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This week metrics and logs join traces in Mastra Studio. • Logs: every event, searchable with full context • Traces: debug any run, end to end • Metrics: cost, latency, errors, and scores at a glance With all three pillars of observability in one place, you can now see... show more

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10,509 views • 4 months ago •via X (Twitter)

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[2/5] Introducing Automation Studio 🪩 A dedicated IDE to craft, debug, and deploy browser agents and automations end-to-end. Write code and watch every step in real time with breakpoints and rich logs to fix issues instantly. Editor, live browser, and logs in one place. No context switching, faster iteration.

[2/5] Introducing Automation Studio 🪩 A dedicated IDE to craft, debug, and deploy browser agents and automations end-to-end. Write code and watch every step in real time with breakpoints and rich logs to fix issues instantly. Editor, live browser, and logs in one place. No context switching, faster iteration.

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You can now filter workflow logs to easily view all logs for a workflow run in one place. Jump directly from a run to logs, filter by steps, and quickly find relevant requests.

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Vercel Developers

15,146 views • 4 months ago

Today, we're making Error Tracking by Better Stack generally available. Sentry-compatible. AI-native. At 1/6th the price. Here's why we built it, and how to get the most out of it. What's wrong with error tracking today? Most teams use Sentry. It's solid! But at scale, the bills get brutal. Just 100M exceptions with 90 day lookback? ~$30,000 on Sentry. We charge ~$5,000 for the exact same thing. The math isn't subtle. And so most teams still end up sampling. Which means missing the exact exception that caused the outage. The bigger problem: errors are orphaned data. Your exception lands in Sentry. Your logs are in Datadog. Your traces are somewhere else. Root cause analysis becomes a multi-tab archaeology project at 3 am. We built error tracking natively inside Better Stack: the same platform where your logs, traces, metrics, uptime checks, and on-call schedules already live. Errors are just another signal. They belong together. The part that changes how your team works: Our AI SRE doesn't just surface errors. It fixes them. See a new exception? One click. The AI SRE analyzes the full context, from stack traces, environment variables, browser sessions, related logs and recent deploys, and opens a pull request. Not a ticket. Not a summary. A pull request with the fix. This is what happens when error tracking is fully integrated with the rest of your observability stack instead of bolted on separately. The AI has everything it needs to actually act. The migration is trivial: 1. Keep your existing Sentry SDK. Don't touch a single line of instrumentation code. 2. Point the DSN at Better Stack. 3. Done. Errors flow in. Your dashboards work. Your alerts work. 4. New exception appears. Click "Fix with AI SRE." Pull request lands in your repo. 5. Review, merge, close. That's the whole workflow. The AI angle is real, not a marketing badge. LLMs are genuinely good at fixing bugs if they have full context. The reason AI coding assistants sometimes frustrate engineers is incomplete information, not the model. We solve that by giving the AI SRE your entire telemetry stack as context. Stack traces, logs, traces, service maps, previous incidents and much more. All of it, in one place, at the moment it matters. Observability tools are only useful if you actually ingest all your data. At current prices of other tools, most teams can't afford to. Now you can, and your AI SRE can actually do something about it.

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Juraj Masar

14,920 views • 4 months ago

A production issue shouldn't require a detective Yet that's how most observability works today Most observability tools just dump alerts. Duplicates, no context, and you still fix it yourself Nicolò Magnante (YC P26) and his cofounder Arseniy Shishaev (YC P26) - who spent years building part of Datadog's metrics product - think that's backwards So they built Superlog (YC P26): Observability that's meant never to be opened A wizard scans your repo, installs proper OpenTelemetry, and runs daily to keep up as you ship When something breaks, it groups the errors into one incident, investigates with full context - logs, traces, recent deploys, past Slack threads - and drops a single mergeable PR in Slack. Merge it Ignore it Or open it in Claude Code and tweak it Vendor-neutral, so you keep every log, trace, and metric - even if you leave Not another notification. A fix. Nicolò Magnante (YC P26) CEO & Co-Founder Superlog (YC P26) on Fondo.com START Huge thanks to Eragon for making this episode possible!

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David J Phillips

40,983 views • 2 months ago

I just built this CRACKED Cursor MCP extension that makes your IDE fully aware of all the logs in your browser. Was struggling with a few issues recently and kept having to copy/paste logs but with this tool you can: ✅ Check all console logs + errors ✅ Analyze network requests, responses and errors ✅ Make changes to a selected element in your browser ✅ Take screenshots of your browser ... without EVER having to leave your IDE 🦾 Open source, FREE and compatible with Cursor, Cline, Continue and Zed. Link to the docs with setup instructions down below 👇

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24,742 views • 2 months ago

Your agents can now browse and take actions on the web, just like you can. This lets agents work with sites that don’t have APIs and still complete tasks end to end. Plus, each interaction is streamed live to Studio.

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Andrew Jefferson

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Production-ready RAG systems need observability. From tracking latency and throughput to evaluating response quality with human feedback or LLM-as-a-judge, robust observability gives you visibility into both system performance and output quality, on both a component and system-wide level. This lesson from our Retrieval Augmented Generation course breaks down the core components of an effective eval system and how to balance cost, automation, and accuracy when choosing your metrics. 📚 Learn more in the full course:

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Debugging agents shouldn’t feel like detective work. Today, we’re excited to release two new AI agent interfaces that make agent observability & evaluations even more effective. 🔎 Timeline View – See execution flow and bottlenecks at a glance. No more guessing where your agent gets stuck. 💬 Conversation View – Experience exactly what your users see. Debug from the user's perspective, not just the system's. Combined with last week's Graph View, you now have three complementary ways to debug your agents: → Graph: Visualize decision paths and tool usage → Timeline: Spot performance bottlenecks instantly → Conversation: See the user experience end-to-end AI evaluations + observability are crucial to building reliable AI. These interfaces make it simpler to identify blockers and improve your agents faster. See all three views in action, and try it free with the link below 👇

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499,478 views • 1 year ago

Every single walk-off this season ... all in one place. (And yes, you know which one is at the end 🔥)

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265,191 views • 1 year ago

messed around to see if you can add full forensic tracing with nothing but a helius endpoint turns out you can this traces all historical txs for a wallet, all wallets it interacted with, and lets you filter by token/amount/date — with no indexer insane

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mert

28,460 views • 5 months ago

New in Chrome DevTools: Annotate performance findings with Gemini! You can now ask Gemini to explain performance traces. Specifically you can generate annotations about events in the performance trace. This is a total game-changer. Double-click an event in the Main track, then click Generate label next to the input field. Gemini can suggest a label based on the stack trace and context. Try it out and let us know what you think!

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Sherwood

117,804 views • 6 months ago

🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗 Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take action, and learn how to debug their behavior with LangSmith. Along the way, you’ll: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug your agent with LangSmith Observability & Studio By the end of the course, you’ll have assembled a full team of personal assistants. Enroll for free ➡️

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LangChain

41,016 views • 8 months ago

💥 OSS product analytics for LLM apps. Launching PostHog x langfuse.com integration 🤝 🫳 Day 1 drop of Langfuse Launch Week: We’re marrying product analytics and LLM observability. This integration pipes Langfuse events/metrics/evals into your PostHog project. This allows you to access all of your LLM metrics straight from your Posthog dashboards. I've used it to reality-check our evaluations by correlating them with user retention and ingestion metrics that we already measure in PostHog. This integration is now in public-beta and you can enable it within your Langfuse project settings. Thank you james hawkins, timgl and Lior Neu-ner for working on this over the past couple of weeks and to everyone who joined the private beta. More details: Quick tour of the integration 👇

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Marc Klingen

15,658 views • 2 years ago

I just cracked the code on AI animation ads 🤯 every one of these cost me 12 cents and under 20 seconds to make Gemini Omni + Claude Code is f*cking wild. i built a system that turns any product into an end-to-end AI animated ad in ANY style you want.. claymation, pixar-style 3D, anime, paper cutout, lego, you name it you drop in your product photo and a one line pitch and it handles everything end to end. images, video, voiceover, music, captions, all generated with AI inside Claude.. AI animation ads are crushing on Meta right now and everyone still assumes you need an expensive editor with a 3-week turnaround time to make one. you don't. you just need the right workflow. Im making full end to end high quality AI animation ads in under 3 minutes with this system and they work just as hard organically on TikTok, reels and shorts so i packaged the whole thing up… here's what you're getting: > every prompt i used across all 8 steps > the exact tool stack + the order to run it in > style recipes for claymation, pixar, anime, wes anderson, retro cartoon + CGI > one system that works for paid Meta AND organic built across Claude Code and Gemini Omni RT + reply 'STYLES' and i'll send it over (must be following so i can dm)

I just cracked the code on AI animation ads 🤯 every one of these cost me 12 cents and under 20 seconds to make Gemini Omni + Claude Code is f*cking wild. i built a system that turns any product into an end-to-end AI animated ad in ANY style you want.. claymation, pixar-style 3D, anime, paper cutout, lego, you name it you drop in your product photo and a one line pitch and it handles everything end to end. images, video, voiceover, music, captions, all generated with AI inside Claude.. AI animation ads are crushing on Meta right now and everyone still assumes you need an expensive editor with a 3-week turnaround time to make one. you don't. you just need the right workflow. Im making full end to end high quality AI animation ads in under 3 minutes with this system and they work just as hard organically on TikTok, reels and shorts so i packaged the whole thing up… here's what you're getting: > every prompt i used across all 8 steps > the exact tool stack + the order to run it in > style recipes for claymation, pixar, anime, wes anderson, retro cartoon + CGI > one system that works for paid Meta AND organic built across Claude Code and Gemini Omni RT + reply 'STYLES' and i'll send it over (must be following so i can dm)

Miko

113,272 views • 1 month ago