Datadog Developers

"Sometimes a session replay can literally be four hours long... trying to watch all of that doesn't scale." @OliverKorzen from @ThisWeeknAI chats with @datadoghq Sr. PM Abhi Motgi about how AI Summaries make Session Replay much faster to navigate. Get a summary of what the user was trying to do, where they hit friction, and how the session ended - then jump straight to the important moments with AI Smart Chapters and hyperlinks that take you directly to the events worth investigating. Watch the full walkthrough on YouTube 👉 youtube.com/watch?v=z_pAqw…

Once your agent is in production, people will use it in ways you never expected. That's why @OliverKorzen from @ThisWeeknAI calls out Patterns as one of the Agent Observability features he's been using the most. It automatically clusters conversations into themes, making it easier to discover new use cases, uncover gaps, and decide what your agent should learn next. Watch the full walkthrough on YouTube 👉 youtube.com/watch?v=oN7Hn1… @datadoghq

In his latest walkthrough, @OliverKorzen, from @ThisWeeknAI, calls Lapdog one of his favorite @datadoghq features (and it's free). Watch your coding agent in real time, track prompts, tool calls, file changes, and costs across every session. Catch the full Agent Observability walkthrough on YouTube 👉 youtube.com/watch?v=oN7Hn1…

"AI agents don't just get better, they get better at some things - and worse at others. That's why we built experiment visualization" - Sr. Staff Engineer, Michael Bevilacqua-Linn Instead of digging through charts, this new Agent Observability view makes it obvious what's changing across experiment runs, helping you quickly decide whether your latest version is actually an improvement. Did user satisfaction improve? Did accuracy regress? Did brand voice get better? @datadoghq

@stripe @chatbase @composio @BuildOnNodeOps @CustomerIO @datadoghq @depotdev @klaviyo @pydantic @RevenueCat @GetSchematic @spaceship @steeldotdev @tabstack stoked to be on this - we're in good company.

New providers on Stripe Projects are available now: @chatbase @composio @BuildOnNodeOps @CustomerIO @datadoghq @depotdev @klaviyo @pydantic @RevenueCat @GetSchematic @spaceship @steeldotdev @tabstack

@ryanstp_ @datadoghq i wonder too... let us know what you think 👀

anyone had good experience w/ @datadoghq 's Bits agent? always been a huge fan of DD and just opened it up and its now front and center. obviously pushing it hard. wonder if it can beat claude code + DD mcp lol

@bigdata @atalwalkar @datadoghq @mldcmu always good to hear @atalwalkar 🤘

Zero-shot time series forecasting is now faster AND cheaper than tuning statistical models on the fly 🔎 @atalwalkar (@datadoghq and @mldcmu) traces the full journey of time series foundation models—from early skepticism to Toto V2 beating every public benchmark thedataexchange.media/ameet-talwalka…

With Bits Code automations, you can go from a monitor or error in @datadoghq to an investigated issue and a fix that's ready to review - without someone manually triaging every incident. @ThisWeeknAI see the full video: youtube.com/watch?v=HqyZJ0…

"One of my favorite Bits Code workflows" - Mike Leach, @datadoghq Instead of checking cloud costs manually every Monday, schedule a custom prompt to run automatically. It analyzes your cloud spend, generates a notebook with the biggest changes, and is waiting for you when you start your week. @ThisWeeknAI see the full video: youtube.com/watch?v=HqyZJ0…

LAUNCHED: Stale Flag Cleanup - you ship with feature flags, but do you remove them? If your team uses feature flags, you probably have a bunch of old ones sitting around that nobody has touched in months. @datadoghq now automatically detects stale feature flags, shows you why they're stale, and can generate a removal PR with Bits AI when it's time to clean them up. check the docs → docs.datadoghq.com/feature_flags/…

NYC MEET-UP: Building on @supabase? Come hang with us August 4th. See @datadoghq's Database Monitoring (DBM) for Supabase in action, built to catch and explain performance issues so you don't need a database expert to fix them. We'll cover: ⚡ Query performance and optimization 🔍 End-to-end tracing from app to database 🤖 AI-powered recommendations 🚀 Running production Postgres without needing a DBA Save your spot: luma.com/new-york-2026-…

@FactoryAI love to see it 👏

Factory Incident Response investigates Slack alerts, triages the noise, and prepares a fix before you've opened your laptop.

Datadog has acquired @AdaptiveML, a frontier AI startup that enables organizations to build, own, and deploy specialized AI agents and models using reinforcement learning, synthetic data, and production signals. Welcome to the Adaptive ML team! Learn more: bit.ly/4y0VOnI

Production performance problems don't always show up in testing. Learn how to use @datadoghq Continuous Profiler to: • find CPU & memory hotspots • interpret flame graphs • investigate slow endpoints • compare profiles to spot regressions New free course ↓ learn.datadoghq.com/courses/contin…

Building AI agents with Gemini? Join @datadoghq + @googlecloud on June 30 for a hands-on workshop covering Agent Observability with Vertex AI. Trace prompts, token usage, latency, evaluations, and correlate everything with APM, logs, metrics, and infrastructure. See how to debug and optimize AI agents in production. 👉 save your spot: datadoghq.com/partner/llmobs…

Tomorrow in NYC: @datadoghq, @ArklexAI, and researchers from @Meta are talking about one of the hardest parts of AI engineering - what happens when agents don't behave the way you expect. Reliability, evals, drift, regressions, and building trust in production agents. Join us ↓ luma.com/kkipue1p

WE'RE HIRING: Senior Developer Advocate at Datadog I'm helping build @datadoghq developer growth motion, which means spending a lot of time with builders. @datadogdevs