Your body of work is a knowledge base. Treat it like one.
Generic AI invents what you might have said. Platform search stops at one book, one newsletter, or one talk. Tricky Wombat indexes your full body of work: books, blogs, Substacks, Medium, TED talks, podcast appearances, and guest articles. Readers get answers from what you already wrote and said, with links back to the source.
Scattered body of work
Your audience asks questions about your work. Generic AI answers from the internet.
Someone finishes your latest book and asks how it connects to the framework you sketched in a TED talk five years ago, then refined on your Substack last month. ChatGPT will invent a tidy synthesis. Substack search only sees the newsletter. A Kindle search only sees that one title.
Your readers do not think in ISBN numbers or episode IDs. They ask where your stance on a topic changed. How a model in book two revises book one. What you told a podcast host that never made it into print. Those answers sit across years of formats.
Tricky Wombat connects the full body of work. Readers ask in plain language. They get your answer from your actual words, not a guess trained on everyone else's.
Beyond generic AI
Single-source tools stop at one format
Notebook-style assistants and chatbots treat one document or one prompt as enough. Tricky Wombat treats your body of work as a knowledge system. You are not buying a better summary of chapter three. You are buying a different product surface.
Aggregate ideas across books, essays, and talks
Connect books, Substacks, Medium, TED talks, podcasts, and guest articles as one body of knowledge. A question pulls from the hardcover, refines with the newsletter, and cites the stage talk. Readers stop hunting through every format.
Map relationships between people, ideas, and frameworks
Concepts, models, people, and case studies you mention form a connected graph across your body of work. Ask how two ideas relate, which book introduced a framework, or where your guidance changed. You get linked sources, not a one-page paraphrase.
Trace how your theses evolved over time
Thought leadership is a conversation with yourself across decades. Tricky Wombat surfaces how a thesis moved from early essays to later books and talks: what held, what you revised, what you retired. Readers follow the arc instead of rereading everything.
Answer from your words, cite the source
Responses stay grounded in your content, with links back to the book chapter, essay, talk, or episode where you said it. When you have not covered a question, the system says so. Invented wisdom damages trust faster than an honest gap.
Built for voices with depth across formats, not one newsletter or one book
Single-document assistants stop at the file you upload. Tricky Wombat is for thinkers whose value lives in the library: books, essays, stage talks, podcasts, and years of teaching.
If your best answer spans five formats, your AI should too.
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Ask across books, Substacks, and talks as one library
Ask across books, Substacks, and talks as one library
- Ingest books, blogs, Substacks, Medium, TED talks, podcast appearances, and guest articles into one searchable index.
- Readers pull teaching across formats instead of rereading every title for one detail.
- You keep one knowledge layer that grows as you publish.
Connect the people, frameworks, and ideas across your work
Connect the people, frameworks, and ideas across your work
- Entities extracted from your body of work form a relationship graph, not a bag of keywords.
- Ask which books mention a framework, how two concepts connect, or where you changed guidance over time.
- Answers cite the specific passages or moments you said it, so readers jump straight there.
Show how your theses changed from book to stage to Substack
Show how your theses changed from book to stage to Substack
- Your early essays, later books, and recent talks encode revisions to the same ideas.
- Tricky Wombat surfaces how a thesis held, shifted, or was replaced so readers follow the arc instead of skimming a summary.
- You see the same gaps your audience hits when your public thinking has moved on.
Answer from your work, cite the source
Answer from your work, cite the source
- Responses stay grounded in your content, with links back to the books, essays, talks, or episodes you said it in.
- Readers jump to the passage or moment, not a paraphrase of a single upload.
- When you have not covered a question, the system says so. An honest gap beats a confident fake.
How it works
Answer quality is set before the model writes a word
Most AI assistants hand a question and a chunk of text to a language model and hope for the best. Tricky Wombat treats thought-leader Q&A as a pipeline problem. Stages run before generation so answers stay precise across books, essays, and talks, not the one document currently open.
Classify the question
A fact lookup differs from synthesizing a thesis across your body of work. Classification picks the retrieval strategy before anything is fetched.
Retrieve across your body of work
Hybrid search and reranking pull fewer, better-ranked passages from your indexed library across formats. Stuffing an entire bookshelf into a context window makes answers worse.
Assemble scoped context
Retrieved segments are compressed and scoped to the question. Noise and redundant repeats drop out. The model gets what it needs for this ask.
Generate in your voice with guardrails
Cite sources, stay inside the evidence, match your tone, flag uncertainty. The pipeline defines what a good answer looks like before the model runs.
Score and improve
Faithfulness, relevance, and completeness are scored. Weak answers get caught before readers see them. The system tunes itself with use.
10+
formats is normal for a serious thought leader: books, blogs, talks, podcasts, guest pieces, and more
1
document or prompt is the limit of most notebook-style and chatbot tools
0
tolerance for invented wisdom when your name and reputation are on the answer
Audience intelligence
Every question tells you what to write or speak next
Inboxes and comment threads are noisy. Structured questions against your body of work show what readers still cannot find. Cluster themes, spot gaps against your library, and let demand drive the next essay, book chapter, or talk, not only the algorithm.
- Question clustering by topic and theme
- Trend detection for emerging interests
- Content gap understanding against your published library
- Signals for books, essays, talks, and follow-up pieces
Body of work ingestion
Connect the formats. Watch the feeds. Keep the index fresh.
Ingest sites, newsletters, and media with text and metadata. Watch Substacks and web properties so new essays sync as you publish. Pair written work with podcast and talk transcripts when your ideas live on stage and in audio. The index stays current without rebuilding a private library by hand.
- Book, blog, Substack, Medium, and guest-article ingestion
- TED talks, podcast appearances, and lecture transcripts with links to sources
- New posts enter the knowledge base as watches sweep
- Optional YouTube and site watches beside your written archive
Testimonials
Thinkers who use Tricky Wombat
“My audience explores fresh content across all of my media in real time, without me having to think about it.”
Chip Conley
Founder of MEA & Joie de Vivre Hotels, Strategic Advisor to Airbnb
“I explore my content, synthesize new ideas, and expand my strategic voice using Tricky Wombat.”
Ron Nakamoto
Founder of True Wealth Mentorship, Certified Financial Planner, Financial Coach
Trust-preserving AI
Your audience trusts you. The AI earns that trust by showing its work.
Readers spot a generic chatbot fast. Fabricated frameworks or a flat "I don't know" both break the relationship you spent years building in print and on stage.
Tricky Wombat cites your words and links to the source when your body of work covers the question. When it does not, the system acknowledges the gap and points to related material, or surfaces the miss as a content idea for you. An honest miss beats a confident fake.
Everything you want to know
Frequently asked questions
Thought leaders comparing knowledge-base AI to ChatGPT or a single-document notebook ask the same things. Is this another summarizer? Does it cover books and Substacks together? Will answers sound like me?
Here are the answers the way we give them on a first call.
ChatGPT answers from the open web and often invents what you "would have said." Notebook tools stay scoped to the files you paste in. Tricky Wombat indexes your books, essays, talks, and podcasts as a knowledge base. It aggregates ideas across formats, maps entity relationships, and traces how theses evolved, with citations back to your sources.
Books and manuscripts, blogs, Substacks, Medium, guest articles, TED and stage talks, podcast appearances, and related web properties. Playlist and YouTube watches are available when video is part of your body of work. Watches keep new posts syncing into the same index.
As content ingests, people, frameworks, concepts, and case studies get extracted into a graph with relationships between them. Answers connect mentions across formats, for example every time you taught a model, or how two ideas show up together. That differs from matching keywords in one PDF.
Your public thinking revises itself. Idea evolution surfaces how a thesis moved from early essays to later books and talks: what you kept, what you changed, what you dropped. Readers follow the current view with context. You see where your body of work contradicts itself or leaves a gap worth filling next.
The pipeline learns linguistic patterns from content you designate as representative of your voice: structure, vocabulary, formality, humor. It does not rely only on a short system prompt. Responses stay grounded in what you wrote and said, with sources attached.
Connect a representative slice of your body of work, ingest and index, then test with real reader questions. A typical engagement starts with a short fit call about your body of work and audience. The people who built the platform help with setup.
See how it works with your body of work
Connect books, essays, talks, or a Substack. Ask a question your readers would ask. See the answer with sources. One call. No commitment.
Book a 20-minute fit callFull-library search without the enterprise price.
Plans start at $35/seat.