Its still not a Hype, its still crazy what is possible today and we still have no clear at all if this progress continues as it does or not with the implication, that if it continues, it has major implications.

My wife, who has no clue about coding at all, chatgpted a very basic android app only with guidance of chatgpt. She would never ever been able to do this in 5 hours or so without my guidance. I DID NOT HELP HER at all.

I'm 'vibecoding' stuff small stuff for sure, non critical things for sure but lets be honest, i'm transforming a handfull of sentences and requirements into real working code, today.

Gemini 3 and Claude Opus 4.5 def feel better than their prevous versions.

Do they still fail? Yeah for sure but thats not the point.

The industry continues to progress on every single aspect of this: Tooling like claude CLI, Gemini CLI, Intellij integration, etc., Context length, compute, inferencing time, quality, depth of thinking etc. there is no current plateau visible at all.

And its not just LLMs, its the whole ecosystem of Machine Learning stuff: Highhly efficient weather model from google, Alpha fold, AlphaZero, Roboticsmovement, Environment detection, Image segmentation, ...

And the power of claude for example, you will only get with learning how to use it. Like telling it your coding style, your expectations regarding tests etc. We often assume, that an LLM should just be the magic work collegue 10x programmer but its everything an dnothing. If you don't communicate well enough it is not helpful.

And LLMs are not just good in coding, its great in reformulating emails, analysing error messages, writing basic SVG files, explaining kubernetes cluster status, being a friend for some people (see character.ai), explaining research paper, finding research, summarizing text, the list is way to long.

Alone 2026 there will go so many new datacenters live which will add so much more compute again, that the research will continue to be faster and more efficient.

There is also no current bubble to burst, Google fights against Microsoft, Antrophic and co. while on a global level USA competets with China and the EU on this technology. The richest companies on the planet are investing in this tech and they did not do this with bitcoins because they understod that bitcoin is stupid. But AI is not stupid.

Or Machine learing is not stupid.

Do not underestimate the current status of AI tools we have, do not underestimate the speed, continues progress and potential exponential growth of this.

My timespan expecation for obvious advancments in AI is 5-15 years. Experts in this field predict already 2027/2030.

But to iterate over this: a few years ago no one would have had a good idea how we could transform basic text into complex code in such a robust way, which such diverse input (different language, missing specs, ...) . No one. Even 'just generating a website'.