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qm – Multiplayer agent harness for work

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Re: qm – Multiplayer agent harness for work

#101

Post by brianjking »

thoughtpeddler wrote: post #47
danielrmay wrote: post #43

Interesting to see they shipped an "anti-slop" taste skill: > description: Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check. > - *PREMIUM-CONSUMER PALETTE BAN (mandatory, second-most-recurring AI-tell…

Doesn’t this just lead to a new “basin of tastelessness” that, sure, looks different from current slop, but is itself just eventually slop all the same?

Yes.

Re: qm – Multiplayer agent harness for work

#103

Post by beambot »

gyanchawdhary wrote: post #102

this looks over engineered, gimmicky and lame. YC is clearly having a "crisis of meaning" in a post AI world

This is (probably) a natural evolution of Garry's gbrain, a basic RAG for individual use. Gbrain is super useful as a starting point for an individual; this seems like an extension to a company.

I've found gbrain to be very effective with meetily (instead of granola), vikunja for project planning, various mcp for email, etc. It's nice not being locked in to vendors and models...

Thanks for making this OSS too.

Re: qm – Multiplayer agent harness for work

#106

Post by gyanchawdhary »

Finbarr wrote: post #80
kevinwang wrote: post #21

What is yc software?

A team of brilliant people who work at YC shipping products internally and externally.

A team that pioneered writing small checks for outsized returns. AI is making that venture model a lot less attractive, so now they're building productivity software for the startups they once only invested in.

Re: qm – Multiplayer agent harness for work

#108

Post by jauntywundrkind »

duderific wrote: post #86
jauntywundrkind wrote: post #74

Earlier quoted context omitted.

These new experiences are built atop layers and layers of bedrock libraries that we, generally, don't reinvent. Or we reinvent one or two. What's notable to me is that ux doesn't so far generally have this behavior. That as per this post people just build a new app, a new experience. I want to believe over time we'll have better composable & malleable ux experiences atop broader platforms for us. That over time the "…

People are using the UX systems though, just that it's the agent that is gluing them together now. Under the hood, it's still React plus component libraries like shadcn, lucide, tailwind, axios and so on. The agents are so good at this, there's literally no point in not doing it that way.

These are all surface veneer but so so so much less than an app. The entire rest of the owl has to be redrawn, and all the guts inside the owl redesigned.

Re: qm – Multiplayer agent harness for work

#109

Post by buremba »

I love the concept to use different harness frameworks in qm but a true multiplayer harness needs to support other agents and any MCP clients, including Cowork.

Making agents multiplayer is mostly a context problem. You could be using ChatGPT or a Slack bot, or a web interface and the agent needs to know you, your conversations in Cowork etc. so it can enable multi channel collaboration with your agents and your colleagues. We're working on it at https://lobu.ai

Re: qm – Multiplayer agent harness for work

#110

Post by jaggederest »

nozzlegear wrote: post #78
supermdguy wrote: post #18

Earlier quoted context omitted.

Still figuring it out, but it's been really convenient to have an always-on agent that has access to internal systems and can be triggered by webhooks. Some examples of what we use it for: - automatically fixing simple CI failures - getting production alerts and automatically creating RCAs and a fix PR - periodically checking slow DB queries and finding ways to speed them up. - creating charts to answer one-off quest…

> periodically checking slow DB queries and finding ways to speed them up. How does this work in practice?

At least for me, I have a couple dozen years of DB experience but robot, given performance metrics, can get really close to optimal on a tactical level (single query or pattern of queries) but can't yet do the full normalize/denormalize level of improvements without supervision. But really solid if you have one misbehaving query and give it explain analyze access on a read only account
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