Chairpersons welcome and opening remarks<\/p>\n
With AI copilots, code generators, and self-healing systems, developers are no longer working alone<\/em>. This panel explores the new dynamic between humans and AI in software creation\u2014how to best collaborate, what skills remain uniquely human, and how AI can augment creativity rather than replace it.<\/p>\n As AI continues to reshape the technology landscape, the role of the developer is evolving rapidly. This panel brings together experts from across the industry to discuss the tools, skills, and mindsets that will define the next generation of AI developers. Topics include emerging frameworks, MLOps integration, prompt engineering, ethical AI practices, and the growing importance of cross-disciplinary knowledge. Panelists will share insights on how organizations can nurture talent, foster continuous learning, and prepare teams to thrive in an era where human creativity and AI collaboration drive innovation.<\/p>\n This session is tailored for AI developers looking to move models beyond prototypes and notebooks into robust production systems. It focuses on engineering best practices for deploying, scaling, monitoring, and maintaining AI solutions, including data pipelines, model versioning, CI\/CD for ML, performance monitoring, and handling drift. Attendees will gain practical guidance on building reliable, secure, and maintainable AI systems that deliver real business value in production environments.<\/p>\n Low\u2011code and no\u2011code platforms are lowering barriers to AI innovation\u2014but how can developers leverage them without compromising scale or performance? This talk examines how visual workflows and pre\u2011built components accelerate development while maintaining governance, security, and enterprise\u2011grade quality.<\/p>\n As generative AI moves from experimentation to large-scale deployment, organizations face new challenges around performance, efficiency, and responsible use. This session explores practical techniques for optimizing generative AI models for production environments\u2014covering topics such as model fine-tuning, inference acceleration, cost-efficient scaling, and latency reduction. The presentation also addresses safety and governance considerations, including content filtering, bias mitigation, and human-in-the-loop validation. Attendees will learn how to balance innovation with reliability to deliver secure, high-performing generative AI applications in real-world settings.<\/p>\n Deploying AI at enterprise scale presents unique challenges, from infrastructure and data management to collaboration and governance. This panel brings together seasoned AI practitioners to share practical lessons on building scalable, maintainable, and high-performing AI systems. Discussions will cover strategies for effective MLOps, cross-team integration, performance optimization, and navigating organizational barriers. Attendees will gain actionable insights on how to move from pilot projects to enterprise-wide AI adoption while minimizing risk and maximizing impact.<\/p>\n This presentation demystifies the EU AI Act for start-up founders and teams, cutting through regulatory complexity to deliver actionable insights.<\/p>\n The session begins with a clear breakdown of what the legislation actually requires, covering the four-tiered risk categorisation system and the specific obligations for each category.<\/p>\n A critical timeline reality check addresses the August 2026 enforcement deadline and the phased implementation approach, helping start-ups understand exactly when different requirements take effect. The presentation then focuses specifically on start-up implications, identifying which companies are affected regardless of their location, and dispelling common misconceptions about scope and applicability.<\/p>\n The final section provides a practical compliance requirements breakdown, translating abstract regulatory language into concrete documentation and process requirements that start-ups can implement. Attendees will leave with clarity on whether their AI systems fall under the Act’s scope and a roadmap for building compliance into their development workflows rather than treating it as an afterthought.<\/p>\n Designed for founders, CTOs, and product teams who need to understand regulatory impact without getting lost in legal complexity, this session transforms AI Act compliance from an overwhelming challenge into a manageable competitive advantage.<\/p>\n The Reality Gap: Solutions that look simple on paper or video often fail to work in a real enterprise RAG- Strict Knowledge Boundaries: Restricting AI answers solely to internal company data.<\/p>\n AI AGENT- Production-Ready Text-to-SQL: Refining natural language queries to work reliably on live, messy databases.<\/p>\n AI AGENT- Format-Preserving Translation: Delivering high-fidelity translations without losing document layout.<\/p>\n Chairpersons welcome and opening remarks.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Panel: Beyond the Prototype: Why Most AI Applications Never Reach Production","slot_type":"Entry","slot_day":"Same","slot_time":"9:40 - 10:20","slot_alternative_track_type":"","slot_text":" Everyone has an AI proof of concept. Far fewer have AI systems serving millions of requests reliably in production. Engineering leaders discuss what happens after the demo, from LLMOps and infrastructure to observability, developer experience and operational resilience, and the architectural decisions that separate successful AI products from abandoned experiments.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Fireside: Why the Hardest Problems Begin After the Model Works ","slot_type":"Entry","slot_day":"Same","slot_time":"10:25 - 10:55","slot_alternative_track_type":"","slot_text":" Getting an LLM to answer a question is easy. Building an AI application that remains reliable, observable and maintainable at scale is not. This discussion explores orchestration, evaluation, context engineering,\u00a0memory\u00a0and platform design, and why production AI is becoming an engineering\u00a0discipline in its own right.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: Production-Ready Generative AI: Techniques for Optimisation and Safety ","slot_type":"Entry","slot_day":"Same","slot_time":"11:00 - 11:20","slot_alternative_track_type":"","slot_text":" Moving generative AI from experimentation to production requires more than powerful models. This session explores practical techniques for optimising performance, managing costs and latency, and building safety and reliability into production-ready GenAI systems. Discover approaches to evaluation, monitoring, guardrails and deployment that help organisations scale generative AI with confidence.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Networking Break","slot_type":"Break","slot_day":"Same","slot_time":"11:20 - 11:40","slot_alternative_track_type":"","slot_text":" This session is tailored for AI developers looking to move models beyond prototypes and notebooks into robust production systems. It focuses on engineering best practices for deploying, scaling, monitoring, and maintaining AI solutions, including data pipelines, model versioning, CI\/CD for ML, performance monitoring, and handling drift. Attendees will gain practical guidance on building reliable, secure, and maintainable AI systems that deliver real business value in production environments.<\/p>\n","slot_speakers":[{"ID":49907,"post_author":"3334","post_date":"2025-11-19 16:39:35","post_date_gmt":"2025-11-19 16:39:35","post_content":"\n I am an Engineering Lead at Lloyds Banking Group within the Public Cloud Platform, where I focus on building enterprise-ready infrastructure that underpins the bank\u2019s analytics and AI transformation. My work centres on leveraging Agentic AI to reimagine the end-to-end engineering lifecycle - driving new levels of automation, intelligence and efficiency across how we build, deliver\u00a0and scale products.<\/p>\n","post_title":"Parinita Kothari","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"parinita-kothari","to_ping":"","pinged":"","post_modified":"2025-12-23 12:08:11","post_modified_gmt":"2025-12-23 12:08:11","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.ai-expo.net\/global\/?post_type=speaker&p=49907","menu_order":77,"post_type":"speaker","post_mime_type":"","comment_count":"0","filter":"raw"}],"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: Evaluating AI Before Your Customers Do","slot_type":"Entry","slot_day":"Same","slot_time":"11:40 - 12:10","slot_alternative_track_type":"","slot_text":" Traditional software testing wasn’t designed for probabilistic systems. Learn how engineering teams are building evaluation pipelines, automated benchmarks and observability frameworks that detect regressions before users experience them to ensure quality and business performance.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: Context Engineering - The Hidden Layer Behind Reliable AI Applications","slot_type":"Entry","slot_day":"Same","slot_time":"12:15 - 12:45","slot_alternative_track_type":"","slot_text":" As foundation models become increasingly capable, competitive advantage is shifting away from model selection and towards how applications manage context. This session explores the engineering patterns behind reliable AI systems, including context windows, retrieval strategies, memory, tool use and prompt orchestration. Learn how engineering teams are designing context pipelines that improve accuracy, reduce hallucinations and create more predictable AI behaviour in production.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Lunch Break","slot_type":"Break","slot_day":"Same","slot_time":"12:45 - 13:45","slot_alternative_track_type":"","slot_text":" As generative AI moves from experimentation to large-scale deployment, organizations face new challenges around performance, efficiency, and responsible use. This session explores practical techniques for optimizing generative AI models for production environments\u2014covering topics such as model fine-tuning, inference acceleration, cost-efficient scaling, and latency reduction. The presentation also addresses safety and governance considerations, including content filtering, bias mitigation, and human-in-the-loop validation. Attendees will learn how to balance innovation with reliability to deliver secure, high-performing generative AI applications in real-world settings.<\/p>\n","slot_speakers":[{"ID":49887,"post_author":"3334","post_date":"2025-11-19 15:58:54","post_date_gmt":"2025-11-19 15:58:54","post_content":"\n Isaac Bakare is a technology and security engineer with over 20 years of hands-on experience across embedded systems, software engineering, and artificial intelligence. Beginning his career as a teenage mobile phone repair entrepreneur, he has since delivered high-impact solutions in fintech, legal-tech, power-tech, and brokerage environments\u2014driving operational efficiency and business expansion across multiple continents. He has led engineering teams, co-founded a startup as CTO, and architected scalable enterprise platforms, including the transition of core systems to modern multi-tenant architectures. Today, he works in financial services, building secure, intelligent, AI-powered systems and advancing the integration of security into autonomous technologies.<\/p>\n","post_title":"Isaac Bakare","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"isaac-bakare","to_ping":"","pinged":"","post_modified":"2025-12-23 12:01:38","post_modified_gmt":"2025-12-23 12:01:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.ai-expo.net\/global\/?post_type=speaker&p=49887","menu_order":113,"post_type":"speaker","post_mime_type":"","comment_count":"0","filter":"raw"}],"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Panel: Engineering Reliable AI Agents at Scale","slot_type":"Entry","slot_day":"Same","slot_time":"13:45 - 14:25","slot_alternative_track_type":"","slot_text":" AI agents are moving rapidly from experimentation into enterprise applications, but reliability remains the biggest engineering challenge. Engineering leaders discuss planning, orchestration, tool use, memory and failure recovery to build dependable AI agents<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: Engineering AI Platforms for Enterprise Velocity ","slot_type":"Entry","slot_day":"Same","slot_time":"14:30 - 15:00","slot_alternative_track_type":"","slot_text":" As AI adoption accelerates, the real competitive advantage lies in platform thinking. In this session, Kapil Poreddy discusses how modern AI platforms empower developers to build, deploy, and iterate faster while maintaining governance and reliability at scale. Drawing from experience at Walmart Global Tech, this presentation covers reusable AI infrastructure, internal developer platforms, LLM integration strategies, observability for AI workloads, and balancing innovation with enterprise controls. Attendees will gain actionable insights on building AI ecosystems that enable teams – not just models – to scale.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: Building AI Platforms Developers Actually Want to Use","slot_type":"Entry","slot_day":"Same","slot_time":"15:05 - 15:25","slot_alternative_track_type":"","slot_text":" Successful AI programmes depend on more than powerful models \u2013 they require internal platforms that enable developers to experiment, deploy and operate AI safely and efficiently. This session explores the principles behind effective AI platform engineering, covering APIs, reusable components, governance, developer experience and self-service infrastructure that accelerate AI delivery across engineering teams.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: Building AI Platforms Developers Actually Want to Use","slot_type":"Entry","slot_day":"Same","slot_time":"15:30 - 15:50","slot_alternative_track_type":"","slot_text":" Successful AI programmes depend on more than powerful models – they require internal platforms that enable developers to experiment, deploy and operate AI safely and efficiently. This session explores the principles behind effective AI platform engineering, covering APIs, reusable components, governance, developer experience and self-service infrastructure that accelerate AI delivery across engineering teams.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Chairperson's Closing Remarks","slot_type":"Entry","slot_day":"Same","slot_time":"16:05","slot_alternative_track_type":"","slot_text":"","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true}]},"yoast_head":"\n10:35 – 11:05<\/h2>\n
Networking Break<\/h2>\n
11:05 – 11:45<\/h2>\n
Panel: Building the AI Developer of Tomorrow: Tools, Skills & Insights <\/h2>\n
11:50 – 12:20<\/h2>\n
Presentation: How to take AI usecases into production <\/h2>\n
12:20 – 13:40<\/h2>\n
Lunch Break<\/h2>\n
13:40 – 14:00<\/h2>\n
Presentation: Democratising AI Dev: Low\u2011Code\/No\u2011Code Strategies Without Sacrificing Quality<\/h2>\n
14:05 – 14:35<\/h2>\n
Presentation: Production-Ready Generative AI: Techniques for Optimization and Safety <\/h2>\n
14:40 – 15:20<\/h2>\n
Panel: Scaling AI Across the Enterprise: Practical Lessons for Developers <\/h2>\n
15:25 – 15:35<\/h2>\n
Presentation: EU AI Act Decoded: What Every AI Start-up Must Know Before August 2026 <\/h2>\n
15:40 – 15:50<\/h2>\n
Presentation: Building an Enterprise AI Platform: From Theory to Reality <\/h2>\n
Here are a few of the challenges we came across and how we solved them.<\/p>\n15:50<\/h2>\n
Chairperson’s Closing Remarks<\/h2>\n","protected":false},"featured_media":0,"template":"","meta":{"_acf_changed":false},"class_list":["post-48936","agenda","type-agenda","status-publish","hentry"],"acf":{"day":"2","event":["AI"],"region":"Global","track_type":"Free Track","time_slot":[{"slot_heading":"AI Developer Day: From Prototype to Production","slot_type":"Title and Track Sponsor","slot_day":"Same","slot_time":"","slot_alternative_track_type":"","slot_text":"","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Chairperson\u2019s Opening Remarks","slot_type":"Entry","slot_day":"Same","slot_time":"9:30 - 9:40 ","slot_alternative_track_type":"","slot_text":"