Https://opencode.ai/ OpenCode was the first agent harness I used, and I have always like it. You can configure a wide variety of providers, but it's open source and has a number of core contributors. The other opinionated option is Pi (the Pi agent harness). This is a great lightweight option and also supports a number of providers. You can also use local model servers. - Source: Hacker News / 9 days ago

OpenCode with GLM 5.2 wrote custom Emacs Lisp to pinpoint within the file where the missing or extra bracket could be. It rewrote the custom code to check various parts of the file. Each of those is a tool use and many, many tokens burned. The next step is to turn those custom scripts written by the AI agent into a tool to speed up the process, or a skill that shows how to use other tools to speed up the process. - Source: dev.to / 12 days ago

I gave GLM-4.5-Air (106B, open weights) 12 coding tasks through opencode on my RTX 3090. It scored 0% — never edited a single file. - Source: dev.to / 13 days ago

Set up your stations. I work in two Ghostty terminals. The left side is for planning and viewing, the right for synchronous agents running through OpenCode. - Source: dev.to / 21 days ago

If you want to try it yourself: grab OpenCode, point it at OpenRouter, select GLM 5.2, and give it a real task instead of a benchmark. The z.ai docs have the rest of the details. - Source: dev.to / 22 days ago

At Pythagora, we've built security reviews directly into the AI development process. Instead of requiring developers to manually catch these patterns, our platform identifies common security issues as code is generated and suggests fixes automatically. - Source: dev.to / about 1 year ago

At Pythagora, we build these security measures into the development process by default, rather than requiring separate prompts. Security shouldn't be an afterthought - it should be integrated from the first line of code. - Source: dev.to / about 1 year ago

At Pythagora, we've seen too many promising AI-generated projects die because users couldn't understand what was going wrong when issues inevitably arose. That's why we built debugging capabilities directly into the development process:. - Source: dev.to / about 1 year ago

At Pythagora, we've built our platform specifically to address these transition points where other AI tools break down. Instead of just generating code and leaving you stranded when issues arise, Pythagora provides:. - Source: dev.to / about 1 year ago

When we started building Pythagora in 2023., it was one of the first agentic systems where AI agents work together to create entire codebases - so, we wanted to share it with the world by showing and inspiring others to build complex systems. However, we knew we needed to protect our innovation from being exploited by larger companies. - Source: dev.to / over 1 year ago