Blog
Thoughts, updates, and insights from the Superagent team.
The March of Nines
The gap between a working demo and a reliable product is vast. Andrej Karpathy calls this the 'march of nines' — when every increase in reliability takes as much work as all the previous ones combined. This is the hidden engineering challenge behind every production AI system.
The case for small language models
Most agents today rely on large, general-purpose models built to do everything. If your agent has a single, well-defined job, it should also have a model designed for that job. This is the case for small language models: models that handle one task, run locally, and can be retrained as your data evolves.
Why Your AI Agent Needs More Than Content Safety
You've enabled Azure Content Safety or Llama Guard. Your AI agent still isn't secure. Here's why content filtering isn't enough when your AI takes actions.
Shipped: Runtime Redaction and Command-Line Security
The past two weeks brought runtime redaction, a powerful CLI, URL whitelisting, and a developer experience that puts security directly in your workflow. Here's what shipped and why it matters for teams building with AI agents.
Three years later: AI can (now) defend AI
In 2022, Simon Willison argued that 'adding more AI' was the wrong fix for prompt injection and related failures. He was mostly right at the time. What people tried then were brittle ideas that either overblocked or were easy to trick. This post explains what has changed since, what has not, and why builders can now use AI to meaningfully defend their agents in production.
Introducing Superagent — Defend Your AI Agents in Runtime
Today, we are proud to announce Superagent — the runtime defense platform that keeps your AI agents safe from prompt injections, malicious tool calls, and data leaks.
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