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

AI Won't Fix Your Engineering Culture

Julia Kordick

Developers spend 60% of their time battling infrastructure, not writing code. Throwing AI at a broken system won't fix your engineering culture, but rapidly accelerates your technical debt.

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#1 about 3 min

Defining engineering culture and natural software team behaviors

Engineering culture emerges from natural, unwritten rules concerning architecture decisions, failure handling, and knowledge sharing in daily team operations.

#2 about 2 min

The reality of cognitive load and non-coding engineering tasks

Modern enterprise environments burden engineers heavily with distributed systems, complex toolchains, and strict compliance demands.

#3 about 4 min

Addressing the gap between coding assistants and complex workflows

The transition to agentic AI introduces new challenges involving context token costs, security integrations, and unmanaged tool sprawl.

#4 about 2 min

Four core use cases for AI in software engineering

Effective generative AI implementation must span greenfield development, legacy brownfield projects, application modernization, and broad SDLC support.

#5 about 3 min

Securing AI agents against internal and external threat vectors

Operating AI at scale necessitates strict devsecops guardrails to prevent accidental secret exposure and defend against outside aggressors.

#6 about 2 min

Platform engineering as the foundation for scaling AI tools

Internal developer platforms provide the vital self-service interfaces, consistency guidelines, and structured measurement needed to govern an influx of AI tooling.

#7 about 1 min

Managing prompts and agent configurations through everything as code

AI configurations such as prompts, agent instructions, and access setups must be strictly maintained in source control alongside infrastructure.

#8 about 5 min

Measuring developer experience to eliminate rigid workflow friction

Integrating human-centric frameworks like SPACE and DORA helps organizations measure hidden bottlenecks and silent feedback voids that actively stall productivity.

#9 about 4 min

Fusing developer experience and platform engineering for agentic SDLC

Because AI algorithms amplify existing weaknesses, organizations need solid platform boundaries and optimized processes running before safely operating multi-agent systems.

#10 about 2 min

Industry data on high-performing AI software engineering organizations

Market research reveals that top-tier companies succeed with AI deployments by closely integrating tracked outcome metrics and human-centric workflows.

#11 about 2 min

Strategic next steps for implementing an agentic developer experience

Successful transformations require prioritizing functional end-to-end user journeys, establishing robust internal platform engineering, and championing empathetic change management strategies.

#12 about 2 min

Generating engineering impact through sandboxed multi-agent experimentation

Providing safe isolation environments lets engineers creatively deploy multi-agent patterns to solve complicated and tedious jobs like CI/CD framework migrations.

#13 about 1 min

Overcoming executive FOMO and driving meaningful process change

Senior engineering staff can guide C-level leadership toward better infrastructure decisions through transparent data measurement and forcing direct hands-on AI interaction.

Matching moments

4:08 min

Transitioning software engineering teams to AI-native development workflows

Florian Deter Florian Deter +4 · WWC Europe 2026

2:34 min

Balancing developer autonomy with the adoption of coding agents

Clemens Wasner Clemens Wasner +4 · WWC Europe 2026

3:33 min

Navigating developer bottlenecks and human accountability

Werner Vogels Werner Vogels +1 · WWC Europe 2026

1:21 min

Using artificial intelligence to reimagine developer experience

Alexander Trusheim Alexander Trusheim +1 · WWC 2025

1:57 min

Accelerating AI maturity and the evolution of engineering roles

Alejandro Saucedo Alejandro Saucedo · WWC 2025

5:30 min

Core engineering skills required in the era of AI

Chris Heilmann +2 · LIVE

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