The Research Layer
The Metagraph and the Content Compiler
BY ANDY HOUSTONContext
Retrieval that unifies full-text, vector, and graph search is where agent quality gets decided, and off-the-shelf answers stop short of it. So this is the R&D I run for myself: no client, no invoice, no deadline anyone else set.
Problem
Every agent system inherits the quality of what it can retrieve. Off-the-shelf stacks answer one kind of question at a time, and a real customer's world needs connections, exact words, and meaning served through one door. Nobody sells that. So I built it.
Approach
The Metagraph unifies full-text, vector, and graph retrieval under agentic automation, one platform behind one door. The Content Compiler treats content as code: written material as structured data that can be measured, revised, and recompiled. Both run in production and feed every client engagement. The internals sit below the category level and stay there.
Category silhouettes: platform shapes as outlines, internals unlit by design.
Stack
- Category level only: multimodal retrieval (full-text, vector, graph) under agentic automation
- Content as compiled, measurable data
- Working surface: the WikiDesignCo platform
- Published trail: the WikiDesignCo research articles
Result
The platforms exist, run, and back the public writing at WikiDesignCo. Anything published there is published long after the value came out of it.
Published-trail timeline: WikiDesignCo articles appearing long after each build date.
Impact
Every client engagement inherits tools nobody else brings. Everyone else's sample project is a to-do app. Mine is a metagraph and a compiler.
Lessons
None published, by design. The lessons are where the edge lives. Quant firms settled this decades ago: the world can know the category and the direction, and the internals stay home.
Why this matters to you
The difference between talking about agent infrastructure and building it. If you want to know whether the agent talk on this site is backed by anything, this is the anything.
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