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The task here is simple: to reduce work, it's a simple investment. The choice of picking the correct bottleneck is as important as the tool itself, as this gives it use. If it's never used, it never creates value. The same goes for uptime, it's important that stability is almost perfect, as downtime undermines the utility of having the tool. Remember that making and using a tool also creates debt for future maintenance of the tool.
To adhere to this, I often choose Golang or Python as they are cheap to maintain. Golang has good stability because it is easy to code and compile checks give early error detection. A word of caution on AI generated tools: while they are cheap to make, the maintenance debt grows exponentially, as the code is often poorly understood by the team and difficult to reason about over time.

Portfolio Engine

A lightweight portfolio and financial data backend written in Go. Tracks companies, currencies, revenue reports, and trades across configurable time periods — replacing spreadsheets with a proper database, REST API, and interactive shell.

Roadmap
  • Price update endpoint
  • Multi-currency conversion
  • Frontend dashboard
  • Shares outstanding history database table
  • Earnings per share (EPS) based on shares owned
  • First-In, First-Out (FIFO) realized gains
  • Dividends earned and related taxes
  • Total tax obligations
Git repo
Accounting Management

A lightweight, SQL-backed, web-based CLI system designed to track assets and liabilities. The goal is to provide a simple, fast, and scalable financial tracking tool that can grow from personal use to more advanced scenarios.

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