16yo Founder & Dev. Obsessed with building impactful products. Documenting my journey from dorm room to CEO.

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Timur Akybaev  • Peerlist

17 | KZ | Full-stack dev | Building https://kwillo.live

Kwillo is built specifically for engineering teams who are tired of manual task tracking after every technical sync. It’s a bridge between your meetings and your workflow.The Problem: Most meeting notes never make it to Jira. Developers spend hours manually updating statuses and creating tasks discussed during calls.How Kwillo solves it:<ul><li>Real-time Context: Transcribes Google Meet calls and identifies technical decisions.</li><li>Automated Jira Ops: Automatically creates sub-tasks, updates statuses, and reassigns tickets based on what was said.</li><li>GitHub Intelligence: Connects your code changes (diffs/commits) with the meeting context to ensure Jira tasks are always accurate.</li></ul>Tech Stack:<ul><li>Frontend: VueJS / TypeScript</li><li>Backend: Python / FastAPI</li><li>AI: Google Gemini for high-accuracy technical transcription and reasoning.</li><li>Integrations: Deep hooks into Jira and GitHub APIs.</li></ul>

Kwillo — AI for Dev Teams

-   Created a full-featured blog platform with a REST API backend and an Aiogram 3 bot as the client. -   Implemented a real-time "like" system. -   Wrote a comprehensive E2E test suite using Pytest, covering all API endpoints and business logic. -   Configured a CI/CD pipeline with GitHub Actions to automate testing on every commit.

FastAPI Blog Platform with Telegram Bot

-   Developed a high-performance URL shortener using a hybrid storage architecture. -   Leveraged Redis as the primary data store for redirects to ensure microsecond latency and used PostgreSQL as the source of truth. -   Implemented a background job with APScheduler to synchronize click counts from Redis to PostgreSQL. -   Built a secure authentication system using JWT tokens and the OAuth2 standard.

Link Simplifier

-   Engineered a microservice-based system with a FastAPI backend and an asynchronous worker for parsing job vacancies. -   Implemented RabbitMQ as a message broker for reliable, decoupled communication between services. -   Utilized Redis for caching user data, significantly improving API response times. -   Containerized the entire stack (API, worker, PostgreSQL, Redis, RabbitMQ) using Docker and Docker Compose.