2026-04-14 –, Merck Plenary (Spectrum) [1st Floor]
Software engineering is changing fast. With AI now writing and reasoning about code, does it still make sense to learn Python or any language at all?
Is this the evolution of our craft, a true revolution, or just hype from those who benefit most? Join us to debate the future of Python, the risks of AI-driven development, and what skills will actually matter next.
Software engineering is at a crossroads. With AI systems now capable of generating, debugging, and even reasoning about code, the very definition of programming is being challenged.
Does it still make sense to invest years learning Python, or any programming language, if machines can translate natural language specifications into working software? Are we witnessing the evolution of coding into a higher-level craft, the revolution of the software industry, or merely an illusion fueled by hype from those who benefit most?
This panel moderated by Sebastian Neubauer will confront these questions head-on. We will debate whether programming languages remain essential, whether software engineers are at risk of obsolescence, or whether the demand for engineers may actually explode in ways we cannot yet imagine. We will also explore the risks of over-reliance on AI, including potential security vulnerabilities, fragile or unexplainable systems, and the loss of deep understanding of the software we build.
Come prepared for uncomfortable questions, bold predictions, and no easy answers. This is a session designed to challenge assumptions, spark debate, and imagine the possible futures of Python and software engineering in an AI-assisted world.
Note: Join our interactive workshop to explore the future of Python and AI-assisted coding on Wednesday . Everyone is welcome to share ideas, debate risks, the future of Python and help shape what software engineering could look like in the age of AI.
Data scientist forever; Worked everywhere in Blue Yonder, messed with data science, built platforms, now exploring GenAI & AI agents. Known to always ask the question nobody else dared.
Markus Klein is a Founding Engineer at Supermetal. He maintains open-source projects including the odbc2parquet command-line tool and the arrow-odbc Python wheels. Throughout his career, in both management and individual contributor roles, he has advocated for Continuous Delivery, Test-Driven Development, and Mob Programming. Sometimes successfully. He still finds it strange to write about himself in the third person.
I started as a data scientist, building ML microservices and deploying models into production. I later moved into a consulting role, where I helped adapt ML models to real customer needs, translate business problems into measurable objectives, interpret results, and monitor model performance over time.
Over the years, my work gradually shifted towards GenAI. I now design and build AI agents from scratch for internal process optimisation, support colleagues in adopting GenAI and agentic AI responsibly, and promote security-aware practices in solution development. A large part of my work focuses on evaluating and monitoring agent behaviour in real environments to ensure these systems remain useful, safe, and trustworthy after deployment.
Serhii Sokolenko is a co-founder of Tower, a Pythonic platform for data flows and agents running on top of open analytical storage. Prior to founding Tower, Serhii worked at Databricks, Snowflake and Google on data processing and databases.