Automate Brag Document Writing with LLMs

A brag document is a powerful tool to highlight your work by making it visible, measurable, and demonstrating its real impact on you and your organisation - but such a document can be time-consuming to maintain. My talk explores automation of the writing process with language models fed with data from tools like Jira, Notion, and code commits. Learn how to save time, avoid registering missed achievements, and make your work stand out. Ideal for engineers at all levels looking to grow their impact.

No prior knowledge required

Getting your work noticed is often the key to expanding your impact and moving forward in your career. It’s not just about doing great work—it’s about making sure it’s being seen and recognized. I recognised this first hand in my previous roles, both as a manager but also as an individual contributor.

That’s where brag documents come in. First introduced by Julie Evans and championed by leaders like Will Larson (author of Staff Engineer, An Elegant Puzzle), they’re a simple but powerful way to keep track of your achievements, allowing you to showcase your work and your manager to make a clear promotion case for you. The problem? They can be tedious to maintain, leading many of us to put them off and forget key wins.

I will explore and show how ingesting data from task management tools (Jira, Notion, Linear) and code commits, summarising the information with language models and storing the summaries, you keep an up-to-date brag doc. I’ll walk you through the framework, how it works, how I use it to keep my work visible and aligned with goals, and how you can use it.

This session is valuable for python engineers at all levels who want to make their impact more visible, grow their impact, and advance their career. The tone is informative and no prior knowledge required —just curiosity as well a desire to grow and to optimise their workflow.

Outline:

• Why visibility matters: Growing your impact through recognition.
• The brag document basics: How and why they work.
• How to automate that process with language models: A look at how it pulls data from your daily tools and makes use of it.
• My workflow: How I use it to save time and boost visibility.
• Key takeaways: Key takeaways from the talk