models, big data, and compute. These systems excel at pattern recognition and analogical reasoning, but they remain probabilistic engines, not true intelligences. We have not built artificial cognition; what we call “AI” today is a sophisticated layer of prediction, not biological intelligence.

Limitations and Missing Pieces

• Lack of artificial cognition – Current models are prediction machines, not entities that understand or think.
• Need for new mathematics and architectures – Beyond large language models, breakthroughs may require new math, novel architectures, and possibly new physics (e.g., nuclear fusion, quantum computing).
• True AI requires understanding emergence – Imitating human behavior may never be the optimal path; we need to understand how intelligence emerges in the first place.

The present wave is transformative, but if it vanished tomorrow, the industry would keep moving. The real shift will occur when machines can generate new concepts, hypotheses, and world models autonomously—something beyond “just another AI model” like Claude 4.6 or Gemini 3.1.

Impact on Work and the Economy

Software development, junior programmers, and many other roles are already feeling the pressure of business decisions: weekly layoffs, constant patch cycles, and broken‑window fixes. This is not merely a question of replacing developers; it is a question of number‑crunching, with AI arriving at a time when capital and compute are abundant.

The current dynamics create a downward spiral:

1. AI promises efficiency → companies invest heavily.
2. Money flows into AI tooling → hardware prices rise.
3. Cost pressures lead to layoffs → workers have less purchasing power.
4. Reduced demand pushes prices higher, perpetuating the cycle.

From a “Dr. Evil” perspective, AI becomes a convenient excuse to cut high‑cost staff hired during boom periods, especially when growth expectations fall short and inflation erodes margins. The real issue isn’t if AI will replace developers; it’s how we manage the transition and ensure the technology serves broader societal goals.

Looking Forward

The most promising application of AI is still in augmenting creative processes, not just automating spreadsheet tasks. We have yet to take full ownership of these tools to steer evolution toward beneficial outcomes.

I don’t have a definitive answer for breaking the current spiral, but history shows that societies adapt—from the industrial revolution to the internet age. Perhaps we need to collectively give AI real meaning, purpose, and governance so that its benefits are shared widely rather than concentrating wealth and power.

Call to Action

What are you changing for the better? Have you witnessed the AI revolution in your own work or life? Share your experiences and ideas so we can shape the next phase together.