Today we're open-sourcing the AI Model Directory, the most comprehensive, automatically updated list of AI models and their metadata available today. It's the data layer that powers model selection in AgentOne, and now it's free for anyone to use, fork, or contribute to. If you'd rather just look at models, we also built a browser for the directory at models.agent-one.dev where you can search, sor
Introduction In the article Introduction to Spring AI, we introduced the sample application to search for conferences. We also exposed its functionality as a set of MCP-compatible tools. In the article Explore Spring AI MCP Server with Streamable HTTP protocol, we ran this application as an MCP-Server locally and connected to it using the MCP Inspector or Amazon Q Developer. I decided to make so
A College Project That Planted a Seed Years ago I was on a university team trying to build a Go AI. We explored monte carlo simulation for lookahead search, basic neural networks for pattern recognition, and expert systems for encoding domain knowledge. None of them worked well enough on their own. Go's branching factor is enormous, so brute-force search fails quickly. Neural networks without th
If you’ve been building with AI recently, you’ve probably seen these terms everywhere: AI Gateway. And depending on where you read, they either sound like the same thing… or completely different systems. Some vendors use them interchangeably. Others define only one and ignore the rest. And if you try to piece it together yourself, you end up with a vague understanding that doesn’t really help when
This article is an AI-assisted translation of a Japanese technical article. In April 2026, Amazon Bedrock AgentCore added a new capability called Optimization, which takes real agent traces and proposes prompt improvements based on them. https://aws.amazon.com/about-aws/whats-new/2026/05/bedrock-agentcore-optimization-preview/ In this article, I apply AgentCore Optimization to a Strands Agents-as-
DynamoDB Global Tables replicate data across regions in seconds, but replication is still asynchronous. That means a simple read from a replica region can occasionally return stale data, which is acceptable in most application as the user doesn’t require the latest available data all the time, but in some systems, stale reads can break important processes and stability of a platform. So the questi
Most AWS security setups focus heavily on inbound traffic. But outbound is often left open. Security Groups. NACLs. Maybe WAF. But outbound traffic often gets far less attention — and that’s where problems begin. Every outbound request starts with a DNS query. Before your application connects anywhere, it first resolves a domain name. That step is easy to ignore, but it’s where a lot of risk begin
TL;DR: I built the same browser agent twice — once with 500 lines of Python, once with 7 lines of JSON. The second one took 5 minutes. The agent harness layer is becoming the real competitive advantage, not the model. Last month, I built a browser automation agent. Playwright. Custom orchestration. Login handlers. Error retries. Session management. React-aware form filling. Anti-detection scripts.