RevOps FM

Every time you explain your business to an AI from scratch, you’re repeating work. The opportunity with context engineering is to make your company’s expertise, processes, and past learning available whenever an agent needs them—so each new task builds on what you already know.In this episode, I’m joined by Jacob Dietle—a consultant focused on context engineering and AI collaboration—to explore company brains, shared knowledge, and how to give agents the information they need to do useful work.We discuss:What context engineering means in practiceWhen to move beyond individual ChatGPT projects to shared company contextHow existing knowledge bases fit into a company brainTurning customer conversations into insights agents can reuseUsing skills, version control, and source evidence to manage contextHow agents find information without loading everything at onceThe challenges of keeping context useful across teamsWhether you’re building AI workflows for yourself or helping your company adopt agents, this conversation explores the decisions involved in organizing knowledge, choosing tools, and starting with practical use cases.About Today's GuestJacob Dietle helps teams organize company knowledge and build systems for AI collaboration through Taste Systems.His work combines context engineering, knowledge management, and team enablement, with a focus on making company expertise usable across people and agents. In this conversation, he shares his approach to working with seed and Series A companies on AI for go-to-market.You can find him sharing his work on LinkedIn and his Substack, Speed to Insight.Key Topics[00:00] - Introduction and defining context engineering[03:30] - How business context changes AI outputs[05:15] - From individual AI projects to company brains[09:20] - Where existing knowledge bases fit[14:27] - Choosing where to start[17:12] - Turning customer calls into grounded insights[22:45] - Building useful skills without modeling the whole business[25:25] - Version control and preserving organizational learning[30:46] - Choosing tools and structures for your use case[33:06] - Progressive disclosure and how agents retrieve context[34:53] - File-based retrieval versus semantic search[39:44] - Managing context across teams[41:40] - Self-learning systems and human review[43:26] - Connecting with JacobResource LinksTaste SystemsContext OS QuickstartWhat even is context?Applied Context EngineeringLearn MoreVisit the RevOps FM Substack for our weekly newsletter: Newsletter

Justin and Lily reflect on their parallel journeys diving deep into AI throughout 2025. They discuss why most AI content misses the mark for operators and system builders working within corporate constraints, share lessons from building production AI tools, and explore what's next for bringing these capabilities into the enterprise.Guest: Lily Luo — Systems & Operations Leader, Author of Applied AI for MOps SubstackRead more of Justin's thoughts on AI Builders: The operator's roadmap for AI in 2026KEY TOPICSThe Gap in AI Content Most resources target researchers or GTM engineers focused on outbound automation. There's little guidance for operators dealing with cloud tools, security, and corporate complexity. That creates an opportunity to define best practices for this underserved audience.2025 Project Highlights Lily built an "Analysis Dossier" tool that generates full account research reports at the click of a button. Justin replaced a vendor intelligence tool with a custom system using Retool and a conversational agent.Lessons Learned Start with tightly scoped AI steps in linear workflows for reliability. Pre-process insights asynchronously rather than relying on real-time agent calculations. Match tools to use cases. Failures teach more than successes.Atlas: Lily's Autonomous Agent Runs on Google Cloud and wakes every 4 hours to research and progress projects. Uses a three-layer memory architecture: identity, temporal journal, and knowledge graph. Can push its own code and interact with other agents.2026 Outlook Focus on scalability, reduced hallucination, and team enablement. Build infrastructure that unlocks flexible, ad-hoc use cases. Bridge the gap between AI capabilities and enterprise readiness.The Human Side Working closely with AI changes how you think. Boundaries matter—don't let AI become a crutch.RESOURCESApplied AI for MOps — Lily's SubstackAI Builders Blog — Justin's SubstackTools mentioned: Claude Code, Gemini, ChatGPT, Zapier, Retool, Dust, Azure AI Foundry, Letta, VS CodeONE TIP FOR GETTING STARTEDPick a real pain point. Start with low-code tools you already know. Test relentlessly. Expect to fail—and learn from it.

SEO used to be the ultimate growth lever—offering massive “free” traffic to marketers who could outsmart the algorithm. But in 2025, it's a different game.In this episode, I’m joined by Gaetano DiNardi—an SEO strategist with deep experience across B2B SaaS—to unpack how AI is reshaping the search landscape.We discuss: The SEO playbook for 2025 How zero-click search is impacting real-world traffic Why brand is actually a competitive moat for SEO How to appear in AI search previews and LLM recommendations When a startup should consider SEO How to optimize content for the top, middle, and bottom of the funnelWhether you’re running SEO for an enterprise brand or figuring out your growth strategy as a founder, this conversation will help you recalibrate your approach to search in the age of AI.About Today's Guest Gaetano DiNardi is an SEO expert and principal consultant at Marketing Advice.He’s spent over a decade in B2B marketing, helping 50+ SaaS companies drive growth and demand. He’s battled in some of the most competitive trenches out there—categories like identity theft, business VoIP, employee monitoring, insider threat detection, LMS software, and more.You can find him sharing lessons from the field on LinkedIn and Substack.Key Topics[00:00] - Introduction[01:24] - Evolution of search over the past 10 years[04:09] - Impact of brand on rankings[05:36] - Did SEO degrade search quality?[11:30] - Impact of zero-click results[20:28] - How to get recommended in AI preview[34:15] - When should a startup focus on SEO?[41:39] - SEO for TOFU, MOFU, and BOFU Resource LinksMarketing AdviceMarketing Advice SubstackScrunch AI - Brand monitoring for AI searchWhat is Brand Authority and How Is It Calculated? - Moz Learn MoreVisit the RevOps FM Substack for our weekly newsletter: Newsletter

AI agents are everywhere in conversation right now—but what actually makes them work? It’s not just slapping a large language model into a workflow and calling it a day. Under the hood, real agentic systems operate differently. They make decisions. They adapt. They break out of rigid if-this-then-that logic and enter something closer to human judgment.In this episode, I talk with Daniel Vassilev, co-founder of Relevance AI, a platform purpose-built for building and deploying true agents. We dig deep into how agentic systems are structured—from core instructions to tool orchestration—and how that foundation changes what’s possible. Daniel explains the difference between automation and autonomy in clear, practical terms that any builder, founder, or operator can understand.We also explore real-world use cases: where agents shine today, where they fall short, and how teams are already using them to 10x output without ballooning headcount. Whether you’re dabbling in LLM workflows or ready to rethink how your company works entirely, this conversation will level up your mental model.If you’ve been wondering where the hype ends and the real architecture begins—this is the episode.About Today's Guest Daniel Vassilev is Co-Founder and Co-CEO of Relevance AI, a platform to develop commercial-grade multi-agent systems to power your business. With a background in software engineering, he previously created, grew and monetised two apps to a combined 7 million users, reaching #1 on the App Store top free.Key Topics[00:00] - Introduction[01:31] - Defining agentic AI[03:28] - AI in linear workflows vs. agentic systems[08:19] - How agents work under the hood[11:24] - Always-on agents[13:43] - Selecting the right tasks for agentic AI[17:42] - Copilot vs. Autopilot [22:44] - Are there tasks we should never delegate to AI? [25:03] - Coolest use cases[34:30] - Agent memory and continual improvement[37:55] - Compounding effect of agent teams[41:39] - Relevance the company and platformLearn MoreVisit the RevOps FM Substack for our weekly newsletter: Newsletter Disclosure: I am using an affiliate link for Relevance AI, which means I earn a small bonus if you sign up through my content.

Not many people make it to VP of Marketing Operations—Kimi Corrigan has done it twice. In this episode, she shares her journey from marketing coordinator to leading marketing ops at companies like Duo Security, Cisco, Wiz, Expel, and DataRobot. We dive into what it really takes to reach VP level, how to position yourself for leadership, and why marketing ops pros should start asking for that title.Kimi also gets real about the challenges of scaling teams, navigating internal politics, and balancing the tactical with the strategic. We talk about how marketing ops has evolved, the role of data and strategy, and why building strong cross-functional relationships is just as important as knowing your way around a tech stack.If you're a marketing ops pro wondering what’s next in your career—or how to level up—this one’s for you.About Today's Guest With over 19 years in marketing operations and leadership, Kimi Corrigan thrives on optimizing marketing strategies for efficiency and effectiveness.Kimi has held marketing ops leadershiop roles at Duo Security, Cisco, Wiz, Expel, and DataRobot.https://www.linkedin.com/in/kimicorrigan/Key Topics[00:53] - How Kimi got started in marketing operations[03:04] - Early-generation marketing automation[05:54] - How you know if MOPS is working well[10:11] - Navigating people and organizational problems[16:51] - Becoming a VP Marketing Ops[22:31] - Operations and strategy [33:47] - Composable stacks vs. suites[37:51] - MOPS team structure[39:50] - Planning cycleResource Links Learn MoreVisit the RevOps FM Substack for our weekly newsletter: Newsletter