Multiplayer

The debugging agent for developers.

[Multiplayer @trymultiplayer]

Multiplayer: the debugging agent for developers.

We connect your favorite coding agent to prod to fix application bugs automatically.

Run us locally and eliminate PR slop.

[Multiplayer @trymultiplayer]

Big news: Multiplayer is joining @FilingRamp 🎉

Four years ago we set out to help teams work better on distributed systems. Along the way we grew to thousands of users, open-sourced our AI debugging agent, and found success building alongside the FilingRamp team.

Together, we're bringing real AI to the InsurTech space: smarter filing, agentic workflows, and deeper insight into your data.

Our CEO, @BkStephJ1 shares the full story here 👇

https://t.co/SzvcqWGMTr

To everyone who's been part of this journey, thank you. This is just the beginning. 💜

[Multiplayer @trymultiplayer]

@tomjohnson3 Full article: https://t.co/owkNVL38JA

[Multiplayer @trymultiplayer]

Myth: connecting your agent to your APM closes the debugging loop.

Reality: the agent inherits every structural limitation of the data underneath it.

Our CTO @tomjohnson3 explains it best in this article 👇

[Multiplayer @trymultiplayer]

When something breaks on mobile, Multiplayer captures it and sends your coding agent the exact runtime data it needs to fix it automatically.

[Multiplayer @trymultiplayer]

What data is your AI agent actually working from?

[Multiplayer @trymultiplayer]

If only your coding agent could generate PRs from unsampled, pre-correlated, full-stack data… oh wait, it can 😏

[Multiplayer @trymultiplayer]

Check the full use case here: https://t.co/H5ybBoxJyq

[Multiplayer @trymultiplayer]

The best support ticket is the one that never gets filed …

[Multiplayer @trymultiplayer]

The token optimization advice everyone is missing:

An agent is only as good as the environment it operates in. And traditional observability wasn't designed for agents with its sampled data, aggregated metrics and siloed context that stops at system boundaries.

By structuring the data layer natively for machine consumption you give the agent a curated, correlated, session-scoped package of exactly what it needs to understand your system and how to fix it.

Precision beats volume.

[Multiplayer @trymultiplayer]

Issues are our answer to noisy alerts and duplicate PRs.

We aggressively correlate data per session: user interactions, session metadata, network requests, backend traces, and logs.

We then aggressively deduplicate and group sessions into issues.

The same bug appearing across a hundred user sessions becomes one issue. ✨

[Multiplayer @trymultiplayer]

Your terminal shows the debugging sessions you're running.

The web dashboard tab shows every debugging session anyone on the team ran, today or three weeks ago.

[Multiplayer @trymultiplayer]

Why trust our word for it when you can watch the debugging agent catch and fix a bug yourself? One command. 👇

[Steph Johnson @BkStephJ1]

Team efficiency is a different goal than individual velocity.

The developers I find most interesting right now don’t ask 'how do I ship more with AI?', instead they ask 'how do I make sure what we ship is worth keeping?'

[Thomas Johnson @tomjohnson3]

Finished doesn't mean closed.

One of my favorite things about the Multiplayer web dashboard is that you can reopen any session and keep going in the same thread the agent used the first time.

[Multiplayer @trymultiplayer]

One npm install.
Try a demo.
Setup existing project.
Arrow keys, Enter.

That’s it. That’s all you need to do to get full-stack, unsampled, runtime data into your coding agent.

[Multiplayer @trymultiplayer]

And it's just one copy/paste command to install 😇

[Steph Johnson @BkStephJ1]

I could tell you the debugging agent catches and fixes bugs on its own. Or you could just watch it happen.👇

[Multiplayer @trymultiplayer]

Targeted runtime visibility without managing your own infrastructure OR targeted runtime visibility with full control.

No wrong choice, only great options 😉

[Multiplayer @trymultiplayer]

Dev: What kind of game is Multiplayer?
Me: The kind were you squash bugs in prod. 😇

Check the live demo today.

[Multiplayer @trymultiplayer]

Here are four concrete strategies engineering teams are already using:

‣ Give agents the right data, not all the data
‣ Use the right model for the right task
‣ Context minimalism
‣ Teach your agents to be less verbose

Full article: https://t.co/NBtpAEVApm

[Multiplayer @trymultiplayer]

Token optimization is the new tokenmaxxing.

[Multiplayer @trymultiplayer]

The token leaderboards are already coming down. Token optimization is the natural next step: giving agents exactly what they need to do their best work, and nothing more.