Stop debating which AI agent is best - build the stack that actually works
Every Reddit thread about Hermes Agent vs Claude Code ends the same way: someone recommends Hermes, another says Claude is better, a third says both are overrated.
After deep-diving into all three:
Coding? Claude Code. Best codebase understanding, terminal-native loop.
Monitoring + research? Hermes. Runs 24/7, messages you on Telegram.
Quick edits? Cursor. Tab completion that reads your mind.
Browser automation? None of them. All fail on Cloudflare, CAPTCHAs, dynamic rendering.
The teams shipping fastest in 2026 are not using one tool for everything. They are stacking - each tool for its strength, plus a browser automation layer for the web.
Full comparison + decision matrix:
https://www.browseract.com/blog/hermes-agent-vs-claude-code-cursor?co-from=blog-vs
#IndieHackers #AIAgents #BuildInPublic #SaaS
The “one tool for everything” mindset usually breaks once workflows become real-world messy.
Stacks are becoming much more about reliability and specialization than finding one perfect AI agent.
It is true, we had faced a lot of downfalls testing one tool for all, and finally discovered breakthrough when relied on a stack for different work.
Agreed! use what works for you. thanks for the link
This framing is exactly right "which agent is best" debate is almost always the wrong question.
One thing I'd add from experience building AI-powered products: the biggest friction point isn't choosing tools, it's orchestration how you pass context between agents cleanly so each one picks up where the last left off without losing state or hallucinating about what happened upstream.
We've seen this especially in enterprise workflows where you might have a research agent handing off to a coding agent handing off to a QA layer. The stack works great in isolation, each tool doing its job well, but the "glue" between them is where most teams underestimate effort.
A few things that've helped: standardizing output schemas between agents (even simple JSON contracts), logging agent decisions for human review at key checkpoints, and treating the orchestration layer as a first-class product concern rather than an afterthought.
Curious how others here are handling the handoff problem are you using something like LangGraph, custom middleware, or just prompt chaining?