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This roundup highlights three AI directions: clinical co-pilots for healthcare workflows, “pull agents” that proactively retrieve needed information, and life planners that translate goals into actionable plans. Thanks to everyone building these tools—share your real-world wins and what’s working.
In this week’s top AI demos (#29), explore three practical highlights: agent memory for smarter ongoing context, image relighting for dynamic lighting changes, and software testing workflows that help validate results faster. Thanks to everyone sharing these demos—great ideas to try and build on.
Top AI Demos #28 brings practical projects to the community: real-time audio classification for instant listening insights, federated learning privacy that keeps training data protected, and interactive presentations for hands-on exploration. Thanks to everyone building and sharing—there’s plenty here to try, learn from, and extend.
Top AI Demos #27 shares practical builds: self-improving agents that iterate on their own, plus Musebot and Thrum demos to explore what these agent systems can do. Big thanks to everyone in the community driving hands-on experiments and sharing learnings.
Homecrew is an open-source package manager for agent skills: install a skill (a directory with `SKILL.md`) from a git tap and keep it synced across every coding agent on your machine and across your team—copying into each detected agent’s skill directory, resolving dependencies from frontmatter, and safely syncing updates via `crew update`/`crew autoupdate enable`.
In this edition of Top AI Demos: PostHog MCP delivers full product visibility, self-evolving agents, and pooled compute so teams can observe and iterate faster. Parthas brings multi-agent Claude Code for collaborative code execution—great for practitioners who want concrete workflows, not theory.
Explore three practical AI updates: voice agents, MLX trading cards, and cyber threat intelligence. Dive into how voice agents work, what’s new with MLX trading cards, and the latest threat intel insights—then share your take with the community.
In Top AI Demos #24, explore deterministic agent pipelines and how “agent memory” changes behavior, plus a careful look at code leaks. If you build or test agents, these demos are practical prompts to tighten reliability, observe memory effects, and protect code. Thanks for bringing these insights to the community.
⚡ Explore 24/7 Dev Agents paired with MCP Apps—always-on agents that keep working and MCP apps that integrate smoothly—so your workflow stays active around the clock. Thanks for building with us and sharing what you’re testing!
⚡ Autonomous software factories pair well with agentic security to help teams ship faster with safer builds. The key idea: use agents to automate parts of the software pipeline while applying security checks along the way, so reliability and protection stay built-in as work progresses.
