Designer & Builder
•
Self-Initiated
•
Ongoing
•
2026
Global Trend Engine
Designed and built an AI-powered futurology intelligence dashboard where eight named agents scan the live web for frontier signals, synthesize cross-domain patterns, and generate predictive convergence insights.
ROLE
Designer & Builder
Company
Self-Initiated
Duration
Ongoing
Year
2026
The Challenge
Tracking meaningful signals across seven global domains — AI, climate, biotech, geopolitics, energy, society, and space — requires reading dozens of sources constantly. There was no single tool that gathered these signals, synthesized patterns across them, and pointed toward probable future developments. Existing news aggregators surface what's happening now — but they don't synthesize signals across domains or point toward what might be coming next.
The Solution
An AI-powered dashboard where seven named domain agents (Turing, Gaia, Mendel, Caesar, Faraday, Orwell, Sagan) scan the live web for frontier signals, a synthesis layer identifies cross-domain patterns, and a predictive agent called Nostradamus generates a convergence insight with an estimated timeframe — visualized as a convergence timeline diagram.
"The gap between 'designer who uses AI tools' and 'designer who builds AI products' is narrower than most people assume — and the design skills most relevant to agentic systems are the ones we already have."
— Daniel Rivas, case study reflection
Outcomes
8 Agents
AI-powered scanning
~45s
Full 7-domain scan
2 Deploy
Targets (Claude + Vercel)
The process
1
Discovery & Research - Summary
Identified a gap in available tools for tracking meaningful signals across multiple global domains simultaneously. Existing aggregators surface current news but don't synthesize across domains or predict future convergence points.
Users
Self — as a futurology enthusiast tracking global trends across AI, climate, biotech, geopolitics, energy, society, and space.
Needs
A single interface that gathers frontier signals from live web sources, synthesizes them across domains, and surfaces predictive patterns — without requiring hours of manual research.
Findings
No existing tool combined multi-domain signal gathering with cross-domain synthesis and predictive insight.
AI agents with live web search could replace hours of manual monitoring.
Naming agents after historical figures (Turing, Gaia, Mendel) created an intuitive mental model for users.
2
Definition - Summary
Designed a system of eight AI agents — seven domain specialists and one predictive synthesis agent — each with a named identity tied to a historical figure relevant to their domain expertise.
Opportunity
Claude's web search capability and API made it possible to build a fully agentic scanning system that retrieved real, current frontier signals rather than relying on training data.
Key Design Decisions
Apply existing portfolio design system (DM Serif Display, DM Sans, #F8F7F4, #1a56e8) for visual consistency.
Expose model toggle (Sonnet vs Opus) as a first-class UI element — treating cost and quality as design dimensions.
Signal intensity bars in sidebar show relative domain momentum, not just binary signal presence.
Convergence timeline uses circuit-board elbow routing to communicate how signals route into a single prediction.
3
Design - Summary
Built the full interface in React with the portfolio design system applied throughout. Designed eight distinct agent identities, a domain toggle system, model selector, signal cards, synthesis panel, and the Nostradamus convergence timeline visualization.
Agent System
Turing — AI & Computation
Gaia — Climate & Earth Systems
Mendel — Biotechnology & Health
Caesar — Geopolitics & Power
Faraday — Energy & Infrastructure
Orwell — Society & Culture
Sagan — Space & Frontier
Nostradamus — Predictive Synthesis
Convergence Timeline
An SVG diagram using straight right-angle elbow routing — horizontal lines turning 90° at junction points into a vertical spine, then a trunk arrow into the Nostradamus rounded-rect node — communicating how independent domain signals converge toward a single predicted future state.
4
Delivery - Summary
Deployed as a React artifact inside Claude (live API calls, no external hosting required) and as a standalone Vercel app with a serverless API proxy that keeps the Anthropic API key server-side.
Result
A fully functional futurology intelligence dashboard with live web search, cross-domain synthesis, and predictive convergence visualization. Runs in approximately 30–60 seconds for a full 7-domain scan.
Lessons Learned
Prompt engineering is interface design — the quality of every output is determined by how the model is instructed.
Agentic UX requires designing for uncertainty — every state (idle, scanning, cancelled, errored, complete) needs deliberate design.
Naming creates meaning — agent names with historical resonance give the system character and help users build mental models instantly.
Visualization is synthesis, not decoration — the convergence timeline communicates the Nostradamus function more clearly than any prose description.
