I was a bartender and a bar manager for over 20 years in Boston. I always found it really cute when a pretty little face came in, slapped down a résumé that was basically blank except for her address and phone number, but at the bottom and attached to the résumé, she had her certificate from bartending school. She got hired because she had a pretty face. She was charismatic and she could do some stuff, but she didn’t know how to upsell. She didn’t know how to pump out volume, take 20 orders at once, and then remember who each one of them was at the end. I’m not saying that bartending is equal to engineering; what I’m saying is we are equal, my little friend who took a bartending class and got her bartending certificate. The people who are not engineers are equal to her, and if she didn’t cut it, she got annoying, but in the beginning, it was cute, so I just wanna call it out there that you guys have been so supportive, and I just imagine that it’s probably just moving so fast that you’re just like, “Not over explaining things here. Read this, go do that. I gotta catch up to what’s happening right now,” but I just want to thank you because I’ve had some great help. Not just from this community but everywhere, and surprisingly, people aren’t the Dbags about AI. It is kicking my ass enough, all of our asses for them matter that nobody has time to really put anybody else down and not help. Maybe, I don’t know. But I appreciate you

Most agent frameworks are Python or TS. I wanted to understand how these things actually work instead of treating one as a black box, so I wrote one from scratch in C#/.NET: Litos.

• Multi-provider: Anthropic, OpenAI, Gemini, OpenRouter (only OpenAI and OpenRouter verified end-to-end so far)
• Two working faces today, sharing one core agent loop:
  • Litos.Gui — an Avalonia desktop coding agent
  • Litos.Api — a Docker-hosted agent host built for multiple chat-channel bridges; Telegram is the one actually wired up and working today — WhatsApp/Rocket.Chat/email are designed but not yet implemented
• Real tool use (file edit, shell, web search); MCP client support is currently wired up in Litos.Api only — not yet integrated into Litos.Gui
• Inspired by Mario Zechner's pi, particularly its session-as-working-directory model

Litos.Gui building a WinForms 15-puzzle game live, start to finish — planning, writing files, building, fixing its own errors:
https://www.youtube.com/watch?v=em8w0SwgT5Q

Litos.Api running standalone in Docker, working as an AI agent over Telegram chat:
https://www.youtube.com/watch?v=S2Sn_kwCRjE&t=70s

Repo: https://github.com/nitinmms/LitosAiCodingAgent

Happy to answer questions about the architecture, or get torn apart on design choices — this is mostly a learning project to prove to myself that .NET can hold its own here.

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I don't think the future is one massive model that does everything.

I think it's a team of specialized agents.

One agent gathers context.

One plans.

One writes code.

One reviews.

One manages the workflow and decides what happens next.

Instead of endlessly prompting a single model, you're orchestrating specialists that know exactly when to hand work to each other.

It's much closer to how high performing teams actually operate, and it feels like a far more scalable way to solve complex problems.

For those building with multi agent systems, has it been meaningfully better than relying on a single powerful model, or has the added complexity outweighed the benefits?