"Data moved us into the information age. Context will move us into the intelligence age." Airbyte CEO @MichelTricot launched Agent Blueprint a Substack with incisive insights on data infrastructure in the AI era. First piece: Data pipelines move information for analysis. Agents

Stop writing custom integration code from scratch. 🛑 Learn to build a connector using Airbyte's intuitive UI. See when to use the builder, how it works, and ask questions. Sign up: https://t.co/jvecbl5qsX

When business teams wait days for data analysis while data engineers drown in ad-hoc requests, innovation stalls. ⏸️ This bottleneck prevents teams from freely exploring data and applying domain expertise to uncover insights. In @thenewstack, Airbyte CEO @MichelTricot breaks

AI agents need context to work. Airbyte connects them to 600+ data sources with proper permissions and fresh data. One embeddable widget. LLM agnostic. Designed for your success. Learn more: https://t.co/i6TapwKfqr

Stop getting lost in API documentation! Watch us create a custom connector in the Airbyte UI from scratch—HTTP API to destination. Sign up: https://t.co/jvecbl5qsX

🛑 Stop exporting CSVs from @Salesforce manually. Set up automated data pipelines that keep your warehouse in sync with your CRM. 👍 This tutorial walks through implementing Salesforce integration using Airbyte ⬇️

Airbyte is now used by thousands of companies and valued at around $1.5B 📈 But rewind to 2019, and our CEO @MichelTricot was cycling through failed startup ideas. On the Before It Clicked podcast with @sunnyrekhi, Michel rewinds to share the full journey — the dead ends, the

We started Airbyte in 2020 to solve data movement. Back then, analytics was the main use case. In 2023, everything changed. ChatGPT hit the market. Suddenly, every company needed to be AI native yesterday.

Building AI agents that actually work isn't about throwing tools at an LLM and hoping for the best. So, we built a hands-on starter kit that shows you exactly how workflows and agents differ (and when to use each approach.) Full technical breakdown, implementation details, and

Another fantastic #AWSreInvent in the books! 🎬 Our booth was busy with some excellent conversations about getting data movement ready for AI. Teams are wrestling with how to move data faster, maintain sovereignty, handle multi-cloud environments, and make their infrastructure

Your data pipelines just got 4-10x faster ⚡ We rearchitected Airbyte's core platform to eliminate the bottlenecks slowing down data movement. MySQL to S3 that took 5+ hours now runs in under an hour. What this means for data teams: Lower compute costs with 17-25% fewer

⚡ Faster data transfers. Predictable pricing. Accurate and secure data for AI and analytics. We've made significant updates to a range of Airbyte connectors and plans! The popular Snowflake destination connector is up to 95% less expensive to perform high-volume syncs and is

🛑 It's demo time! Join us live to see how to create data pipelines in minutes and solve your data integration challenges with Airbyte. Sign up here: https://t.co/myzADj57rF

Building with Airbyte? You're not alone 🤝 Our Slack community is where 25,000+ data engineers connect, troubleshoot, and share insights. Whether you're just getting started or running complex pipelines at scale, there's always someone ready to help. 👉 https://t.co/l7e9qWIXLX

So, you want to convert the data in your customer support environment into an S3 storage bucket that prepares it for ingestion by an LLM. Airbyte is equipped to handle this situation for you! 👍

This week on The Room Podcast, we're LIVE from Inside Summit with @MichelTricot, Co-Founder & CEO of @AirbyteHQ the open-source platform transforming how companies move data. https://t.co/XkF0ELLY66

👀 Take at look at what Typing and Deduping was doing, why Direct Loading is superior, and how you can save 50-70% on data warehouse costs.

Every AI breakthrough announcement points to the same thing: we're at an inflection point. But here's what gets missed: these advances only matter if your data infrastructure can keep up. AI agents need to retrieve data, modify systems, and take real-world actions. That requires

If you're dealing with a data source that doesn't have an off-the-shelf connector, you've got a few options: 1️⃣ Wait for your engineering team to build it (weeks/months) 2️⃣ Pay a vendor to custom-build it ($$$$) 3️⃣ Build it yourself in under 10 minutes We built Airbyte's

From whiteboard to $1.5B: Inside @AirbyteHQ's ideation Airbyte is now a $1.5B company, but when @MichelTricot left his job in 2019, he didn’t have an idea yet -- he just knew he wanted to start a company. So Michel and @JeanLafleur cycled through a ton of ideas, including: -