Product design / frontend engineering / knowledge systems

Building interfaces for complex knowledge.

I am Axel Pond. I design and build Noosaga, a visual atlas for seeing how fields connect, split, and evolve. This site is the portfolio layer: the product decisions, interface logic, and frontend craft behind the work.

Explore Noosaga Read the case study

Flagship Noosaga

Strength Information architecture

Build Frontend craft

Live system

Flagship product

Knowledge atlas Field to framework to concept

1,500+ fields mapped

18 top-level categories

4 core reasoning views

Working rule

Orient the user before trying to impress them.

What ships

Atlas routes from category to field to subfield
Compare views for schools, frameworks, and debates
Concept maps, timelines, guides, and reading paths
Source labels, confidence states, and AI-assisted workflows

Axel Pond

I design and build tools for navigating complex subjects.

information architecture interaction design frontend systems knowledge mapping provenance and trust complex subjects

Product Proof

Each interface view should earn its place.

Noosaga is strongest when every surface answers a specific user question. Switch modes to see the argument in interface form.

Test the claim

Each view should help answer a different question.

Switch modes to see how the same field becomes easier to browse, compare, trace, and trust. This is a working proof, not a screenshot gallery.

Macroeconomics / overview / field spine

Start with the shape of the field, not a random result.

Orientation

The first screen should show what the field covers, which schools matter, and where to go next.

Field spine Route clarity Low-friction overview

Question unlocked

What are the main schools in this field, and where should I go next?

Macroeconomics

Schools

Timelines

Concepts

Guides

Debates

Interface decision

Lead with a field map, clear routes, and one obvious branch into frameworks, concepts, or guides.

User outcome

Users get bearings early instead of committing too soon to one book or article.

Engineering implication

One shared structure has to drive every view so the hierarchy survives across cards, filters, and routes.

1 entry screen

4 next steps

0 context lost

The point is not density. It is to make the field legible early.

Method

The work sits where research, design, and implementation shape each other.

I studied mathematics and NLP, then kept returning to the same product problem: interfaces change what people notice. The work usually starts with a model and ends in shipped UI.

Model the field

Start with what the user cannot yet see: categories, rival schools, concept clusters, or source lines.

Choose the right view

Different questions need different views: overview, comparison, maps, and guides.

Build the interface behavior

Hierarchy, motion, responsiveness, and state should help users stay oriented.

Make trust visible

If AI helps shape the content, the interface has to show what is sourced, inferred, and still uncertain.

Collaborator Signals

What the work should make easy to judge.

The site should quickly show how I think, what I can build, and where Noosaga is headed.

Flagship

Noosaga is the proof object.

It shows how I handle information architecture, product judgment, trust cues, and frontend execution in one system.

Read the case study

Product

Clear reasoning before feature volume

The work favors sharper user questions, fewer vague surfaces, and decisions that can be defended.

Design

Structure made visible

Taxonomies, comparisons, maps, and provenance cues become interface behavior instead of background notes.

Build

Frontend craft that supports orientation

Layout, state, motion, and responsive behavior are judged by whether they help the user stay oriented.

Trust

Uncertainty stays visible

AI-assisted systems need source state and confidence cues inside the flow, not hidden after the fact.

Choose the clearest next signal.

Live product

If the work is relevant, start with the product or send a short note.

Noosaga is the clearest artifact. The case study, lab, and code show how the system is made.

Product Noosaga Artifact Noosaga case study Experiments Lab Email axel@noosaga.com Social @axel_pond Code GitHub