1. Introduction
In this episode of Impact of AI: Explored, we (James O’Regan and Gerjon Kunst) sat down with Citrix’s Dave Brear to talk about something that sits right at the intersection of productivity, AI, and knowledge work: the AI-powered second brain.
What started as a conversation about note‑taking and personal knowledge management quickly turned into a deep dive on how to use AI as a genuine thinking partner, how to avoid “AI slop,” and what all of this might mean for the future of enterprise IT and EUC.
2. Meet the Guest
Dave Brear is a Technology Strategist at Citrix, working closely with enterprise customers to ensure they get real value from their Citrix investments rather than just licenses on an invoice. He’s a classic knowledge worker: his output is a mix of emails, documents, meetings, and strategy – nothing you can literally put on a pallet.
Outside of his day job, Dave has become known for his hands‑on exploration of AI and augmented cognition. He publishes regularly at davebrear.ai, where he shares how he built his own AI‑powered second brain using Obsidian, markdown notes, and modern LLMs, and how others can follow the same path. His public “vault” is even available as an MCP connector and GitHub repo for people who want to experiment with his system as a starting point.
In other words: Dave doesn’t just talk about AI and second brains – he’s actually running his day‑to‑day work through one.
3. Setting the Stage
We’re living in a world where AI can generate endless content on demand, from emails and blog posts to slide decks and code. That’s powerful, but it also introduces a real risk: a flood of generic, low‑nutritional “AI slop” that looks like content, but doesn’t actually say anything.
In this environment, questions of trust, authorship, and thinking become critical. Does it matter that the thinking behind something was truly ours? How do we preserve our own “chain of cognition” when working with AI tools? And how can we make AI amplify our real expertise instead of replacing our voice with bland averages?
This episode is for anyone who feels like they’re drowning in information and tools – and wants a practical way to build an AI‑augmented system that actually matches how their brain works, rather than yet another shiny app they abandon after two months.
4. Episode Highlights
Highlight 1 – Chain of cognition vs. AI slop
Early in the conversation, Dave set the tone with a simple but powerful idea: what makes content valuable is not whether a human or an AI typed the final words, but whether there’s a real chain of cognition behind it. For him, “AI slop” is content that has no nutritional value – it’s “meaning-shaped” text with no ideas you can stand behind. A great post (human or AI assisted) has a story, a clear premise, a point it wants to land, and a journey that gets you there.
Highlight 2 – From failed note‑taking systems to a living second brain
Dave walked us through his long history with note‑taking systems – OneNote, Evernote, Notion, physical notebooks, bullet journaling – and how he would always start with enthusiasm, then fall off the wagon after a few months. The breakthrough came when he read How to Take Smart Notes and adopted the Zettelkasten approach: atomic notes (one idea per note), written in his own words, linked together in a network. Combined with Obsidian and markdown, this evolved into a long‑lived, AI‑augmented second brain that he still uses daily in 2026.
5. Deep Dive: The AI Second Brain and Chain of Cognition
At the heart of this episode is Dave’s idea of the second brain as a thinking system, not just a storage system. The second brain starts with classic Zettelkasten principles:
- Capture ideas as small, atomic notes, each containing a single thought in your own language.
- Store them in a simple, durable format (markdown files in Obsidian).
- Link notes together based on relationships: “this reinforces that”, “this contradicts that”, “this follows from that”, forming a network of thought rather than a static archive.
On top of this structure, Dave layered AI. Initially, his attempts to use AI were underwhelming – the classic “write this email for me” workflows that produce something mediocre he then had to rewrite anyway. The turning point came when he stopped using AI as a compression tool and started using it for expansion and reflection.
Instead of “write an email to this customer,” he started with rich context: the customer’s background, stakeholders, politics, motivations, desired outcome, likely objections, and his own intent. He then asked AI to help shape these into a carefully balanced email. Crucially, the intelligence came from his context and thinking; the AI helped him walk the tightrope.
When more capable models arrived, Dave connected them directly to his Obsidian vault. Suddenly, the AI had access to hundreds of his notes: his ideas, reflections, and previous reasoning. That’s when his second brain truly “came alive”: instead of starting each chat with a blank slate, he could bring the full weight of his past thinking into the conversation.
“Chain of cognition” is his way of keeping this honest. It’s not about who typed the final sentence, but whether he can trace the ideas back to his own experience, reasoning, and notes. The second brain becomes a way to externalize and extend that chain – not outsource it.
6. Real-Life Stories & Examples
One story that really illustrates how Dave works with his second brain is the email to a customer in a contentious situation. He needed to address sensitive issues with multiple stakeholders, each with different motivations and political angles. Instead of dashing off an email or asking a colleague for a quick review, he opened a chat window and poured in everything he knew: stakeholders, their roles, the history, the desired end state, and what he wanted people to feel and do after reading the email.
The AI helped him craft a message that walked the line perfectly. When he sent it, the feedback from both the customer and internal colleagues was that it was exactly what was needed. But importantly, this wasn’t “AI writing the email”; it was Dave’s thinking, expanded and surfaced via AI with guardrails. In his words, it was more like a performance that needed to be choreographed carefully – and AI was a backstage coach, not a stunt double.
Another example is how he dealt with the “too much context” problem once he connected his vault. With hundreds of markdown files, simply dumping everything into an AI context window was like a snake swallowing a goat: technically possible, but not healthy. So he used AI to help him design tools that index metadata, traverse wiki links, and selectively load only the relevant notes for a given question. If he’s exploring a particular idea, he can start from one note and let the system follow the chain of related notes, pulling in just what’s needed.
These stories show the pattern: he uses AI inside his second brain, not as a separate toy. Real work, real stakes, real constraints.
7. Key Takeaways
- AI slop vs. real thinking: The problem isn’t AI itself, it’s content with no chain of cognition behind it. Ground your work in your own lived experience and reasoning.
- Second brain as a thinking system: A good second brain is more than storage. Atomic notes, your own words, and rich links turn it into a genuine thinking partner over time.
- Use AI for expansion, not just compression: Dumping “write this for me” prompts into an LLM often disappoints. Start with your full context and let AI help you explore, challenge, and refine.
- Context is the new user profile: In enterprise and EUC, your vault – your layered context – is becoming more important than the device or session you’re on.
- Keep brains separate, but connected: Dave and Brian Madden don’t merge their vaults. Instead, they expose public versions and talk to each other’s “agents” when they need another perspective.
- Ownership and risk are real questions: If you build your second brain inside corporate walls, who owns it? Could it be used to replace you? Encryption, separation of personal and corporate layers, and policy will matter.
- Start simple and personal: Don’t copy someone else’s elaborate system. Start with a blank folder, let AI interview you, and build a workflow that matches how you think.
8. Closing Thoughts
Recording this episode with Dave left both of us rethinking how we work with AI day to day. It’s easy to get distracted by tools and features, but the real leverage comes from designing a system where your own thinking compounds over time – with AI as a partner, not a puppeteer.
If this resonates with you, consider the episode your invitation to start – or reboot – your own second brain. Read a book like How to Take Smart Notes, spin up a simple markdown‑based vault, point your favorite AI at it, and begin with one real problem you need to solve this week.
We’d love to hear how you’re approaching this. Are you already experimenting with an AI‑powered second brain, or are you still at the “I created a folder and that’s it” stage? Drop us a comment, share your setup, and let’s keep this conversation going as we explore the impact of AI together.
