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 Startup Founders Should Think About Local-First Dev
What Local-First Dev Means for Startup Founders If you’re a startup founder, you’re always looking for some kind of edge–a way...
The Future of AI Code Generation
AI Code Generation Is Still in Early Innings AI code generation tools are still relatively new. The first tools like OpenAI...
AI Inference: A Guide for Founders and Developers
What Is AI Inference (And Why Should Devs Care?) AI inference is the process of machine learning models processing previously...
Regulation & Copyrights: Do They Work for AI & Open Source?
Emerging Questions in Global Regulation for AI and Open Source The 46th President of the United States issued an executive order...
How Local-First Development Is Changing How We Make Software
What Local First Is, and Why It Matters Local-first development is a development ethos that keeps data and code on your device...
The Future of Coding in the Age of GenAI
What AI Assistants Mean for the Future of Coding If you only read the headlines, AI has already amplified software engineers...
How LLM Guardrails Reduce AI Risk in Software Development
How LLM Guardrails Minimize the Risks of AI in Software Development Integrating Language Learning Models (LLMs) into software...
Data Council 2025: The Databases Track with Sai Krishna Srirampur and Craig Kerstiens
Heavybit is thrilled to be sponsoring Data Council 2025, and we invite you to join us in Oakland from Apr 22-24 to experience 3...
Navigating Markets in Open Source As Your Startup Matures
What to Consider About Market Forces in Open Source Why is Heavybit posting this extensive interview about how to navigate...
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...
MLOps vs. Eng: Misaligned Incentives and Failure to Launch?
Failure to Launch: The Challenges of Getting ML Models into Prod Machine learning is a subset of AI–the practice of using...