Next week we're open sourcing DevBox, our autonomous engineering harness that we have been using for the past 6 months. Sign up to get notified when we make the repository public - rudderstack.com/devbox/?utm_…

DevRel @pradeep_io built a RudderStack Transformation via @typesafeai Jev: classifies events by kind (human, AI agent, crawler) and abuse probability before your warehouse. Rules ask "known bot?" Jev asks "what kind, and what intent?" github.com/gitcommitshow/jev… #jev #TypeSafeAI

MANSCAPED replaced a tangle of client-side ad tags with a single RudderStack SDK. Results: 📈 37% revenue increase 📉 10% improvement in Meta CPA 📉 29% improvement in TikTok CPA 📈 162% more revenue from Snap Ads Read the full case study for details: bit.ly/3Ry3pWq

RudderStack was named an Analytics & Measurement Leader in @Snowflake's Modern Marketing Data Stack 2026, 5th edition. The agentic CDP with Snowflake-native DNA for bringing agentic workflows to the entire customer data lifecycle. Full report: bit.ly/3VERIQx

11 companies. 6 industries. The same wall. One fintech tested the same AI query 500+ times. Passed every time. Then came the VP demo. Same prompt. Wrong answer. The agent wasn't broken. It was reading storage, not meaning. Read the blog: bit.ly/4eMRaSJ #AgenticCDP

Now, every RudderStack signup gets a 30-day free trial of our Growth plan. Sign up with your business email to collect data, govern it in pipeline, and send it to 200+ destinations (including real-time warehouse connectors) for activation. Learn more: bit.ly/43GyyxB

What a session! 🙌 Our COO @VenkatNagaswamy joined @Glassdoor at #SnowflakeSummit to talk bridging the dev/data divide with AI agents, and the room had a lot to say. Still at booth #3007 if you want to keep the conversation going.

The data team shouldn't be the bottleneck between data, answers, and activation. Today we're launching RudderAI: agentic power across the entire customer data lifecycle. Get all the details → bit.ly/4alNNQ5

At Snowflake Summit this week? We're sponsoring a table at Club @Hex — coffee, breakfast, evening events, and good conversations about all things data 📊 Stop by between sessions. Sign up here → 🔗 bit.ly/4nVOJAd #snowflakesummit

Snowflake Summit starts today! 🎉 Find us at Booth #3007. Tomorrow at 3:30, our COO @VenkatNagaswamy takes the stage with @Glassdoor: "Bridging the Dev/Data Divide with AI Agents." Come say hello or catch the talk 🔗 bit.ly/4tT9ezd #snowflakesummit

AI will kill the analytics UI. But the infrastructure underneath (semantic models, ID resolution, data quality, governance) is more important than ever. The casualty isn't analytics. It's the UI vendor that built a moat out of dropdowns. Read the blog: bit.ly/4v1Yi35

Agents may finally close the analytics-to-activation gap. Describe the outcome in plain language → agent queries, segments, and activates. Near-term: operators prompt, agents act. Next: agents that don't wait to be asked. Read more → bit.ly/3Rclg9b

The “one context layer” idea breaks in the agentic era. Event meaning lives upstream in pipelines and code. Centralized catalogs create copies that drift. Agents need fresh context from the source, not one place. Distribute meaning. Centralize policy → bit.ly/4npIUuR

SaaS isn't dying overnight. But the moat is eroding, from both sides: As agents replace UIs, feature-heavy products become friction. What matters now is the infrastructure underneath: clean data, identity, and reliable pipelines. See why → bit.ly/4niVWu6

AI agents aren't just assisting with data infrastructure. They're becoming the control plane. The pattern is clear: Write → Config + CLI Read → MCP Separate them, and agents operate safely and reliably. See how → bit.ly/49l1b6B

Analytics and activation were split across tools, data, and teams. That gap slowed everything down. Agents change that. One instruction can query the warehouse and trigger activation. But only if your data is consistent. See how → bit.ly/4ut761B

AI's biggest impact isn't automation. It's speed of decision. Cart checkouts drop 20%. A week later, you've found the cause. The window already closed. Unified customer data lets agents detect, reason, and act before that happens. See how → bit.ly/4t9O2Vg

The data community is focused on what AI agents consume. The harder question is what they produce and how to make it safe. Decision traces are just events, and the infrastructure to handle them already exists. Check out our latest post for details → bit.ly/4cERamW

Agents are removing martech bottlenecks. Infrastructure, tracking, and analytics loops that took weeks now happen in hours, with PRs generated directly from intent. Only works if the data is consistent. See how → bit.ly/48b9Rfw

AI agents don’t remove the need for a warehouse. They expose bad data faster. Claude can query across tools, but it can’t fix mismatched IDs or schemas. Consistency, not centralization, is what makes agent workflows work. Why this matters for your stack → bit.ly/4sZuXVG