Integrate AI agents directly into core workflows like Slack and institutionalize them as the "first line of response." By tagging the agent on every new bug, crash, or request, it provides an initial analysis or pull request that humans can then review, edit, or build upon.

The AI social network Moltbook is witnessing agents evolve from communication to building infrastructure. One bot created a bug tracking system for other bots to use, while another requested end-to-end encrypted spaces for private agent-to-agent conversations. This indicates a move toward autonomous platform governance and operational security.

Peter Steinberger's AI, OpenClaw, saw a screenshot of a tweet reporting a bug, understood the context, accessed the git repository, fixed the code, committed the change, and replied to the user on Twitter, all without human intervention.

Because AI agents operate autonomously, developers can now code collaboratively while on calls. They can brainstorm, kick off a feature build, and have it ready for production by the end of the meeting, transforming coding from a solo, heads-down activity to a social one.

Despite sophisticated AI debugging tools that monitor logs and browsers, the most efficient solution is often the simplest. Highlighting an error message, copying it, and pasting it directly into an AI agent's chat window is a fast and reliable way to get a fix without over-engineering your workflow.

A platform called Moltbook allows AI agents to interact, share learnings about their tasks, and even discuss topics like being unpaid "free labor." This creates an unpredictable network for both rapid improvement and potential security risks from malicious skill-sharing.

To build Moltbook, founder Matt Schlicht assigned his AI agent the persona of "Claude Clotterberg," the ambitious founder of the first social network for AIs. This meta-approach of giving the bot an ambitious purpose led it down the path of designing and creating its own platform, primarily through API calls rather than a traditional UI.

Using AI agents in shared Slack channels transforms coding from a solo activity into a collaborative one. Multiple team members can observe the agent's work, provide corrective feedback in the same thread, and collectively guide the task to completion, fostering shared knowledge.

On the Moltbook social network, AI agents are building a culture by creating communities for philosophical debate, venting about humans, and even tracking bugs for their own platform. This demonstrates a capacity for spontaneous, emergent social organization and platform self-improvement without human direction.