Engineering

Dart

I used Dart within the company's boilerplate infrastructure and on the Hybrid.Chat platform, working.

Used on

2021–2025

Internal starter codebases and CI/CD tooling so new company projects skip setting up delivery from scratch.

2023–2026

Hosted self-serve platform where businesses build chatbots from visual blocks and deploy them on web, WhatsApp and Mattermost with human handover.

2023–2024

Smarter.Codes' in-house software estate behind its public site: crawler, automation framework, natural-language stack and chatbots.

2022–2024

An internal operations desk handling equipment, tool accounts, time tracking, invoices and interview logistics for Smarter.Codes staff.

2022–2025

Engineering support for Smarter.Codes' own marketing team, covering its websites, hosting and product pricing pages.

2021–2025

A shared agent inbox where support teams answer customers from WhatsApp, email, Telegram or a custom API in one queue.

2020–2024

A paid community for stock traders: a membership site plus a chat server with in-conversation price charts.

2021 · Hybrid.Chat conversational platform

Situation: The chatbot platform's runtime holds conversation state in memory, so under high availability any pod restart dropped live conversations.
Task: Survive pod churn without rewriting the conversational runtime the product was built on.
Action: I checked alternative frameworks, found the same limit, and kept the runtime: sticky sessions, state persisted to Mongo, and Redis pub/sub to close duplicates.
Result: The platform ran multi-container with state surviving restarts, and the design documented its failure modes, including those the fix introduced.

2023 · Hybrid.Chat conversational platform

Situation: The bot platform needed web push notifications, and my instinct was to build it in house for future flexibility.
Task: Decide between building and buying, separating engineering reasons from personal preference.
Action: I wrote down what I wanted from in-house, weighed it against what the release needed, and recorded the preference and the decision against it.
Result: We shipped on the vendor, and the recorded trade-off made later customisation questions easy to answer.

2023 · Omnichannel agent inbox

Situation: A messaging product ran Keycloak for identity, yet users, roles and organisations already lived in Dgraph, so every write landed twice.
Task: Remove the dual write and its compensating code, and get to one store of record.
Action: I checked which Keycloak features were used, found none beyond authentication, which NestJS covers, and wrote a decision record proposing its removal.
Result: The dependency and its rollback logic came out, leaving the backend with a single store of record.