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World Congress 2026 Europe • Jul 9, 2026 • Session details

The AI-Native Engineering Org: What’s Real, What’s Hype, What’s Next

Taroon Mandhana , Sebastian Kister

AI accelerates coding, but what happens when autonomous agents confidently build the wrong thing? Discover why alignment is the new bottleneck in AI-native engineering.

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#1 about 4 min

Shifting bottlenecks from code generation to team alignment

AI accelerates the entire development loop, making the speed and quality of decision making the primary bottleneck.

#2 about 1 min

Emphasizing clarity and alignment left of code

Strong alignment on the exact user problem to solve becomes crucial during the initial decision phase.

#3 about 4 min

Accelerating right of code workflows with AI agents

AI speeds up code reviews, deployment, and incident management to keep pace with increased code volume.

#4 about 4 min

Managing context and complexity in large brownfield enterprises

Centralizing organizational history and dependencies into a semantic layer gives agents the context needed to function effectively.

#5 about 2 min

Orchestrating collaborative workflows between humans and agents

Integrating agents as first-class team members requires systems of record that route tasks based on capabilities and cost.

#6 about 6 min

Establishing accountability and identity for system agents

Maintaining security and compliance at scale demands that AI agents operate with explicit identities tied to human oversight.

#7 about 4 min

Shifting skill requirements for entry-level software engineers

New engineers must act as product-minded generalists with high learning agility to effectively orchestrate multiple AI agents.

#8 about 4 min

Empowering cross-functional teams to prototype and ship software

Designers and product managers can leverage agents to build high-fidelity working prototypes and resolve immediate user experience issues.

#9 about 2 min

Building contextual layers with an organizational teamwork graph

Investing in a shared organizational brain improves agent outputs and optimizes token consumption across various developer tools.

Matching moments

2:20 min

Transitioning to AI-native engineering teams and workflows

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

4:08 min

Transitioning software engineering teams to AI-native development workflows

Florian Deter Florian Deter +4 · World Congress 2026 Europe

1:55 min

Shifting developer workloads and realistic AI productivity gains

Chris Heilmann Chris Heilmann +2 · LIVE

2:34 min

Balancing developer autonomy with the adoption of coding agents

Clemens Wasner Clemens Wasner +4 · World Congress 2026 Europe

2:12 min

The impact of AI agents on software engineering

General Program · World Congress 2026 Europe

1:35 min

Introduction to agentic AI engineering and code scanning

Isaac Evans Isaac Evans · World Congress 2026 North America

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