Karolina

Karolina was an experiment with a persona that understands conversation context, remembers the user, and answers with more character than a generic chatbot. It first ran on Make, Airtable, and Telegram, then moved toward Python, FastAPI, and Firebase.

For MemeMatch, the matching mechanic alone was not enough. I wanted to test whether a character with memory, humor, and a clear voice could increase engagement and give the product a stronger personality.

If AI remembers the user and has a clear role inside the product, it can become part of the experience instead of another chat box in the corner.

• First MVP on Make, Airtable, and Telegram.
• User memory, forgetting outdated facts, and contextual answers.
• Python, FastAPI, Firebase Auth, and Firestore version.
• Voice, support, and social-content experiments.

The LLM answered through a specific persona, using user memory and context. The important part was interaction style: less generic assistant, more character that fits MemeMatch.

Make, Airtable, Telegram, Python, FastAPI, Firebase Auth, Firestore, OpenAI/GPT, and ElevenLabs experiments.

• Treat the persona as part of the product, not prompt decoration.
• Test behavior in a simple MVP first.
• Avoid selling it as a standalone product without a stronger use case.

Experiment with memory, humor, support, and social content. In this portfolio I treat it as a MemeMatch module, not a separate product.

Return to Karolina when MemeMatch or a similar product needs its own AI character.