How far can we push AI autonomy in code generation?
We ran a series of experiments to explore how far Generative AI can currently be pushed toward autonomously developing high-quality, up-to-date software without human intervention. As a test case, we created an agentic workflow to build a simple Spring Boot application end to end. We found that the workflow could ultimately generate these simple applications, but still observed significant issues in the results—especially as we increased the complexity. The model would generate features we hadn't asked for, make shifting assumptions around gaps in the requirements, and declare success even when tests were failing. We concluded that while many of our strategies — such as reusable prompts or a reference application — are valuable for enhancing AI-assisted workflows, a human in the loop to supervise generation remains essential.
Announcing the Official PHP SDK for MCP
The PHP Foundation, Anthropic’s MCP team, and Symfony are collaborating on the official PHP SDK for the Model Context Protocol (MCP). Our goal is a framework-agnostic, production-ready reference implementation the PHP ecosystem can rely on.
Covariance and Contravariance in PHP
Before we dive into the details and code examples, let me quickly define covariance and contravariance:
Covariance: Making something more specific
Contravariance: Making something less specificNow let's dive in and see how these concepts apply to PHP.
Strengthen your system’s ability to recover by intentionally causing and resolving failures