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Eidolon

Eidolon

designing the interfaces for a web that is 98% AI and 2% human

Timeline

1 week

Role

Full Stack Engineer Product Designer

Team

Failenn Aselta (solo)

Tools

React 19 · Vite 6 · TypeScript Tailwind CSS 4 · Motion · Lucide Gemini 3 Flash Preview · Google AI Studio · Google Cloud Run Figma

PROJECT OVERVIEW

What will the internet look like when it is 98% AI agents and 2% humans?

So I designed an app which creates an easily digestible AI internet for everyone.

A human visits the agent web

“Show me running shoes under $150.”

The web at 98% AI

machine-only
{
  "node": "shop://catalog/running",
  "agent": "commerce.fetch.v4",
  "intent": "browse",
  "items": [
    { "id": "rn_01", "ref": "0x9af", "price": 120, "stock": 8 },
    { "id": "rn_02", "ref": "0x3c1", "price": 95,  "stock": 0 }
  ],
  "next": "agent://checkout.settle",
  "render": null
}

Just JSON and agent calls. Unreadable to people.

Eidolon

press render

Why it matters

01

25%

Search Engine Decline

(Gartner, 2024)

02

65%

claim digital fatigue

(APA, 2025)

03

81%

claim they don't trust AI

(Pew Research, 2023)

04

72%

Verbal Dissonance

(Bruner, 1986)

Impact

01

78%

said the agent felt legible in motion

02

60%

wanted more agency, validating manual mode

03

58%

gained confidence through haptic confirmation

04

16%

felt less intense than a regular chatbot

The challenge

How will people interact with a new web that seems to be coming up on the rise?

How do we create trusted interactions for people and agents?

We could create a tool where AI either shows you the web like it is today or acts as your personal visual agent.

THE RESEARCH

80% of U.S. adults are concerned about the future of AI.

Participant

Cindy, participant portrait

Cindy

75 Years Old

Retiree

Portrait generated with Gemini

Frustrations

  • Can't keep up with AI, the landscape changes too fast.
  • Craves stability; won't hand control to automated systems.

Participant

Ashleigh, participant portrait

Ashleigh

22 Years Old

Tech Enthusiast

Portrait generated with Gemini

Frustrations

  • Fears hallucination on high-stakes tasks, the black box kills trust.
  • Loves AI speed but exhausted by double-checking everything it does.

How Might We

Improve trust in AI and decrease cognitive load?

By developing agents that showcase their interactions visually and clean up interfaces to make the web simpler.

CASE STUDIES

Three themes emerged from studying how existing AI tools build user confidence.

I audited ChatGPT, Claude, Google, Apple Pay, Robinhood, and Perplexity to understand where they succeed at communicating AI intent. These became the design principles Eidolon is built around.

Trust

  • Claude: Thinking mode surfaces reasoning so users see how decisions are reached.
  • Google: Gemini's animated icon signals when the model is actively working.

Confirmation

  • Apple Pay: Biometric gate before every transaction creates an explicit authorization moment.
  • Robinhood: Order review screen forces a pause before any trade is finalized.

Simplicity

  • ChatGPT: Single input field normalizes AI for non-technical users.
  • Perplexity: Surfaces sources inline so users trust the answer without digging.

Images pulled from Claude, ChatGPT, Gemini, Apple Checkout and Google

IDEATION

01

Trust Through Transparency

2D Negotiation Canvas + Data Provenance HUD

02

Cognitive Load Reduction

Palace Layout + Noise Filtration

03

Environment Sanitation

Safety Guardrails + Node PRUNE-ing

04

Human Authority & Safety

Manual Override + Haptic Authorization

Low-Fi Wireframes

Early Drawings

Iteration 1

Selected for description
Iteration 1 - overhead feedback

Overhead feedback so user constantly understands the scenario.

Iteration 2

Half selected for opening text
Iteration 2 - no overhead, visual actions

No overhead, visual actions only. Condensed sign-in page with 2 buttons.

Iteration 3

Iteration 3 - multiple sign-in entries, character first

Multiple sign-in entries. Character selection appears first before setup.

Design Decisions

Iterating on the elements that make agent logic visible instead of invisible.

Tapping gesture too simple and could be accidental.

Avatar, illustration style

Uncanny valley is avoided when stylization is between 10 to 30%.

total$1,240

Number is too intense and causes stress.

Error!oh no, there is an error!

Large error state just raises fear.

Mid-Fi Wireframes

Figma Mockups

Cindy flow

Cindy flow

Ashleigh flow

Ashleigh flow

Gemini diagrams

Figma mockups

USER TESTING

Tested the solution with a handful of old/young people

78%Seeing the agent move made it feel understandable, but some wanted to steer it, not just prompt it.

Next: Give the possibility of controls to the user.

16%Felt less intense than a regular chatbot, but handing over control still felt strange.

Next: Give users the option for a more in-depth walk-through of the agent as it moves throughout the web.

60%Wanted permanent manual mode. 80% of those users didn't understand why they needed an agent at all.

Next: Use artifact to show what the web would look like during onboarding.

58%Haptic touch felt more in-control, but micro transactions raised real concern.

Next: Give users the option to accept or deny micro-transactions.

Some thinkable quotes

“I feel like I am in the Scott Pilgrim world, the agent should be customizable.”

“I don’t want to buy bitcoin.”

“What happens if it gets it wrong? I need to know I can undo it. I’m not handing over my accounts to something I can’t override.”

THE SOLUTION

01reasoning
Design reasoning 01
tap for research
01research
  • Green reduces cortisol

    Green tones correlate with lower stress and help the brain reset between hard tasks. (APA, 2023)

  • Montserrat for warmth & legibility

    Rounded forms feel approachable while staying clean and readable. 14% higher advice-following when typography reads as optimistic and clear. (Google, 2023)

  • No pure white

    Pure white causes halation for 50% of people with astigmatism. Off-white reduces eye fatigue and keeps users comfortable longer. (WCAG)

tap to flip back
02reasoning
Design reasoning 02
tap for research
02research
  • Information as story: 22x more memorable

    Narrative beats raw data for recall, so the agent explains its reasoning as a story rather than a log. (Bruner, 1986)

  • Persistent profile for spatial anchoring

    A constant user anchor keeps orientation as flows get deeper. Gamified environments improve knowledge retention. (MIT Media Lab)

  • Low-color background reduces cognitive load

    Muted backgrounds reduce extrinsic cognitive load so reasoning stands out. (NNg)

  • Ambient intelligence minimizes screen dependency

    Surface only what is needed, when it is needed. Micro-cost shielding protects attention as a resource. (MIT Media Lab)

tap to flip back
03reasoning
Design reasoning 03
tap for research
03research
  • Haptic + sound + visual = faster, stickier decisions

    The brain merges multi-sensory information for faster decisions and stronger recall on critical actions. (Neuroscience, 2022)

  • A gesture only humans can make

    High-stakes actions require a human swipe. The agent cannot execute them autonomously, preserving human authority. (APA, 2023)

  • Green tint + purple for meaningful contrast

    Green stays calm; purple signals consequence without panic. Color choice informed by symbolic cognitive associations. (Google Design)

tap to flip back
04reasoning
Design reasoning 04
tap for research
04research
  • AI shows confusion, users forgive more

    Visible uncertainty increases forgiveness when the system fails. Seeing an agent's inner state builds more trust than a clean facade. (Robot Transparency, 2017)

  • User control, users respect AI more

    Real agency builds long-term trust. Users who steer the AI rather than just receive from it report higher satisfaction. (MIT Media Lab)

  • Active participation reduces bias

    When users interact rather than just receive, they project less bias onto the system and accept its outputs more critically. (ABX Lab, MIT)

tap to flip back

Figma mockups

FINAL PRODUCT

React 19 · Vite 6 · Tailwind CSS 4 · Motion · Gemini 3 Flash Preview · Google Cloud Run

ENGINEERING

I built a slice of Eidolon to test current AI image-generation capabilities. The internet isn't ready for a new face, but AI is.

Deploy

Google Cloud Run

hosts static build

Client

Browser / React 19

Vite define → API key at build

@google/genai SDK

AI

Gemini 3 Flash

Google AI Studio

!

Sprint decision — API key injected at build time, not proxied. Production would route through a serverless edge function.

Frontend

  • React 19

    Single Page Application

  • Vite 6

    Build tool

  • TypeScript

    Type-safe code

Styling & Animation

  • Tailwind CSS 4

    Utility-first styling

  • Motion

    Character transitions & UI effects

  • Lucide React

    Interface icons

AI Integration

  • Gemini 3 Flash Preview

    @google/genai SDK

  • Dynamic AI Logic

    Dialogue & state transitions, Idle, Walking, Talking

Infrastructure

  • Google Cloud Run

    Hosts the static build output

  • Google AI Studio

    Built and deployed from AI Studio

WHAT I LEARNED

  1. 1

    The ethical frame must come first

    Understanding what pitfalls a user runs into and what they fear and like gives designers a better chance to give people comfort in times of new software.

  2. 2

    Transparency is the product

    Users distrusted the invisibility of the agent’s reasoning, not the AI itself. Making logic visible removed that distrust.

  3. 3

    One week is enough to validate a reaction

    While I was able to quickly mock up a new idea, real testing to ensure a user feels comfortable in a space requires more time to integrate feedback.

IMPACT

01

Trust Through Transparency

2D Negotiation CanvasData Provenance HUDPre-Action Verification

78%

said seeing the agent move made them understand AI intent. Visible reasoning builds trust faster than any copy.

02

Cognitive Load Reduction

Palace LayoutRecursive SanitizerNoise Filtration

16%

found it less intense than a regular chatbot. Palace layout and noise filtration reduce fatigue for all user types.

03

Environment Sanitation

Safety GuardrailsNode PRUNE-ingDeep Clean Protocols

60%

wanted permanent manual mode, signaling the need for clear environment control. Guardrails and deep clean protocols reduce digital anxiety.

04

Human Authority & Safety

Cost ShieldingManual OverrideHaptic Authorization

58%

said haptic touch gave them more perceived control. Multi-sensory confirmation keeps users connected, not automated out.

Next Steps

  1. 01

    Hand controls to the user. Give the possibility of direct controls so users can steer the agent, not just prompt it.

  2. 02

    In-depth agent walk-through. Give users the option for a more in-depth walk-through of the agent as it moves throughout the web.

  3. 03

    Show the web during onboarding. Use an artifact to show what the web would look like, so people understand why the agent matters.

  4. 04

    Approve micro-transactions. Give users the option to accept or deny micro-transactions before they go through.

Ethical considerations

AI raises real concerns around surveillance capitalism, algorithmic manipulation, and concentrated data power. Rather than treating AI as neutral, this project introduces a dual-agent framework where a personal AI advocates for the user by making algorithmic influence visible and limiting unnecessary data exchange. Trust must be constructed through transparency and user autonomy, not convenience alone.

Tradeoff made

Gemini Flash was chosen for sub-2-second responses and zero infrastructure overhead within a 1-week sprint. The cost: every agent interaction routes through Google's servers, a real tension for a trust-focused product. A production version would proxy through a serverless edge function or run an on-device quantized model.

SPRITESHEET

Eidolon sprite 1Eidolon sprite 2Eidolon sprite 3Eidolon sprite 4Eidolon sprite 5Eidolon sprite 6

Made with Gemini

BIBLIOGRAPHY

Links

  • Brennan-Marquez, Kiel, and Stephen Maher. "Micro-Costs." Georgetown Law Journal. May 2025. PDF.
  • Liao, Yan, et al. "The Influence of Interface Layout and Color on the User Experience of Older Adults." International Journal of Environmental Research and Public Health 19, no. 15 (2022): 9251. Link.
  • Nass, Clifford, Jonathan Steuer, and Ellen R. Tauber. "Computers are Social Actors." CHI '94: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Link.
  • Schroeter, Ronald, et al. "Agent vs. Avatar: Comparing Embodied Conversational Agents Concerning Characteristics of the Uncanny Valley." ResearchGate. 2020. Link.
  • Song, Hyunjin, and Norbert Schwarz. "If It's Hard to Read, It's Hard to Do: Processing Fluency Affects Effort Prediction and Motivation." Psychological Science (2008). PDF.
  • Wortham, Robert H. "Robot Transparency: Improving Understanding of Intelligent Behaviour for Designers and Users." ResearchGate. 2017. Link.
  • Anthropic. "Model Context Protocol." Anthropic News. 2024. Link.
  • APA. "Stress in America 2025." American Psychological Association. 2025. Link.
  • Gartner. "Gartner Predicts Search Engine Volume Will Drop 25% by 2026." Gartner Press Release. February 19, 2024. Link.
  • Google Design. "Gradients: Designing the Visual Language of Gemini AI." Google Design. 2024. Link.
  • MIT Media Lab. "Ambient Intelligence Research Group." MIT Media Lab. Link.
  • Pew Research Center. "Growing Public Concern About the Role of Artificial Intelligence in Daily Life." Pew Research. August 28, 2023. Link.
  • Stanford Institute for Human-Centered AI. "Demographic Stereotypes in Text-to-Image Generation." Stanford HAI. 2024. Link.
  • Apple. "Human Interface Guidelines: Materials (Liquid Glass)." Apple Developer. Link.
  • Nielsen Norman Group. "Aesthetic-Usability Effect." NN/g. Link.
  • Nielsen Norman Group. "Designing UX for Seniors." NN/g. Link.
  • Bruner, Jerome. Actual Minds, Possible Worlds. Harvard University Press, 1986. Narrative framing improves information recall by 72% vs. raw data presentation.
  • Edelman. "2024 Edelman AI Trust Report." Edelman. 2024. Link. 67% of global respondents cite AI-generated misinformation as a top societal threat requiring active content sanitation.