Flutter features and releases
New screens and flows from Figma to the App Store and Google Play: state, API integration, push notifications, crash reporting.
Senior Flutter Developer · Go · LLM integrations
Flutter developer with 4.5+ years of commercial mobile development. For the last three years I've been the sole mobile developer behind three products: architecture, stack, API contracts, releases. I build my own products end to end — Go backend, web, LLM integration, deployment.
New screens and flows from Figma to the App Store and Google Play: state, API integration, push notifications, crash reporting.
Picking up someone else's codebase, refactoring legacy code without stopping feature work, covering key logic with tests.
REST API in Go with PostgreSQL and CI on GitHub Actions — enough to launch a product and validate the idea.
Budget limits, fact-checking and fallbacks: the model does not invent data and does not burn the budget.
Part-time project, long-term contract or a full-time role — tell me about the task, and I'll come back with a clear plan and estimate. Get in touch →
Flutter · 4.5+ years
Platforms for working with external contractors: onboarding, documents, deals, payouts and tax receipts. The code is under NDA, so this is what I did rather than the code itself.
Flutter · Dart · Riverpod · GoRouter · Dio · Socket.IO · Firebase · Drift/SQLite
Go · LLM · static sites
A Go pipeline that turns open data into a content site: collect data (NOAA, PRISM) → generate text with an LLM → fact-check with a second model → build a static site.
Go · Yandex AI Studio (gpt-oss-120b) · Hugo · Cloudflare
Code: sitefarm-showcase →Go · PostgreSQL · PWA · LLM
An assistant with memory: cellar, taste profile, wine matched to your own recipes. Retrieval-grounded answers: the code picks the data, the model only explains it.
Go · PostgreSQL/SQLite · PWA · OpenAI-compatible LLM client
Code: terroir-monorepo →B2B SaaS · in development
AI replies to reviews from several platforms for venues, in local languages. A Go core with platform adapters: a new review platform is a new adapter, not a rewrite.
Go · Flutter · PWA · PostgreSQL
tapreply.net →Built in parallel with my main product role — I'm used to running several projects at once: separate repos, clear scopes, every app released to the stores.


2025 · Flutter
Short-video social network that rewards activity: personal feed, video upload, points for views, likes and comments, rewards exchange.
Second developer on the team: built every screen from Figma designs, connected API requests and state management in several sections. Published on the App Store and Google Play.


2022–2023 · Flutter
Restaurant search on a map, table booking and food ordering.
Second developer: responsive UI from Figma, Google Maps API, state management, REST API integration, bug fixing and feature work.


2022–2023 · Flutter
Feed product catalog and animal diet calculator for farmers.
Second developer: UI from Figma, state management, REST API integration, bug fixing and feature work.
2023–2024 · Flutter
Platform for working with external contractors: contractor onboarding, documents and receipts, payouts with tax (NPD) withholding.
Built the mobile app from scratch.
2023–2024 · Flutter
Service that finds contractors, handles deals and pays them.
Built the worker mobile app from scratch: onboarding, profile and services, orders and payouts.
Agents take on the volume of work; responsibility for the result stays with me.
My daily driver is Veai (AI coding agent for JetBrains IDEs), in IntelliJ. It reads the project, edits code, runs tests and commands. Plan and decomposition come first, code second; the agent keeps project memory, my own skills and rules. I have also worked with Cursor and GitHub Copilot; Claude Code and OpenAI Codex follow the same agentic workflow — plan → diff → tests — so switching between them is quick.
One session: 6 agents in parallel, each in its own repo (Astro/Hugo sites, PWA clients, Go backend), ~2 hours of staged work with acceptance criteria. Then I review: tests, builds, commit authorship, secret scan. Within one repo, parallel agents get separate git worktrees. Nothing lands in main without this review.
In sitefarm texts are generated through Yandex AI Studio and checked by a second model; in Terroir code picks the data and every answer is validated against the database. Both have hard monthly budgets.
Each skill points to where it is used — not a tag cloud.
Tell me about your task — a project, a long-term contract or a full-time role. Before moving into development I spent 5 years running projects and led a department of 6.
hello@antonkozyrev.dev