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World Congress 2026 Europe • Jul 10, 2026 • Session details

The Last Mile of AI: From Prototype to Production

Clemens Wasner , Holger Hammel , Martin Remmelgas , Max Jacobson , Marius Cosareanu

Developers now spend 95% of their time reviewing AI-generated code rather than writing it. Learn how top engineering teams are overhauling testing to conquer AI’s chaotic last mile.

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#1 about 2 min

Company backgrounds and engineering organization scale

An overview of the panelist software products and their respective engineering team sizes.

#2 about 3 min

Personal and professional workflow changes from large language models

How coding agents and recent models have accelerated delivery and simplified information retrieval.

#3 about 4 min

Adapting team structures and agile workflows for agentic tools

Why organizations must reinvent workflows and adopt lean methods to leverage AI effectively.

#4 about 3 min

Blurring roles and cross-functional expectations in engineering pods

How AI tools blur traditional job boundaries and enable engineers to handle broader scopes of work.

#5 about 3 min

Reviewing and adapting machine-generated code in smaller teams

The shifting discipline of maintaining codebases when human reviewers evaluate non-human architectural models.

#6 about 1 min

Productivity amplification and technical debt risks with AI

How AI magnifies both the output of strong developers and the complexity introduced by weaker ones.

#7 about 3 min

Transitioning toward AI-first coding and managing token costs

The push to maximize coding agent usage while balancing the rising costs of frontier models.

#8 about 3 min

Balancing developer autonomy with the adoption of coding agents

Why mandating AI tool usage can frustrate engineers who value deep technical flow over managing unreliable agents.

#9 about 3 min

Creating reliable feedback loops and automated testing for AI

Applying mutation testing and deterministic checks to prevent agents from introducing unreviewed complexity.

#10 about 3 min

Implementing property-based randomized testing for generated code

Using continuous adversarial testing to align AI-generated logic with actual business invariants.

#11 about 5 min

Treating plain English specifications as the new compiler

Why comprehensive specifications and end-to-end testing are required to safely integrate black-box AI logic.

#12 about 2 min

Exploring progressive deployments and production monitoring

The potential for making highly granular iterative changes directly to production relying purely on monitoring.

Matching moments

1:55 min

Shifting developer workloads and realistic AI productivity gains

Chris Heilmann Chris Heilmann +2 · LIVE

2:52 min

Moving beyond demos to build production-ready software

Seth Webster Seth Webster · World Congress 2026 Europe

4:08 min

Transitioning software engineering teams to AI-native development workflows

Florian Deter Florian Deter +4 · World Congress 2026 Europe

3:33 min

Navigating developer bottlenecks and human accountability

Werner Vogels Werner Vogels +1 · World Congress 2026 Europe

2:20 min

Transitioning to AI-native engineering teams and workflows

Tomislav Tipurić Tomislav Tipurić +1 · World Congress 2026 North America

3:24 min

Shifting bottlenecks in AI-accelerated software delivery

Darko Mesaros Darko Mesaros +4 · World Congress 2026 North America

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