Monte Carlo analysis for product development
Explains how to use Monte Carlo analysis for product development, using TweetDeck screen capacity as a practical example.
Tom Ashworth shares insights on product management, software development, and technical leadership, with a focus on probabilistic modeling, Rust, GraphQL, and practical guides for teams.
7 articles from this blog
Explains how to use Monte Carlo analysis for product development, using TweetDeck screen capacity as a practical example.
A guide outlining the responsibilities and expectations for a Project Lead role in a software development team, including planning, execution, and launch phases.
A Twitter engineer shares insights and lessons learned from launching GraphQL at scale, handling billions of daily queries.
Exploring Rust for migrating complex CLI tools from Bash, covering requirements, useful crates, and considerations for adoption.
A tech lead's role is to guide the team's future direction, not just write code. Focus on strategy, planning, and empowering engineers.
Introducing two JavaScript libraries, if-expression and try-expression, that wrap if/try statements in functional expressions for cleaner code.
An update on using Flight.js at TweetDeck in 2016, covering mixins, state management, data flow with RxJS, and component architecture.