Thiago Cardoso is the Director of Data & AI at iFood and the architect behind iFood Pago's AI agent platform. This fintech system serves millions of restaurants across Brazil through WhatsApp and the iFood app. In this episode, he breaks down what it actually takes to ship agentic AI in production at scale.

The Control-vs-Magic Spectrum Building Agents

Sherwood Callaway is the founder of Sazabi (YC P26), the AI-native observability platform built for engineering teams who ship fast. He previously founded and exited a YC company — now he's back, betting that logs are all you need to replace Datadog.


Logs Are All You Need: Rethinking Observability with AI Agents

A walk-through of RePPIT, a five-step framework for shipping production code 2-3x faster with AI that is used by companies of all sizes, from seed-stage startups to public enterprises.

RePPIT: A Framework to Ship Production Code 2-3X Faster

Joe Maionchi (Co-founder & COO) and Rod Christensen (Co-founder & Chief Architect) of RocketRide join the MLOps Community to walk through AIDE — the AI Integrated Development Environment. RocketRide is an open-source AI pipeline platform that lets developers build, debug, and run production-grade agentic AI workflows directly from their IDE, with support for 13+ LLM providers, 8+ vector databases, and full multi-agent orchestration.

AI Is Fast. AI Projects Are Slow. Let's Fix That.

<p>Real-time ML use cases like personalization and risk decisioning come with a unique set of challenges: serving fresh feature values at low latency for inference, generating temporally consistent backfills for training, and building complex chains of on-demand, batch, and streaming transformations. In this roundtable, practitioners from Intuit, CreditKarma, Depop, and OpenAI will share how they use Zipline and the OSS Chronon project to solve these challenges and deploy real-time ML use cases in production.</p>

Building Real-Time ML Systems with Zipline + Chronon

<h1><em>Paper: </em><strong><em><a href="https://arxiv.org/abs/2605.05287" rel="noopener noreferrer" target="_blank">Securing the Agent: Vendor-Neutral, Multitenant Enterprise Retrieval and Tool Use</a></em></strong></h1><h1>Retrieval-Augmented Generation and agentic AI are increasingly common in enterprise deployments, but real enterprise environments introduce challenges largely absent from academic treatments and consumer-facing APIs: multiple tenants with heterogeneous data, strict access-control requirements, regulatory compliance, and cost pressures that demand shared infrastructure. </h1><h1><br></h1><h1>This paper identifies a fundamental problem underlying existing RAG architectures in these settings. Retrieval systems rank documents by relevance, not by authorization, so a query from one tenant can surface another tenant’s confidential data simply because it scores highest. The authors formalize this relevance-authorization gap alongside related shortcomings (tool-mediated disclosure, context accumulation across turns, client-side orchestration bypass) and introduce a layered isolation architecture combining policy-aware ingestion, retrieval-time gating, and shared inference, enforced through server-side orchestration. They validate it through an open-source implementation in OGX, a vendor-neutral OpenAI-compatible Responses API, showing empirically that ABAC gating eliminates cross-tenant leakage while introducing negligible overhead.</h1><h1><br></h1><h1>The discussion will be led by Francisco Javier Arceo, co-author of the paper, joined by co-hosts David DeStefano, Rohan Prasad, and Valdimar Eggertsson, and moderated by Arthur Coleman. They will walk through the problem, the architecture, and the benchmarks, dig into the open-source framework, and open up to a live audience Q&amp;A.​​​​​​​​​​​​​​​​</h1><h1><br></h1>

Securing the Agent: Vendor-Neutral, Multitenant Enterprise Retrieval and Tool Use

<p>Join us for Session 14 of the Coding Agents Lunch &amp; Learn, our weekly community series exploring the tools, workflows, frameworks, and real-world applications shaping the future of AI coding agents.</p><p>This week, we’re diving into what happens when agents move beyond demos and into production workflows.</p><p>We’ll kick things off with a behind-the-scenes case study from Port of Context, where CEO Patrick Kelly will unpack how their team built and evaluated a GTM agent using Goose X Code Mode. Expect a practical look into agent design, performance measurement, token usage, execution time, lessons learned, and what actually matters when evaluating autonomous systems in production. Patrick will also share how manually running this process inspired the creation of the Agent Voyager Project (AVP), an open public specification for agent observability.</p><p>We’ll also hear from Sahil Kathpal for a focused lightning talk on techniques and frameworks for running long autonomous agent sessions reliably, the kind of agent workflows that persist for 60–90 minutes and require robustness, persistence, and orchestration to succeed.</p><p>Whether you’re building coding agents, experimenting with autonomous workflows, or trying to understand what reliable agent systems look like in practice, this session is for you.</p>

Coding Agents Lunch & Learn - Session 14 From Agent Demos to Production Reality

<p><strong>This week’s Coding Agents Lunch &amp; Learn will feature a deep dive into collaborative agent workflows, orchestration, and AI-native development environments.</strong></p><p><br></p><p>Agor creator Max will demo Agor, a collaborative workspace designed to coordinate coding agents across branches, sessions, environments, reviews, and team workflows. The session will explore how agent work, often invisible and fragmented, can become visible, collaborative, and easier to manage through shared workspaces.</p><p><br></p><p>We’ll walk through practical workflows including spawning agents, tracking progress, forking sessions, comparing approaches, reviewing outputs, and coordinating work across teams in a way that keeps humans meaningfully in the loop.</p><p><br></p><p>Beyond the demo, Max will share lessons from real-world experimentation around agent orchestration, runtime environments, context and memory management, automation workflows, and how teams are thinking about coding agents beyond traditional software development.</p><p><br></p><p>As always, this will be an interactive, discussion-driven session designed for engineers, founders, researchers, and practitioners exploring the future of coding agents and AI-native workflows.</p><p>Featuring Special Guest Max ( The Creator of Agor ) - showcasing <a href="https://agor.live/?utm_source" rel="noopener noreferrer" target="_blank">Agor</a> and practical lessons in coding agent orchestration.</p><p><br></p>

Coding Agents Lunch & Learn Session 13 - Collaborative Coding Agents, Workflows & Community Show-and

<p>As AI systems evolve into more autonomous, agent-driven architectures, the way we design platforms, tools, and infrastructure is rapidly changing. In this session with BuzzHPC, we’ll explore the shifting boundary between platforms and tools, what developers expect platform providers to handle versus what they want to control and build themselves. </p><p><br></p><p>We’ll unpack what modern agentic stacks look like today, how teams are structuring them in production, and where these architectures are heading as systems become more complex and distributed. A key focus will also be on agent interoperability, how different agents communicate, coordinate, and operate within shared environments.</p><p><br></p><p>Finally, we’ll share insights and lessons from a recent AI hackathon delivered in partnership with Bell, Buzz, Mila, and KHP, highlighting how these concepts are being tested and applied by builders in real-world scenarios.</p>

Architecting Modern AI Systems: Platforms, Agents, and Integration

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