When Shipping Becomes Too Easy
When the hardest part of building shifts, so does leadership We have gotten very good at building software. We have not gotten equally good at…
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Federate Phishing Detection: Training a URL Classifier without Sharing Browsing Data
At Mozilla.ai, we believe useful machine intelligence shouldn’t require centralizing sensitive user data. Federated learning offers a practical path toward collective intelligence without surveillance-style data…
Owning Code in the Age of AI
Software engineering is going through a shift that feels small on the surface but changes something fundamental: code is no longer scarce. For decades, writing…
The Star Chamber: Multi-LLM Consensus for Code Quality
Every AI model has blind spots. It might overlook context, lean toward certain patterns, or fill gaps with confident guesses. When you’re using an AI…
any-llm in the Wild: Three Integrations as We Grow Our Ecosystem
A core part of building any-llm is making sure it is present where developers already are. Over the past few months, we’ve integrated any-llm into…
Run OpenAI, Claude, Mistral, llamafile, and more from one interface, now in Go!
Go where the models are When we released any-llm v1.0 last year, the goal was simple: one interface to use any model, cloud or local,…
Integrating Alinia into any-guardrail for Multilingual AI Security
Introduction In Evaluating Multilingual, Context-Aware Guardrails: Evidence from a Humanitarian LLM Use Case, we explored how guardrails responded to the same policies and prompts in…
Evaluating Multilingual, Context-Aware Guardrails: Evidence from a Humanitarian LLM Use Case
Effective large language model (LLM) evaluation needs to be context-, language-, task-, and domain-specific. As developers gravitate towards custom performance benchmarks, they are also increasingly…
The Misunderstood Small Model Market: A Look Beyond OpenRouter’s Data
The recent State of AI report by OpenRouter and Andreessen Horowitz (a16z) offers compelling insights into the growing adoption of open-weight LLMs. It categorizes models…
Octonous: Making AI useful for everyday work
Most teams don’t wake up asking for “more AI.” They just want less busywork and fewer tabs open. In practice, that usually means one thing:…
AI Generated Code Isn’t Cheating: OSS Needs to Talk About It
Without an AI Coding policy that promotes transparency alongside innovation, Open Source codebases are going to struggle Remember early 2025? “Vibe coding” was a meme…
Secure Your Keys, Track Your Costs: any-llm Managed Platform Enters Open Beta
Over the last few weeks, we’ve been running a small, gated alpha of any-llm managed platform: our client-side encrypted API key vault and usage tracking service…
mcpd Plugins: Extend Your Agent Infrastructure Without Touching Your Code
In October, we shipped mcpd as a “requirements.txt for agentic systems”, a way to declaratively manage your MCP servers across environments. A few weeks later,…
Building in the Open at Mozilla.ai: 2025 Year in Review
A Year of Building Momentum The year 2025 has been a busy one at Mozilla.ai. From hosting live demos and speaking at conferences, to releasing…
Polyglot AI Agents: WebAssembly Meets the Java Virtual Machine (JVM)
Following up on Baris Guler’s excellent exploration of browser-native AI agents using WebLLM + WASM + WebWorkers, we’re excited to present a complementary approach that…