Demetrios Brinkmann talks with Siddharth Bidasaria about Anthropic’s Claude code — how it was built, key features like file tools and Spotify control, and the team’s lean, user-focused approach. They explore testing, subagents, and the future of agentic coding, plus how users are pushing its limits.

Building Claude Code: Origin, Story, Product Iterations, & What's Next

Deploying AI agents in enterprises is complex, balancing security, scalability, and usability. This post compares deployment paths on Google Cloud—highlighting Cloud Run with IAP as the most secure and flexible option—and shows how teams can build powerful agents with ADK without losing the human touch.

Deploying AI Agents in the Enterprise without Losing your Humanity using ADK and Google Cloud

How do fine-tuned models and RAG systems power personalized AI agents that learn, collaborate, and transform enterprise workflows? What kind of technical challenges do we need to first examine before this becomes real?

Fine-Tuned Models Are Getting Out of Hand

As AI agents become more capable, their real-world performance increasingly depends on how well they can coordinate tools.

This month's paper introduces a benchmark designed to rigorously test how AI agents handle multi-step tasks using the Model Context Protocol (MCP) — the emerging standard for tool integration.

​The authors present 101 carefully curated real-world queries, refined through iterative LLM rewriting and human review, that challenge models to coordinate multiple tools such as web search, file operations, mathematical reasoning, and data analysis.

Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queries

<h1>The Virtual AI Event That’s Actually... Fun</h1>We know what you’re thinking: another virtual conference. Another day of talking heads, awkward silences, and the constant urge to check your email. You’ve been there. You get distracted, you drop off, and you end up missing the one talk you needed. The truth is, most virtual events are a snooze-fest.That's not how we do it.<h3>100% AI Agents in Prod. BUT This Isn't Just Another Zoom Link.</h3>This is the 6th Annual Virtual Conference. We’re not just packing the day with the biggest minds building AI agents; we’re making sure you stay hooked from the first moment to the last.Last year, we saw folks start talking about agents. Companies stopped playing with them and started building real-world solutions. We got the best around to come talk about the challenges they had to overcome to get the new technology working.That's why we're doubling down on the progress, lessons, and breakthroughs that are truly shaping the future. Our theme is once again Agents in Production. You'll get cutting-edge, actionable insights that will move you from experimentation to legit deployment.<h2>30+ Talks on AI Agents. I Promise You Won’t Log Off Early</h2>We’ve engineered this high-energy virtual event to be FUN. Sitting still for hours is impossible, so we're building in the kind of spontaneous, engaging moments that make live events great:<ol><li data-list="bullet">Hilarious Skits: Short, professionally-produced, and funny skits woven between sessions to break up the talks and give your brain a laugh.</li><li data-list="bullet">Improvised Live Music: Our in-house musicians will spontaneously compose songs based on the session topics, turning a technical deep-dive into an unforgettable performance.</li><li data-list="bullet">High-Energy Engagement: You’ll be treated like a live audience member, not a muted participant.</li></ol>The most important piece of the event is the deep technical content that our presenters bring. But in the breaks, we make a fool of ourselves. It's a conference for your brain AND your attention span.<h2>What You'll Miss If You Stay Home</h2>If you're not with us on November 18th, you’ll be missing out on:<ol><li data-list="bullet">Real Stories from Real Practitioners</li><li data-list="bullet">The Hard-Won Lessons: Inspiring use cases and practical applications that tell you exactly how the leading companies are successfully deploying agentic AI.</li><li data-list="bullet">The Deep Dives: Hands-on technical workshops and talks from the voices defining the future of AI.</li><li data-list="bullet">The Connections: Global opportunities to collaborate, share, and grow within the ML community.</li></ol>This is your chance to get up to speed on the global AI scene, connect with innovators, and actually enjoy a virtual event.

Agents in Production - MLOps x Prosus

This month's paper: <h1><a href="https://arxiv.org/abs/2506.18203" rel="noopener noreferrer" target="_blank">Shrinking the Generation-Verification Gap with Weak Verifiers</a></h1> Language models are getting better at reasoning but their ability to verify their own outputs still lags behind. This paper tackles that challenge head-on by introducing Weaver, a framework that combines multiple weak verifiers into a single, stronger verifier without relying heavily on labeled data.Weaver uses weak supervision to estimate verifier reliability, normalize inconsistent outputs, and filter low-quality signals, resulting in a unified score that better reflects true response quality. In practice, this approach significantly boosts reasoning and math task performance rivaling models several times larger, such as achieving o3-mini-level accuracy using only Llama 3.3 70B as the generator. <h2>💡 Special Guest - Author of paper:</h2><h2>We’re thrilled to be joined by the Jon Saad-Falcon, Stanford PhD Candidate in Computer Science, to discuss the paper and take questions from the group.</h2> 📅 Date: November 20th🕚 Time: 11amET<h2>Speakers: <a href="https://www.linkedin.com/in/adamissimo/overlay/about-this-profile/" rel="noopener noreferrer" target="_blank">Adam Boaz Becker</a> - Founder, HeadOn. <a href="https://www.linkedin.com/in/anaanna417/overlay/about-this-profile/" rel="noopener noreferrer" target="_blank">Jimin (Anna) Yoon</a> - Tech Lead / Senior Software Engineer</h2><h2>Moderator <a href="https://www.linkedin.com/in/arthurcoleman/overlay/about-this-profile/" rel="noopener noreferrer" target="_blank">Arthur Coleman</a>: CEO, OnlineMatters Inc.</h2> Join the #reading-group channel in the MLOps Community Slack to connect before and after the session.

MLOps Reading Group Nov – Shrinking the Generation-Verification Gap with Weak Verifiers

AI Agent Builder Summit SF

<h1>AI Agents Are Already Working — Let’s Talk About It</h1>Agents are no longer just experiments. From e-commerce to customer support to analytics workflows, they’re quietly getting real work done in production.On July 17, join the MLOps Community for Part 2 of Agents in Production — a virtual event focused on the messy, practical side of building and deploying AI agents.What’s on deck?<ol><li data-list="bullet">Taming complexity: agent memory, behavior control, latency vs. response tradeoffs</li><li data-list="bullet">Stories from the field: How companies are actually using agents in live environments</li><li data-list="bullet">Tooling that works: routing, evaluation, UX, and cost performance in the wild</li></ol><h2>It’s free, it’s global, and it’s going to be packed. </h2>

Agents in Production 2025

Your AI shouldn’t just work in the demo. It should work in production.Join us for a high-impact, no-fluff Mini Summit focused on building AI applications that can withstand the real world — where APIs fail, users take days to respond, and servers crash without warning. Whether you’re deep into building with LLMs or just starting to explore how to operationalize your AI systems, this event is packed with practical insights, real-world strategies, and modern tooling to help you ship reliable AI that doesn’t break. What’s on the agenda?🔹 Process Calling: Agentic Tools Need State Function calling gave LLMs a way to "do" things — but it’s not enough. When you’re building agents for customer-facing use cases, stateless abstractions fall short fast. Learn why the future of agentic tooling is process-based, not function-based, and what it means to build agents that remember, recover, and reliably finish what they start. 🔹 Building Reliable AI Applications with Durable Workflows Chaining functions together is easy. Keeping AI workflows running when things go sideways? That’s the hard part. This talk introduces durable workflows — systems that checkpoint state, recover automatically, and gracefully handle everything from human delays to API flakiness. You’ll see real examples of AI pipelines that stay resilient in production. 🔹 No YAML? No Problem: Orchestrate Kubernetes Workflows the Easy Way with Python Sick of writing orchestration logic in YAML? You’re not alone. Discover how Hera, the Python SDK for Argo Workflows, lets you express complex Kubernetes workflows using clean, testable Python code. Keep your business logic and orchestration logic in one place — no indentation nightmares required. Who should attend? AI engineers, MLOps professionals, infra leads, and builders who care about more than just flashy demos. If you're looking to make your AI actually work at scale, this one's for you. RSVP now and start building AI that doesn’t break.

Building AI That Doesn’t Break

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