TechLead Conf London 2025: Adopting AI in Orgs Edition

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AI-accelerated Legacy Modernisation

Our world runs on IT built in the 80s and 90s by engineers who are now retiring. This is becoming very worrying for corporates who have critical systems running on legacy code that only a handful of people still understand.

That's where GenAI arrives. With its almost magical transpilation abilities, it is the innovation that was needed to kickstart the legacy modernisations that had been postponed for too long.

Having worked on critical modernisations for more than 15 years, I jumped on the opportunity to experiment with how LLMs can accelerate complex migration projects.

I will share the concrete experience we have accumulated on a wide range of stacks (Swift->React-Native, Eclipse RCP -> Spring Boot, Java 1.6 Spring -> Java 21 Spring Boot, PHP ZF1 -> Symfony 7), cover both the good surprises and the limitations that we uncovered, and share our current playbook to best leverage AI when migrating a legacy system.

This talk has been presented at TechLead Conf London 2025: Adopting AI in Orgs Edition, check out the latest edition of this Tech Conference.

FAQ

Modernizing legacy IT systems presents challenges such as legacy ecology, reliability rupture, feature freeze, and migration mutiny. These include difficulty understanding outdated systems, fear of disrupting functional systems, halting new feature development, and lack of enthusiasm from legacy system teams.

Modernizing legacy IT systems is crucial due to the risks they pose, including business risks, security vulnerabilities, and compliance issues. These systems are outdated and can lead to significant financial losses, security breaches, and regulatory penalties.

AI accelerates the modernization process by handling complex coding tasks, improving system documentation, and facilitating better understanding of dependencies. It helps in breaking down legacy systems into manageable parts and supports efficient migration and updating processes.

While AI brings speed, it also introduces variance, which can lead to chaos if not properly managed. Ensuring quality and avoiding 'vibe coding' are essential to mitigate these risks and maintain system reliability.

Theodo applies AI through its Lean Tech approach, focusing on value for the customer, creating a tech-enabled network of teams, ensuring high-quality coding practices, and continuous improvement through Kaizen. This method aims to balance speed with system reliability.

Lean Tech is a system developed by Theodo that combines Lean Thinking with software engineering principles. It emphasizes customer value, modular team networks, high-quality coding, and continuous improvement to maintain agility and quality in system modernization.

Examples include Nike Capital's $440 million loss due to reactivating old code, Ukraine's power grid being remotely cut due to outdated systems, and Citigroup's repeated erroneous transfers leading to fines.

Theodo reduced a migration project timeline from an estimated 70 weeks to 21 weeks by utilizing AI to speed up code generation, improve system understanding, and streamline the migration process through Lean Tech principles.

future of development

Fabrice Bernhard

23 min

28 Nov, 2025

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Video Summary and Transcription

Discussing the importance of adopting AI in legacy modernizations and the risks associated with outdated systems, challenges in legacy ecology, reliability rupture, and migration mutiny. Exploring Lean Tech at Theodos for maintaining agility and customer value, improving system architecture through visualizing endpoints and high-quality coding. Optimizing accuracy with agent coders, industrializing migration with LeanTech principles for 10x acceleration. Leveraging AI for product building, AI model evaluation, and the preference for Claude over GPT in migration.

Available in Español: Modernización de Legado Acelerada por AI

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AI-accelerated Legacy Modernisation

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