Weights & Biases whitepapers

At Weights & Biases, we’re pioneering the way that machine learning practitioners collaborate and iterate on machine learning models.

These whitepapers are designed to help those operating at the cutting edge of machine learning. They focus on some of the core issues affecting the industry and provide actionable insights to help elevate the way your team approaches the entire model lifecycle.

Whitepapers

2025 Gartner® thought leadership report

How to Choose the Right Architecture to Build AI Agents

Interest in AI agents is soaring, but without a clear understanding of AI agent architecture, teams risk poor design choices that can lead to failed delivery and mounting technical debt. This complimentary 2025 Gartner® report, provided by Weights & Biases, will help your team select the right components and patterns to build scalable, adaptable AI agents that deliver real business value.

A primer on building successful AI agents

AI agents can dramatically boost productivity and innovation, but getting them into the real world takes a lot of iteration. Quality, governance, and security need to be baked into your development process from the start. Having the right tools and development workflows makes all these iterations possible.

Whether you’re exploring agents for the first time or refining your current approach, this primer delivers actionable insights to help your team succeed and thrive in the AI era.

Navigating the EU AI Act: Compliance through governance and observability

The EU’s AI Act establishes a comprehensive framework to ensure the safe and ethical deployment of AI across industries. However, its requirements for strong governance, documentation, and transparency can be difficult to navigate.

Discover how organizations from around the world are turning regulatory compliance into an advantage, driving innovation while maintaining global AI safety and ethics standards.

Evaluating AI agent applications

AI agents offer unprecedented capabilities, but pushing AI agent applications into production without rigorous evaluation risks inconsistent performance and a negative customer experience.

Download this whitepaper to learn how AI app development differs from traditional software development, as well as the three components needed for a rigorous evaluation and a five-step recipe for running successful evaluations.

3 proven strategies to fast track AI projects

ML leaders are being asked to deliver higher quality models faster. Their teams need better tools to train, fine-tune, evaluate, deploy, and monitor models efficiently.

In this whitepaper, we explain the top three strategies our customers use to accelerate experiment velocity, centralize model management, and improve governance.

Deliver AI agents with confidence: Strategies, ops, tooling, and best practices

AI agents can enhance productivity, efficiency, and decision-making—but only if you can securely deploy them to production.

Download this whitepaper to learn how these autonomous systems differ from other AI technologies and explore top use cases. Learn how to overcome challenges and receive guidelines to ensure your AI agents are deployed and managed efficiently.

How to Fine-Tune and Prompt Engineer LLMs

It’s become much more common to either fine-tune or prompt engineer existing LLMs for unique business needs.

In this guide, you’ll learn fundamentals ranging from how to choose between fine-tuning and prompting, to tips and current best practices for prompt engineering.

How to Train LLMs from Scratch

In this whitepaper, we’ll share what we’ve learned from an insider’s perspective.

You’ll read about how much data you need to train a competitive LLM, balancing memory and compute efficiency, how to mitigate bias and toxicity in your modeling, and much more.

MLOps: A Holistic Approach

In this whitepaper, we dig into operationalizing ML so your organization can spin up the right models that create real business value, faster.

We go beyond just suggesting a tech stack and dig deep into three vital areas–people, processes, and platform–to uncover what the most successful organizations do.