Results

Content & Translator Agent saves over 250 hours per month in content generation and enables high quality and customer proximity thanks to specialized LLMs 

With the Agent Architecture, DPD significantly reduces production time and increases output: 2 days → 30 minutes per asset, 270 pieces of content in a short period of time, ~1 FTE/year capacity freed up; in total, this amounts to over 250 hours per month  of saved content and translation work. In service, since 09/2025, a largely automated analysis of conversations provides an objective basis for coaching and quality management (Human-in-the-Loop remains in place).


Initial results show significant efficiency and quality gains: 


  • Time-to-Content: −97% (20 min → < 30 sec per caption) 
  • Output volume: Over 500 social media posts created with the Content Suite 
  • Quality gain: better SEO optimization and greater creativity of the posts 

“Together with Andreas, I trained the Content Butler already during the development phase—and from the very beginning, the collaboration was clear, efficient, and cooperative. His reliability, solution-oriented approach, and enthusiasm for working together greatly enriched the project.


Today, the Content Butler is a real game-changer for us: not only do we produce much faster, but we also keep our brand voice consistent—and that of our clients as well. It enables us to deliver exactly the presence that defines cxb across every channel: clear, unified, professional—and full of personality.”


Maj Lina Schönrock – Head of Marketing at cxb 


Executive Briefing

AI Engineering in 2026 Claude Code, Developer Productivity, and AI Security

William Senn March 26, 2026 Online • 09:00–10:00 CET Language: English

Build faster, build safer. This compact session shows how to use AI code pairing with Claude Code to accelerate routine software delivery, while embedding security and governance into day-to-day dev workflows.

“Speed only matters if it ships safely. The goal is higher throughput with human review, testing, and governance built in.”

Overview

AI assistance is moving from experimentation into standard engineering practice. The difference between “nice demos” and measurable delivery outcomes is implementation: workflow design, quality gates, security controls, and adoption across teams.

What you will learn
  • Accelerate routine software delivery with AI code pairing to reduce time spent on repetitive engineering tasks and ship faster.
  • Embed AI safely into dev workflows with practical adoption patterns for Claude Code, including human-in-the-loop review, testing, and governance.
  • Reduce ramp-up time across teams so engineers become productive faster in unfamiliar systems, improving onboarding and cross-team mobility.
Agenda
  • Claude Code overview and AI code pairing in real dev workflows
  • AI Security overview for engineering teams: risks, controls, and governance patterns
  • Implementation playbook: rollout approach, quality gates, and scaling adoption
  • Key takeaways and optional Q&A
Who is it useful for?
  • Engineering leadership(CTO, VP Engineering, Head of Engineering, Tech Leads)
  • Security leadership(CISO, AI Security Officer, DevSecOps, Security Engineering)
  • Platform and architecture teams responsible for developer productivity and guardrails
  • Developers and product teams adopting AI-assisted delivery in 2026
Speaker

William Senn works across security and engineering as a CISO, AI Security Officer, Developer, and CAIO. He focuses on practical implementation: how teams adopt AI tooling in production workflows with the right controls, quality gates, and governance.

Live session • Optional Q&A Security and governance Practical implementation
Format
  • Duration: 45 minutes + optional Q&A
  • Location: Online (live)
  • Time: 09:00–10:00 a.m. CET (Zurich)
  • Language: English