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 practice
• When to move beyond individual ChatGPT projects to shared company context
• How existing knowledge bases fit into a company brain
• Turning customer conversations into insights agents can reuse
• Using skills, version control, and source evidence to manage context
• How agents find information without loading everything at once
• The challenges of keeping context useful across teams

Whether 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.

Jacob 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.

• [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 Jacob

• Taste Systems
• Context OS Quickstart
• What even is context?
• Applied Context Engineering

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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 Substack

Read more of Justin's thoughts on AI Builders: The operator's roadmap for AI in 2026

KEY TOPICS

The 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.

RESOURCES

1. Applied AI for MOps — Lily's Substack
2. AI Builders Blog — Justin's Substack
3. Tools mentioned: Claude Code, Gemini, ChatGPT, Zapier, Retool, Dust, Azure AI Foundry, Letta, VS Code

ONE TIP FOR GETTING STARTED

Pick 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 funnel

Whether 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.

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.

• [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

• Marketing Advice
• Marketing Advice Substack
• Scrunch AI - Brand monitoring for AI search
• What is Brand Authority and How Is It Calculated? - Moz

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