The Heavybit Library
The Heavybit Library is an extensive catalog of educational content featuring hundreds of hours of expert presentations, insightful podcasts, and articles focused on helping technical founders achieve breakout success.
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LLM Fine-Tuning: A Guide for Engineering Teams in 2025
General-purpose large language models (LLMs) are built for broad artificial intelligence (AI) applications. The most popular...
How to Create Data Pipelines
How to Create Data Pipelines Introduction to Data Pipelines In today’s data-driven world developers and product managers rely...
The Power User’s Guide to Open-Source Licenses
Licensing: A Key Trade-Off for Open Source Startups Why is Heavybit putting together this guide for open-source startup founders...
How to Launch a Dev-First Startup: Day-to-Day Tactics
Welcome to the third article in our definitive series on how to launch a developer-first startup, featuring advice from veteran...
O11ycast Ep. #83, Observability Isn't Just SRE on Steroids with Dan Ravenstone
In episode 83 of o11ycast, the Honeycomb team chats with Dan Ravenstone, the o11yneer. Dan unpacks the crucial, often...
How to Start an Open-Source Project
How to Start an Open-Source Project Why is Heavybit posting a first-principles guide on how to create an open-source project?...
Enterprise AI Infrastructure: Compliance, Risks, Adoption
How Enterprise AI Infrastructure Must Balance Change Management vs. Risk Aversion 50%-60% of enterprises reportedly “use” AI,...
How to Launch a Dev-First Startup: Community & Leadership
Welcome to the second article in our definitive series on how to launch a developer-first startup, featuring advice from veteran...
How to Properly Scope and Evolve Data Pipelines
For Data Pipelines, Planning Matters. So Does Evolution. A data pipeline is a set of processes that extracts, transforms, and...
Understanding Business Models & Defensibility in Open Source
First-Principles Business Models Matter for Open Source A key concern for open-source startup founders is defensibility–how to...
Machine Learning Model Monitoring: What to Do In Production
Machine learning model monitoring is the process of continuously tracking and evaluating the performance of a machine learning...
Technical & Cultural Learnings from 10 Years of Computing
What the Software Community Has Learned from 10 Years in Tech Amara’s Law states, “We tend to overestimate the effect of a...