I have heard a lot of positive things from @Daniel Petro about Mastra, so I wanted to drop this here because this project continues to mature and I am sure it can provide value - especially as it is open source, which provides incredible context for learning from and creating resources/solving problems. https://mastra.ai/

Developer Roadmaps I thought this was a cool resource! Some great looking roadmaps here from when I checked it out! Link: https://roadmap.sh/

Libretto is an open-source CLI that lets agents turn website workflows into fast, reusable scripts you can deploy! Check it out here: https://libretto.sh/ -- I think this would be very useful for anyone (like me) who is exploring new ways in getting more control over browser automation with AI!

What started as an experiment has become a very useful little infrastructure. In continuously expanding out my AI-native system, over time I found myself trusting it for more and more different tasks. I had been using it completely headless, but I started to feel that having a small screen would really enhance it's ability to stay in the loop with me, and would also serve as a clear starting point for an Agent OS that controls the entire machine this level, which has been going very well so far (will have updates on that soon). There's so many things I could get into about controlling this from your phone through Termius, and the benefits of being able to throw over tasks to it. Just the ability to use it as a machine that's always on, and invoke Claude Code via terminal on it for cron jobs has been a great convenience. So in total, so far it's earned itself a face. Let's see if it earns itself a voice too.

Most agent outputs land in two places: the terminal and a markdown file. Both are readable by a human. Neither is queryable by the next agent. The pattern worth knowing: write outputs to JSON lines, not prose. One JSON object per run, appended to a file. The next agent reads the last ten rows and makes a decision without parsing paragraphs. A concrete version: a skill that checks content quality writes a row with the score and any violations. The skill that runs next session reads that row and knows whether to alert or skip. No markdown parsing. Just a tail and a pattern match on score. The difference between an agent that informs and one that compounds is the shape of its output. What format are you using when one agent needs to hand state to the next?