Join us for a free, single-day virtual (completely online) conference for engineers and builders who are shipping AI in production, not just experimenting with it. 11 curated talks covering agentic systems, production safety, evaluation frameworks, memory architectures, and real deployment lessons from practitioners who've done it.
How to Join
Step 1: Click the RSVP button on this event page to register (it's free).
Step 2: Visit the event page on July 18, where a "Join" button will appear when the event starts.
Step 3: Browse the tentative schedule at gdg-chapel-hill.github.io/applied-ai-conference-2026. (We recommend bookmarking it! It's more readable than the agenda below).
Agenda · Saturday, July 18, 2026 (All times EDT)
9:00 – 9:30 AM · I Don't Trust AI Agents (And Neither Should You): Building Production-Ready ArchitecturesDarko Mesaroš · Principal Developer Advocate @ AWS · Technical · 30 min
Your AI agent works great in the demo. Then you deploy it and it hallucinates a refund policy, exposes customer data, or just loops endlessly burning tokens. This session walks through a layered approach to agent safety using Amazon Bedrock AgentCore and the Strands Agents SDK: guardrails, observability, multi-agent safety patterns, and reference architectures you can adapt immediately.
9:45 – 10:15 AM · Shipping Safe AI Agents: A Production Safety Playbook from 2,500 DeploymentsLorenzo Satta Chiris · Director of Excode · Technical · 30 min
A condensed safety playbook drawn from 2,500 real deployments and co-authoring the AURA open-source agent risk framework. Three real failure modes: an agent that escalated its own permissions, a RAG pipeline that confidently cited fake policy docs, and multi-agent outputs that contradicted each other on a customer-facing response, with the root cause, the fix, and the monitoring signal that now catches each one early.
10:30 – 11:15 AM · From Vibes to Verified: Building an Autonomous Eval + Fix Engine for AI AgentsShashank Agarwal · Founder & CEO, Noveum.ai · Ex-AWS SageMaker (2nd Engineer) · Technical · 45 min
Gartner predicts 40% of agentic AI projects will be cancelled by 2027, mostly because teams are shipping on "vibes-based engineering." This session walks through an autonomous eval and remediation engine that runs 106+ scorers across 18 categories, and delivers fixes as actual merged pull requests, not suggestions. Real enterprise results: 200x faster time-to-fix, 4–6x performance improvement across 9 production deployments.
11:30 – 11:45 AM · AI Can Write Code. It Can't See the System.Eshwar Yaddanapudi · Creator of Fluent-Graph · Ex-EM, ServiceNow · ⚡ Lightning · 15 min
AI generates code fast, but it can't see how that code interacts with everything else. A single AI-assisted change can propagate failures through hidden dependencies undetected until after deployment. This lightning talk presents one idea: move dependency visibility to the point of change using system-level dependency graphs, shifting from reactive observability to pre-execution reasoning.
12:00 – 1:00 PM · 🍽 Lunch break
1:15 – 1:45 PM · When Agents Break: Designing Fault-Tolerant Multi-Agent Orchestration Beyond LangChainRavi Kiran Pagidi · Senior AI Data Engineer, Navy Federal Credit Union · Technical · 30 min
A five-agent LangChain system worked in staging and fell apart in production within the first week, with cascading breakdowns where one bad link silently poisoned the entire chain. This talk walks through the custom orchestration layer built on top of LangChain: agent-level circuit breakers, context validation on every handoff, fallback routing, and the monitoring dashboards that catch silent failures. Patterns applicable to LangChain, CrewAI, AutoGen, or custom stacks.
2:00 – 2:15 PM · Using Claude's web_search Tool to Track AI Citations: An Open-Source Python PatternIgnacio Lopez · Fractional Head of AI, Work-Smart.ai · Bilingual EN/ES · ⚡ Lightning · 15 min
"AI visibility" SaaS tools run $300–$500/month per site. This talk walks through a free MIT-licensed alternative built as four Python scripts, using Claude's web_search tool to ask buyer-intent questions and parse which domains get cited. Costs about $1–$3 per run via the Anthropic API. Includes the exact API call structure, parsing approach, and the five query patterns that surface real citation behavior.
2:30 – 3:00 PM · Agent Memory: Building Stateful AI Agents That Remember, Adapt, and Work Across TimeBen Labaschin · Principal AI/ML Engineer @ Workhelix · O'Reilly Author · Technical · 30 min
Most teams treat agent memory as a storage problem: add a vector database, keep more context, expect improvement. In production, the harder problem is what deserves to become memory, how to retrieve the right memory at the right time, and how to prevent old memories from quietly degrading the system. Drawing on lessons from production systems and a forthcoming O'Reilly book, this talk walks through the core design decisions: what to store, what to forget, how to scope retrieval, and how to maintain memory as it ages.
3:15 – 4:00 PM · UISurf: Toward Universal UI Automation with Cross-Environment AgentsHenry Ruiz · Research Scientist @ Texas A&M AgriLife Research · GDE in AI & Google Cloud · 🔧 Demo · 45 min
UISurf is an open-source multimodal agentic UI automation platform that enables AI agents to perceive, reason, and collaborate across browser and desktop environments to complete end-to-end tasks. The demo covers its multi-agent architecture: planning, browser, desktop, automation, and summarization agents coordinated through Agent-to-Agent (A2A) communication, supporting both fully autonomous and human-in-the-loop execution modes.
4:15 – 4:45 PM · 10x Engineering: Battle-Tested Lessons from Transforming Teams with GenAIDennis Nerush · Director of AI Engineering @ Elementor · Technical · 30 min
What happens when generative AI becomes the backbone of how an engineering team actually works? Over the past year, this team multiplied productivity, cut delivery times, and unlocked new collaborative workflows that spread across the company. Practical lessons and battle-tested insights: what worked brilliantly, what failed and why, and the cultural shifts needed to make GenAI a force multiplier rather than just another tool.
5:00 – 5:30 PM · From Prompts to Design-Driven Specs: Lessons in Taming AI ChaosSteve Fox · Founder, cleanapi.ai · Technical · 30 min
Spec-driven AI codegen promises the spec as the durable source of truth, but in practice the code drifts on every iteration until the spec becomes just documentation. This case study walks through three iterations of trying to make the spec actually durable: the constraint each iteration revealed, and the system that finally worked. Closes with a live demo. You'll leave with three principles earned the hard way.
5:45 – 6:15 PM · Spec-Driven Agent Development with ADK & AntigravityJitendra Gupta · Enterprise Architect, Cloud & AI @ EPAM Systems · 🔧 Demo · 30 min
A hands-on walkthrough of Spec-Driven Development (SDD) using Google's Agent Development Kit (ADK) and the Antigravity agent-first IDE. Move beyond prompt-based coding to a structured, artifact-first approach where specifications, plans, and tasks drive implementation, walking through the full SDD lifecycle: specify, clarify, plan, analyze, and implement.
Agenda
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Speakers
Darko Mesaroš - AWS (Principal Developer Advocate)
Lorenzo Satta Chiris - University of Exeter
Lorenzo Satta Chiris is a tech educator and entrepreneur passionate about making technology accessible to everyone. A current Global Excellence Engineering and Entrepreneurship scholar at the University of Exeter, Lorenzo directed Excode & ExeAI—the UK's largest student-led coding bootcamps—where he has taught code to over 900 attendees, earning Tech SouthWest Best Organisation and Finalis…
Shashank Agarwal - Noveum.ai (Founder & CEO, Noveum.ai — Ex-AWS SageMaker (2nd Engineer, Original Team))
Shashank Agarwal is the Founder & CEO of Noveum.ai, building the autonomous evaluation and remediation engine for AI agents. He was the 2nd engineer on the original AWS SageMaker team (2016-2018), building Hyperparameter Optimization before launch, and led ML initiatives at Amazon Prime Video generating $32M in revenue. Noveum.ai is the only company delivering autonomous AI agent fixes as …
Steve Fox - cleanapi.ai (Founder cleanapi.ai)
Steve Fox has been shipping production systems for three decades — neural-network R&D at NASA in the early '90s, CTO of an award-winning voice/chatbot startup in 2003, SaaS APM product leadership at Quest/Dell, and founding AutoScalr, an AWS Marketplace service that used ML to cost-optimize EC2 spot fleets. He's now founder of cleanapi.ai, focused on spec-driven, AI-assisted API generation…
Jitendra Gupta - EPAM Systems (Enterprise Architect - Cloud & AI)
Jitendra Gupta is 13 years experienced IT professional with expertise in GenAI, information security and cloud computing. As a sought-after speaker, with a proven track record of implementing GenAI & security best practices in cloud environments, Jitendra is dedicated to empowering fellow IT professionals with actionable takeaways to safeguard their applications, data and infrastructure on…
Eshwar Sowbhagya Prasad Yaddanapudi
Eshwar Prasad Yaddanapudi is a software engineer and creator of Fluent-Graph, an open-source observability tool for ServiceNow Fluent SDK projects. A former Engineering Manager at ServiceNow, he focuses on building systems that make AI-generated and declarative workflows more observable, traceable, and safe to deploy. His work sits at the intersection of platform engineering, AI systems, and d…
Ignacio Lopez
Ignacio Lopez is the founder of Work-Smart.ai, where he serves as Fractional Head of AI for mid-market companies in the United States and Latin America. He builds custom AI systems for businesses with $5M to $100M in revenue, organized around the AI Operating System framework.
Recent engagements include Capataz (private AI assistant for Argentina's largest construction group, 650 worker…
Ben Labaschin
Ben Labaschin is Principal AI/ML Engineer at Workhelix, where he works on production AI systems involving async LLM APIs, embeddings, and agent memory. He is the author of O’Reilly’s What Are AI Agents? and Managing Memory for AI Agents, and is writing the forthcoming O’Reilly book Agent Memory. Ben has spoken on practical agent and LLM engineering at MLOps Community, ODSC, and Wharton.
Dennis Nerush - Elementor (Director of AI Engineering)
Dennis Nerush is the Director of AI at Elementor, where he leads the company's AI strategy and guides teams through the integration of GenAI technologies that enhance productivity while preserving human creativity and accountability.
With over 15 years of experience as a developer, manager, director, and adviser across multiple tech companies and startups, Dennis has dedicated his caree…
Ravi Kiran Pagidi - Navy Federal Credit Union (Senior AI Data Engineer)
Ravi Kiran Pagidi is a Senior Data Engineer and AI/Data Systems Researcher with over 11 years of experience designing and delivering scalable data platforms, analytics ecosystems, and AI-enabled enterprise solutions. His expertise spans data engineering, big data, data analytics, machine learning, generative AI, agentic AI, and cloud-native data architectures. Across his career, he has focused…
Krishna Tirupati - Microsoft (AI Engineer | Azure Data & ML Architect | Agentic AI | Scalable Pipelines)
Krishna Tirupati is a Senior AI/Data Engineer at Microsoft with over 18 years of experience in building enterprise-scale data and AI systems. His expertise spans machine learning, large-scale data engineering, cloud-native architectures, and Azure platforms including Synapse, Fabric, and Azure ML.
He has led the design and deployment of production-grade AI pipelines for forecasting, ano…
Host
Aan Patel
Get to know me, visit https://aanpatel.tech !
Complete your event RSVP here: https://gdg.community.dev/events/details/google-gdg-chapel-hill-presents-applied-ai-conference-2026/.
