Alexander Traykov

Product designer

I design, code and ship software from micro-businesses to large enterprises.

Pave

Designing a dot-patterns loading language for Pave

Prototype recording Build-wait motifs and builder context The recorded prototype opens on the builder loading state, then cuts to the fixed-pixel motif set behind it.

Work

Product overview · includes an early workflow prototype Pave in 26 seconds A 26-second overview of Pave's builder, Plan Mode, versioning, Direct Edit, and an early workflow idea from the evolving product.

Designing Pave

Designing Pave's enterprise AI app builder, planning flows, direct editing, and navigation

Background
I joined an engineer-built AI app builder as its first product designer, working across product structure, interaction design and implementation.
Problem
The prompt-to-app loop worked. Planning, precise edits, recovery and navigation still needed to feel like one product people could use with confidence.
Coded prototype · mock product data Plan Mode: clarify, review, approve, build A short coded prototype of clarification, plan review, approval and execution using mock dashboard, task and timing data.
Prototype recording · fabricated product data Direct Edit: select, adjust, continue A short prototype of component-aware selection and direct changes using fabricated product data.

Impact

Public launch
Pave grew from an early alpha into a publicly launched product.
Shipped capabilities
Plan Mode and Direct Edit reached the public product; navigation Phase 1 shipped to production on July 16, 2026.
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Earlier closed-beta build A working canvas, not a static map Open a canvas, move through the graph, select a node and keep the relationship between the material visible.

Designing SynapseSys: shaping a clinical AI product's visual language

How I shaped SynapseSys from loud terminal experiment into a distinctive clinical AI interface: retro, modern, terminal, blocktype, motion, restraint.

Background
I designed and built Synapse-Sys as an AI-powered infinite canvas for research and synthesis, where people can connect, revise and use material in the next operation.
Problem
The graph interaction was the hook, but the product also had to keep nodes editable, edges readable and the work recoverable as the canvas grew.
Earlier closed-beta build Keep a growing canvas editable Pan, box-select and tidy the map without leaving it; saved canvases also carry recovery controls for finding work again, undo and redo.
Synapse-Sys canvas showing readable edge paths, operation labels and a compare action between nodes.
Earlier closed-beta build Using an edge as a command Readable paths, operation affordances, labels and enough context to follow one relationship through a busy map of edges.

Impact

Closed-beta product
The product includes accounts, sharing, exports, AI budgets, pricing and checkout flows around the canvas.
Evidence limit
It is nearing launch; public adoption, retention, activation, generated-node reuse and ghost-node acceptance are unmeasured.
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Pipelines OAuth connection design specification showing a reusable account-authorisation pattern.
Design specification · generic sample data One connection pattern for different providers. A reusable OAuth design specification keeps account, permissions, and environment choices visible while allowing provider-specific detail.

Designing trust into Quickbase Pipelines

Three years of Pipelines work across OAuth, editable AI proposals, high-volume automation, troubleshooting, and a code mode for advanced builders.

Background
I designed Pipelines across three years, from reusable connection patterns to AI-assisted creation and expert configuration.
Problem
Builders needed to connect systems, inspect AI proposals, and manage advanced logic without hiding choices that could affect live data.
Pipelines code-mode design specification showing an advanced expression editor and locked visual controls.
Design specification · generic sample data An escape hatch with explicit ownership rules. The specification keeps the code and visual representations from silently overwriting each other.

Impact

Observed reach
Across September 11, 2025 to September 11, 2026, 2,826 customer accounts used the all-Pipelines-AI feature set.
Evidence limit
Product-analytics counts show reach and measured follow-through; they do not establish a successful automation or causal design impact.
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Connection Central resources-side-panel design specification showing a resource hierarchy and nested relationships.
Design specification · sample data · broader than GA A resource hierarchy for understanding relationships. A broader v2 resources-side-panel design specification, not a sequence or a complete December 2024 GA screen.

Untangling Connection Central

A resources-first redesign of Quickbase Connection Central, shaped by research, narrowed for a December 2024 launch, and shipped without a beta with later adoption evidence.

Background
I rebuilt Connection Central’s information architecture after an earlier version by Johnny Lee had accumulated useful but disconnected views.
Problem
Builders could see individual connections and pipelines but had trouble following what a resource touched and what depended on it.
Connection Central two-pane design specification with resources navigation beside a detail pane.
Design specification · sample data · includes deferred concepts Keep the map while inspecting a connection. This broader design specification shows expanded filters and field rows; the detail controls were deferred from the GA release.
Connection Central Pipelines-list design specification with sample pipeline data.
Design specification · sample data · broader than GA A first-class Pipelines view in the broader v2 model. This is a broader design specification with sample data, not a labelled GA screenshot.