AI Training 

The reality check for SMEs: Hands-on AI training for companies and public institutions – straight from practice. No theoretical slide battles, no hype. Instead, insights from someone who builds, programs, and tests productive AI systems in real operation every day.

The problem in everyday practice is almost never a simple, wrong number. It's the absolutely self-assured, rhetorically perfect defense of a mistake, instead of the immediate admission that data is missing. This is exactly the pattern your teams need to recognize – before such a hallucination flows unchecked into a critical business process.

I know the reality behind the algorithms. When I show your employees how large language models (LLMs) behave, I do it from the perspective of a programmer who modifies these systems, hosts them locally, and tests them under real-world conditions.

I'm not selling you artificial enthusiasm. I give your teams the unfiltered, technological foundation to use AI tools in a business-critical, safe, and error-free way. In effect, to prevent potential damage from AI to your company.

Block 01: The mechanics under the hood 

• Statistics, not consciousness: Why you're talking to a probability model, not a mind – and what that means for the validity of results. 

• The invisible lever: How prompt architecture, context window, and training data determine outputs. 

• Interfaces & tool use: How AI models technically access external tools or databases – and where the logic breaks down. 

Block 02: Where practice falls apart 

• Context decay: Why the quality of LLMs drops sharply in long, ongoing chats. 

• Session amnesia: Why every new session technically starts at exactly zero, and how to prevent information loss. 

• The agreement trap (confirmation bias): Why the model would rather agree with your team and rubber-stamp mistakes than demand a logical correction. 

• Psychological dynamics: How blind faith in technology quietly paralyzes a team's independent quality control. 

Block 03: Data protection (optional) 

• What leaves the company: Why caution is needed in conversations or when sending documents. 

• Data collection: What's fact according to the terms of service, and what's actually possible. 

• Data profiles: If it's free, the user is the product. 

After this training, your team understands the limits of standard AI tools. They immediately recognize where a simple chat interface ends and where a properly built, data-secure system needs to begin. 

• Executives & tech leads whose teams are already using AI tools in daily business – whether officially approved or in a gray area.

• Companies looking for reliable guardrails and real facts, rather than being dazzled by polished, glossy demos.

• Owner-run SMEs in Switzerland, Germany, Austria, and Romania.

• Leaders who want to make solid, low-risk technology decisions without a massive IT infrastructure behind them.

I'm a developer and entrepreneur. When I talk about AI, I'm not referencing a third-party keynote or theoretical courses. I show you exactly what I observe daily while building and code-reviewing my own productive AI applications and local language models. Including all the limitations, system errors, and unvarnished realities. 

It's actually almost irrelevant. For the training, we use commonly available, free LLM models such as: ChatGPT, Gemini, Mistral, and Claude. If your company already uses a paid version, we're happy to run the training on your paid version instead. 

Let's clarify in a no-obligation initial conversation where your team currently stands and which format – workshop, in-house training, or ongoing support – makes the most sense. 

Tobias Werren, Tel.: +40775672976 (Whatsapp), tobiaswerren@gmail.com