Root

My personal knowledge companion

812 commits · last on Jun 16, 2026

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Root is a personal knowledge companion designed to help me retain, connect, and reflect on the information I consume.

I spend a lot of time listening to podcasts, watching long-form interviews, and reading books. Yet too often, valuable ideas slip through the cracks. I vaguely remember that I heard something interesting, but not where it came from, why it mattered, or what I actually thought about it at the time. In conversation, I often remember a relevant stat or quote but can’t quickly find the exact source:

  • “I remember hearing something like X in a podcast once.”
  • “What podcast did I hear that fact in?”
  • “What were some interesting stats from that book?”
  • “What were my core takeaways from this source?”

The inability to reference specific sources of information, as well as retain and remember core learnings has led to lots of frustration. Having spent much of my life learning about investing, I understand the power of compounding: small, consistent gains accumulate into something incredible over time. In an age where AI can generate information effortlessly, the advantage of humans has morphed into their experience, taste, and judgment. Root is my attempt to help me compound learning itself.

What Root Actually Does

Root is built around a simple idea: true learning only occurs if you actively engage with the material you consume.

Instead of treating books, podcasts, and articles as disposable streams of information, Root turns them into structured, revisitable objects. Every source you add becomes a place to add citations, takeaways, and your own thoughts.

At its core Root consists of a few fundamental primitives:

Sources

Everything starts by creating a source: a book, podcast, interview, or article. Sources act as anchors, giving every idea a clear origin and preventing insights from becoming detached or misremembered.

Citations

Citations are references from the source material. They capture concrete stated facts or quotes as they appear in the source. They are precise, attributable, and bereft of interpretation. This separates information and reflection.

Comments (formerly Captures)

Comments are your in-the-moment reactions and margin notes — your own thinking in response to what you read or hear. Unlike basic highlights, you can associate multiple comments with a single citation, allowing you to capture different threads of thought on the same quote over time.

Takeaways

Takeaways are synthesized insights from a source: patterns you notice, arguments that emerge, or ideas that are worth remembering. Root limits these per source: this forces you to distill sources into a maximum of 5 takeaways.

Notes

Notes are long-form essays or reflections that sit above individual sources. Where takeaways distill a single source, notes let you synthesize across many — weaving together citations and themes from different books, podcasts, or interviews into a coherent argument or idea.

Search & Retrieval

As your library grows, Root makes it easy to ask questions about your takeaways, citations, or captures. It doesn’t just regurgitate summaries, but surfaces and references specific citations and takeaways to support its answer.

Graph

As the library grows, the graph projects sources, takeaways, and tags into a 2D embedding space and draws edges between semantically related items. Tag clusters surface as labeled regions — Business, AI, Venture, and so on — making it easy to see where your reading is concentrated and where adjacent threads connect. Graph V1 supports full interactive navigation. Sliders allow tuning similarity vs. tag-overlap thresholds to adjust semantic clusters, and the underlying neighborhood structure is wired to support smart recommendation workflows.

Guiding Principles

While Root has some “AI Powered” features, it is intentionally AI-assisted, not AI-driven. Real learning comes from friction and AI can often rob us of that friction.

Low friction, high fidelity — Knowledge should enter the system easily, but original source context is always preserved. A citation without its origin is just a floating quote.

Compounding value — The more you add, the more valuable the system becomes. Every highlight, capture, and note makes future retrieval and synthesis richer. This is the same logic as compounding returns: small, consistent deposits accumulate into something significant over time.

Incremental refinement — Insights aren’t fixed. A takeaway you write today might look different after you’ve read three more books on the same topic. Root is designed to support that evolution rather than freeze your thinking at a single point in time.

How I Use Root

Reading

I upload PDFs directly into Root and highlight text as I read, the same way you’d mark up a physical book. Highlights become citations I can reference later, search across, and pull into notes.

To bridge the gap with physical books, I am currently building a mobile image capture feature—allowing me to take pictures of highlights in printed books and run them through OCR. These scanned highlights flow directly into the suggestions pipeline so I can quickly approve and organize them without manually typing out long paragraphs.

Podcasts & Interviews

With podcasts and YouTube interviews, Root generates interactive transcripts. This makes it incredibly easy to skim through long discussions and see comments or citations mapped directly to specific audio segments.

The Walk While Talk Flow: When listening to long audio on the go, capturing ideas used to be high-friction. Now, with the mobile app, I can tap the voice capture button to dictate a quick thought. The player automatically pauses, records the voice memo, and enqueues it in a local offline outbox. When connectivity is restored, the outbox automatically uploads and processes the note—transcribing the audio and drafting structured comments or citations anchored to the correct timestamp. Once I’m back at my desk, I can skim the transcript, see my notes contextually placed alongside the text, and easily approve the drafts to solidify the learnings.

Synthesis

As I’m finishing a source, I’ll often notice a recurring theme and start drafting a takeaway. I’ll give it a rough title and attach citations as I go. For example, while reading the Steve Jobs biography, a pattern that stood out early was his ability to persuade through charm and conviction; I created a takeaway around that theme and linked supporting quotes as they surfaced. When the same idea starts appearing across multiple sources, that’s when I’ll open a note and start writing something longer.

Roadmap

  • Guided Knowledge Synthesis: Implement proactive AI prodding on the dashboard (e.g., highlighting theme circles, asking guided questions about recent comments/captures) to help users synthesize margin notes into the 3–5 core takeaways via interactive chat (focusing on active learning friction rather than automated summarization).
  • Physical Book Highlights (OCR): Quick photo capture of printed highlights to run through the suggestions review queue.
  • Global Search: Fuzzy search across citations, comments, and takeaways with filters.
  • Kindle & Web Clipper Extensions: Browser integrations for Kindle highlights and general article clip/quotes.