22 explainers, each one running in the page.
Built one at a time, mostly to find out whether I understood the thing. They are grouped by the cell they belong to on the hub.
‹ Back to HiveAgentic Systems
Recursive Agent Optimization
One policy acting at every node of a dynamic delegation tree (arXiv 2605.06639), with an interactive execution tree and a lambda slider.
Run it → jsxPharma QC Pipeline
A working six-agent document-review app for pharma copy that ingests .docx and scores findings by severity.
Run it → htmlUnder the Hood — a Single Co-authoring Turn
The five-layer architecture beneath one chat turn, drawn out.
Run it → htmlAgent Ecosystem
A browsable interface over the fifteen catalogue entries, filterable by kind and category.
Run it →Attention
One Token’s Journey Through the Stack
Vaswani et al. (arXiv 1706.03762) followed end to end — one token from embedding through positional encoding, eight heads, the residual stream and cross-attention, with a live attention playground.
Run it → jsxQuery, Key & Value
An interactive walk through the three self-attention projections, from intuition to the full scale-and-softmax pipeline.
Run it → jsxAttention Sinks Induce Gradient Sinks
Stepped paper explainer (Chen & Yao, 2026): attention mass piling on the BOS token creates a matching sink in the backward pass.
Run it →Deep Learning
Deep Learning in Neural Networks
How stacking layers builds a feature hierarchy from edges to objects, and why depth beats width.
Run it → jsxDeep Learning, Explained by a Chicken, a Pug, and You
A field guide comparing shallow and deep “brains” to explain what the word deep actually buys you.
Run it →Agent Harnesses
Meta-Harness
End-to-end optimisation of model harnesses (arXiv 2603.28052), with feedback compression set against OPRO, TextGrad, GEPA and AlphaEvolve.
Run it → htmlQuantum Maze — Stage 2: Fork / Join Harness
Replays blind and shared fork/join agent traces through the maze harness, side by side.
Run it →