AI Engineering in 2026: Claude Code, Developer Productivity, and AI Security | dreamleap

Expert Briefing

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

19 March 2026 Online • 11:30–12:30 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 is an AI Engineer at dreamleap in Zurich, where he builds enterprise grade AI systems and agentic platforms powered by large language models. Previously, he developed NLP solutions for the State of Geneva and holds a Bachelor’s degree in Computer Technology from Geneva.

He is currently pursuing a Master’s in Artificial Intelligence at the University of Zurich, with a clear focus on one thing: bringing LLMs into real software engineering workflows in a way that is safe, efficient, and production ready. His work helps organisations move beyond pilots and deploy AI at scale with the right quality gates, governance, and measurable impact.

Format
  • Duration: 60 minutes (incl. Q&A)
  • Location: Online (live)
  • Time: 11:30–12:30 CET (Zurich)
  • Language: English