Boring Python: code quality
Boring Python: code quality December 19, 2022 Django, Python This is the second in a series of posts I intend to write about how to build, deploy, and manage Python applications in as boring a way as possible. In the first post in the series I gave a definition of what I mean by “boring”, and it’s worth revisiting: I don’t mean “reliable” or “bug-free” or “no incidents”. While there is some overla
We just did something crazy: we completely rewrote our backend from Python to Node just one week after our launch. We did this so we can scale. Yes, scale. A week in. In some ways, it's a good time right? The codebase is still small and we don't have too many users. But on the other hand, it goes completely against the advice given to early-stage startups which is to just ship and sell, and worry
Intro This guide is intended for people who are already familiar with Python 3 and looking to start a new project. This guide comes from experience building api backends for a variety of startups in different industries, it serves as a starting point for what the state of “best practise” is for how I think about organising Python projects, structuring code, testing, and common libraries I’ve reuse
Does OLAP need an ORM?
TL;DR · ORMs have proven to be useful for many developers in the OLTP/transactional stack (Postgres, MySQL, etc). · OLAP/analytical databases like ClickHouse could potentially benefit from ORM abstractions. · Existing transactional ORMs probably shouldn’t be extended to OLAP due to fundamental differences in semantic meaning between OLTP and OLAP. · Moose OLAP (part of MooseStack) is an open sourc
In Hillel Wayne’s post “I am disappointed by dynamic typing”, he expresses his sense that the Python ecosystem doesn’t really make the most of the possibilities that Python provides as a dynamically typed language. This is an important subject, since every Python program pays a very substantial set of costs for Python’s highly dynamic nature, such as poor run-time performance, and maintainability
In 2023, we launched an AI-powered Chief of Staff for engineering leaders—an assistant that unified information across team tools and tracked critical project developments. Within a year, we attracted 10,000 users, outperforming even deep-pocketed incumbents such as Salesforce and Slack AI. Here is an early demo: By May 2024, we realized something interesting: while our AI assistant was gaining tr
Irrational Exuberance
Hey folks, I’m Will Larson! I wrote An Elegant Puzzle, Staff Engineer, The Engineering Executive’s Primer, and Crafting Engineering Strategy. You might also be interested in my collection of popular blog posts over the years, or to read my writing as it’s published via my newsletter or my RSS feed. Early and late-stage hypergrowth. April 27, 2026 Agents as scaffolding for recurring tasks. April 12
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Why we migrated from Python to Node.js
Building modern Python API backends in 2022
Python’s “Disappointing” Superpowers
Building AI Products—Part I: Back-end Architecture