
Autonomy Is the Bottleneck of the Agents of Today
Today's coding agents are excellent tools for humans in the loop, but real autonomy may require a layer above the agent, not more capability inside it.
Let's have a journey on agents and models.

Today's coding agents are excellent tools for humans in the loop, but real autonomy may require a layer above the agent, not more capability inside it.
Curated reads from the SylphAI team on agents, product releases, and the community building around production AI.

In 5 minutes, you'll understand Skills, how they differ from MCPs and AGENTS.md, and discover how Skills let your AI automatically reuse workflows instead of starting from scratch every chat.

Loop engineering is clearly where we're heading. The missing piece is making it simple enough and affordable enough that every engineer can actually use it.

A coding agent that cannot use a browser is not truly autonomous. Because the real production bugs do not live in the code — they live in the cookies, hydration, redirects, DOM, and the actual clicks...

Andrej Karpathy's shift from vibe coding to agentic engineering captures the real frontier for AI coding: not generating more code, but preserving quality, planning well, and making review faster. This is the layer AdaL is built for.

In 5 minutes, you'll understand Skills, how they differ from MCPs and AGENTS.md, and discover how Skills let your AI automatically reuse workflows instead of starting from scratch every chat.

Loop engineering is clearly where we're heading. The missing piece is making it simple enough and affordable enough that every engineer can actually use it.

A coding agent that cannot use a browser is not truly autonomous. Because the real production bugs do not live in the code — they live in the cookies, hydration, redirects, DOM, and the actual clicks...

Andrej Karpathy's shift from vibe coding to agentic engineering captures the real frontier for AI coding: not generating more code, but preserving quality, planning well, and making review faster. This is the layer AdaL is built for.
Literature review is one of those workflows that sounds simple until you actually do it. Search for papers, filter noise, read the promising ones, keep notes, rank what matters, avoid duplicates, and ...

Every team building serious AI agents eventually runs into the same wall. The model is not the real problem anymore. The real problem is everything around the model. You need the right system prompt...