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AI Coding Agents and How to Code Them
Wed, 23 April
AI agents are rapidly becoming a transformative force, automating routine tasks, streamlining mission-critical workflows, and enabling humans to focus on creative and strategic endeavors. These intelligent systems are poised to revolutionize industries, and their potential for improving everyday coding tasks is equally profound.
This session explores:
- The core principles of building AI coding agents, focusing on how they automate repetitive development tasks and enhance productivity.
- The architecture and technologies behind coding agents, including frameworks, APIs, and libraries commonly used in their creation.
- Real-world applications of AI coding agents, demonstrating how they assist with debugging, refactoring, code generation, and more.
Attendees will gain hands-on insights into coding their own AI agents, from selecting the right tools to designing systems that can interact effectively with developers and environments.
Key Takeaways:
- An understanding of how AI coding agents work and their impact on software development.
- Practical knowledge to start building AI coding agents, including tools, frameworks, and best practices.
- Insights into future trends and how AI coding agents will evolve to tackle complex challenges.
Target Audience: Designed for Developers, AI Practitioners, and Software Engineers looking to create or leverage AI coding agents. Tech Enthusiasts, Product Owners, and Innovation Leaders interested in the practical applications of AI in development will also find this session invaluable.
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About the speaker
Alex Shershebnev
Head of ML/DevOps
Alex is a seasoned Computer Vision and MLOps Engineer with over nine years of experience shaping the future of AI-driven software development. Currently, Alex leads the ML/DevOps team at Zencoder, where he leverages his extensive background in Software Engineering, ML and DevOps to deliver high-quality machine learning solutions. His work spans complex data pipelines, cloud infrastructure management (GCP, Kubernetes), and advanced ML/DevOps pipelines, ensuring scalability and efficiency. Before Zencoder, Alex played pivotal roles in numerous projects, including leading teams at Sanas, ivi and MTS AI. His technical expertise in machine learning, data science, and bioinformatics has led to impactful solutions across industries, ranging from bioinformatics at the University of Massachusetts to video analysis at ivi.ru and MTS AI. Alex has a proven track record of managing complex infrastructure that scales to hundreds of GPUs, enabling effective and easy use of cloud infrastructure for data scientists while driving down costs through cloud consolidation efforts and boosting productivity through the deployment of sophisticated AI models. In addition to his technical contributions, Alex has been instrumental in mentoring teams and fostering a culture of innovation and collaboration. His deep understanding of AI systems, from developing recommendation engines to cutting-edge computer vision algorithms to voice and NLP, positions him as a thought leader in the AI and ML space. Whether it’s speaking on the latest advancements in MLOps, sharing insights on AI-driven automation, or discussing the future of AI in the enterprise, Alex brings a wealth of knowledge, practical experience, and a passion for pushing the boundaries of what’s possible with AI.
