🌽 *orn (Porn Quitter Conversational AI Agent )— A Private Recovery Companion in a Week

Source: Dev.to

This is a submission for the Algolia Agent Studio Challenge: Consumer‑Facing Conversational Experiences

What I Built

I built corn, a private, consumer‑facing conversational AI designed to support people who are trying to quit porn and regain control over compulsive habits.

corn is not a general chatbot and not a therapist.
It’s a calm, judgment‑free recovery companion that focuses on:

• Managing urges in the moment
• Handling relapse without shame
• Staying motivated during difficult phases
• Following a structured 90‑day recovery program
• Anonymous journaling and self‑reflection

The core problem corn addresses is isolation. Many people struggle silently with this habit and don’t want lectures, guilt, or explicit discussions. corn provides a safe space where users can simply talk — especially during moments when willpower is weakest.

The conversational experience is intentionally simple:

• Short, supportive responses
• No explicit content
• No medical claims
• Focused on “get through this moment” rather than perfection

Demo

Live Demo: 👉

Screenshots

Note: The “Rate limit in Google Gemini 2.5 Flash free tier” stops the request for providing a response. Overall, the app works correctly in free‑testing using the Algolia Sandbox and OpenAI.

Testing Video

Google Drive video link

How I Used Algolia Agent Studio

Algolia Agent Studio powers corn’s conversational experience. Instead of putting everything into a single index, I designed the agent using multiple purpose‑driven indexes, each with a clear responsibility.

Indexed Data Structure

Why This Matters

• Routing: Queries are sent to the appropriate knowledge source.
• Separation of concerns: Emotional support stays distinct from structured program data.
• Predictability & safety: Responses remain consistent, context‑aware, and non‑triggering.

Prompt & Instruction Design

I used strict system instructions to ensure the agent:

• Never produces explicit or triggering content.
• Uses a supportive, non‑judgmental tone.
• Stays strictly within the recovery scope.
• Uses emojis sparingly to maintain warmth 🌱

Retrieval from Algolia indexes guarantees the agent responds based on intent‑specific data rather than generic LLM guessing.

Why Fast Retrieval Matters

For this use case, speed and relevance are critical. When someone types:

“I have an urge right now”

they don’t want:

• A long explanation
• A generic motivational speech
• A delayed response

They need:

• The right response
• Immediately
• In the correct emotional tone

Algolia’s fast, contextual retrieval ensures:

• The correct intent is matched instantly.
• The agent replies with focused, calming guidance.
• No unnecessary or off‑topic content is introduced.

This makes the experience feel present and reliable—essential for sensitive, time‑critical moments.

End of submission.

DEV Team Member Id: https://dev.to/abbas7120