Source: Bitkom Research, 09/2026, n=603
This is a maturity gap, not a technology gap. Maturity comes from teams that have run these systems for real, not from teams that only bought them.
Share of German companies using AI
WARNING: > 40%
of agentic-AI projects are cancelled by the end of 2027: cost, unclear value, weak risk controls
Gartner, 06/2025
0% FULLY USED
59% say they do not use AI's potential at all
Bitkom 2026
2 DEC 2027
high-risk duties under the EU AI Act apply (Annex III); transparency duties for existing systems from 2 Dec 2026
Regulation (EU) 2026/1744
ONE IN THREE
companies see their existence threatened by AI
Bitkom 2026
THERE IS ANOTHER WAY.
The signal is clear again. Next: how to spot a bluff.
Anyone can call themselves an AI expert. Four questions separate the people who built from the people who consumed.
A large model writes the instructions, a small one runs the standard case. The choice rests on a test series with your own data, not on a leaderboard.
“We always use the newest model.” No reason, no comparison, no number.
The agent holds only the rights the run needs. Errors are caught, logged and handed to a person before anything is written.
“That doesn't happen with us.” No failure paths, no log, no plan B.
With a fixed test set per workflow: success rate, escalations, response time and cost per task. It runs again after every model change.
“The users are happy.” No before and after, no test series.
Yes, here is the link. It runs in public, and you may test it until it breaks.
“Gladly, in our next meeting.” Slides instead of a system.
Try it now
Ask the agent what we build and how.
Or use the chat button in the bottom right corner of this page.
Talk to a voice agent the way it works in customer service.
A commercial without a camera: camera moves and characters steered by context engineering.
An agentic newsletter on health and nutrition.
NutriMindz Agentic App · in developmentWhoever answers all of them has built. Whoever dodges has consumed.
ChatGPT arrived in November 2022, GPT-4 in March 2023, MCP in November 2024. Nobody has a decade of this in production. TechChase has been building since 2023. We don't claim to know everything — we show what we built.
Which documents and rows an agent sees, and which systems it may write to, is set per run, not once for everything.
An agent never gives the same answer twice. So every workflow gets a test set and criteria that are fixed beforehand.
Scaling, monitoring, cost per task and model changes are part of building, not an afterthought project.
Five questions, one fact per answer, your result at the end. No email needed to see it.
