That moment when a user gets it never gets old. Walked someone through our live demo today. The CLI wizard had everything set up in under a minute. They came in skeptical, but by the time the first issue surfaced automatically, they just watched the agent work.

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?'

I could tell you the debugging agent catches and fixes bugs on its own. Or you could just watch it happen.👇 Those of you who know me will appreciate that I set this up myself. VS Code, npm install, the whole thing. The wizard did most of the heavy lifting, which is exactly the point. 😆

David Fowler nails something that gets glossed over in most AI productivity discussions: 👇 Everyone is celebrating the speed of shipping. Fewer people are asking what happens to the codebase six months later when nobody fully understood what they shipped.

We just open sourced Multiplayer. Some may think this is the worst possible time for that decision: maintainers drowning in AI-generated PR slop, projects folding, and dramatic declarations that 'open source is dead.' 🧵 👉 github.com/multiplayer-...

GitHub - multiplayer-app/multiplayer: The open-source debugging agent for developers. We connect your favorite coding agent to prod to fix application bugs automatically. Run us locally and eliminate ...

The open-source 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-app/multiplayer

github.com

Give your coding agent the data it needs to automatically fix bugs. APMs sample heavily and miss critical content. Multiplayer captures unsampled, full-stack session data and feeds your agent exactly the runtime context it needs. Confident fixes start with complete runtime data.

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.app

Multiplayer@multiplayer.app · 2mo ago

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.

The 10x engineer has never been the person who coded the fastest. This is now more true than ever. And, it should reframe how you think about AI productivity.

The problem: AI generates code faster than teams can review (and debug) it. The constraint: AI tools need complete visibility into runtime context, not sampled fragments, to more accurately generate code or assist with debugging. The solution: 👇

This is how engineering leaders triage production issues: 👇 What this matrix doesn't show: the hidden cost of triaging blind.

AI tools boost velocity but erode deep system knowledge. Debugging and system understanding are the next challenge. Great article by Stephane Moreau: open.substack.com/pub/blog4ems...

Teams are rushing to add AI debugging to their observability stacks. But if the underlying data is: • Aggressively sampled • Missing payloads • Scattered across disconnected tools Adding AI on top just means faster access to incomplete data. Fix the data problem first.

Imagine you're looking for a specific email, but: ‣ Your inbox has 100,000 of them ‣ They're all labeled "Email" ‣ There's no search function ‣ Some emails are in Gmail, some in Outlook, some in Yahoo That's what AI agents face when trying to debug your system. 🧵

If your observability data isn't correlated across frontend and backend (or you're missing critical data due to sampling or lack of instrumentation) adding AI on top won't fix it. It'll just give you faster access to incomplete information. AI debugging is only as good as the data you feed it.

The best engineers were never the ones who wrote code fast or with “clever” solutions. The gap between top and bottom performers continues to widen.

There a debugging bottleneck few talk about: the hours engineers spend reconstructing what happened in production because critical context is missing. For example: • What payload did we send? • What did the external API return? • Which headers were set? • What did the middleware modify?

Which pie chart is your team living in? This is the difference between 3 hours of context switching and 10 minutes of clarity. Bad debugging = manual correlation across scattered tools. Good debugging = auto-correlated runtime context in one place.

Not all session replays are built for the same job. 📊 Product analytics tools answer questions about user behavior. 🪲 Debugging tools need to answer questions about system behavior. When bugs span APIs, services, and data layers, engineers need replays that correlate user actions to backend data.👇

Multiplayer@multiplayer.app · 7mo ago

Not all "session replay" features are created equal. Mixpanel's frontend session replays are an add-on to a product analytics tool. Multiplayer's are built for engineers asking: “What issue did the end-user experience?” “Why is the system behaving this way?" “How do we fix this bug?”

Building developer tools means constantly stress-testing your own assumptions. If you signed up for Multiplayer and bounced during onboarding, understanding why is incredibly valuable to us. We’re offering a $50 gift card for a short conversation about your experience (15–20 min).

Question for teams using LogRocket: how much time do you spend jumping between tools to connect frontend issues to backend problems?

Multiplayer@multiplayer.app · 7mo ago

🔥 Hot take: Session replay without backend visibility is like having a security camera that only films the parking lot. Sure, you can see someone walked into the building. But you have no idea what happened inside.

1/ Looking back at 2025, what stands out the most isn’t one single thing. It’s how a very small team managed to ship our product and achieve our goal: making debugging faster, less fragmented and less manual. And, they did it without sacrificing their sanity.

For engineering teams: what percentage of bugs in your app are purely frontend vs. backend or integration issues? As systems become more complex, partial visibility creates friction across support and engineering. This 👇 highlights why end-to-end context is becoming table stakes for debugging.

Multiplayer@multiplayer.app · 8mo ago

How much is partial visibility costing your team? If you're using Fullstory, you can see what users are doing on the frontend. But when something breaks, can you see why?

Teams design distributed systems and then try to debug them with workflows built for monoliths.👇 That’s why I’m such a believer in session-based visibility: pulling every layer of the system into one full stack session recording so engineers can investigate, debug, and fix issues faster.

Multiplayer@multiplayer.app · 8mo ago

Context fragmentation is the real bottleneck. This captures the day-to-day reality for so many engineering teams. 👇 Teams adopt microservices for autonomy and scale, but unless the debugging workflow evolves with the architecture, you end up with more tools, more friction, and less clarity.

I wish I could laugh, but it’s an uncomfortable truth most executives overlook. We obsess over churn rates and retention metrics, yet rarely measure how much inefficient debugging and support workflows cost the company (and who they actually serve).

Fullstory is fantastic for understanding user behavior. But debugging technical issues? That usually needs more than a replay of the UI. For engineering teams that need deeper visibility there's Multiplayer. dev.to/rohan_rajpal...

Multiplayer vs Fullstory

Session replay tools have become a key component of testing and debugging workflows in recent years....

dev.to

Raise your hand if this describes your technical support 👇 👀 If this feels familiar, I’d love to hear what’s working (or not) in your support flow. Ping me in the comments or DMs. My take: the real problem isn’t the bug. It’s the missing context.

User: What’s the benefit of switching to @multiplayer.app ? Me: 👇

We tend to talk about innovation as if it comes from sudden sparks of genius: one person, one idea, one breakthrough. But most progress doesn’t look like that. It’s rarely a lightbulb moment. It’s actually more like a relay race. 🧵

End-user support is supposed to be simple: a user reports a problem, the team fixes it, everyone moves on. In reality, it’s usually a marathon of manual steps, tool-switching, and endless back-and-forth. What’s tricky is that this marathon often ends with a (deceptively) positive outcome: 🧵👇

Looking for AI-related ice breakers for tomorrow’s MCP demo night in NY. Would this do? 😉

Guess the team at Anthropic could’ve used a Multiplayer session replay for that one 👀

Tom Johnson@tomjohnson3.bsky.social · 10mo ago

Claude Code error or human error? From the latest Anthropic blog post: variable names don’t match (red)…misspelling of urgent (blue) … unnecessary second check (second yellow line)