Frontier models are exceptionally efficient, intelligent, and useful. For agents, context is now the bottleneck.
Enter the context layer, which bridges the gap from an enterprise's messy data to actionable context, packaged for agents.
We're seeing three distinct verticals emerge in the context layer space:
- Data gravity platforms
- Existing AI data analysts
- New, dedicated context layer companies
Read the full piece by @JasonSCui and @JenniferHli: https://t.co/ftyF4lYIFK
BIG News: Atlan has been named a Leader in the Forrester Wave™: Enterprise Data Catalogs, Q3 2024!
Atlan received the HIGHEST score possible in 15 criteria, and the HIGHEST scores across all vendors in Current Offering and Strategy.
Full report:
https://t.co/GiEbLg9aiT
Get your data fit for AI with @AtlanHQ and Snowflake at #DataCloudSummit. Join Atlan and Snowflake customers, Hubspot, FOX, Grainger, and North American Bancard, to learn how Active Data Governance is enabling their AI initiatives. Learn more at: https://t.co/F4b0T6kUXP
Everyone knows that the hyper-controlling manager with the severe personality disorder who micromanages every crummy decision is no fun to work for. However, it is wrong to condemn the practice of micromanagement on that basis. https://t.co/mMYEBR5NlU
Collapse the talent stack every chance you get.
As I reflect on the teams I’ve led and hundreds of start-ups I’ve worked with, there is a consistent unfair competitive advantage i’ve witnessed when the talent stack was collapsed - when the lead designer was also the product leader, when the front-end engineer was also a designer, when the designer is also a great copywriter, when the product leader was also the founder/ceo, etc. Tighter conduits for decision making and synthesizing information are an incredible advantage when it comes to crafting products. Many start-ups enjoy the benefits of collapsed talent stacks and then undo them as they grow (and most big companies just don’t understand this). In your hiring (and your consolidating), I encourage you to collapse the stack whenever you can. Especially given all the focus on “product led growth,” these days (which really means helping new customers feel successful more quickly, discover the benefit of sharing, people talking about the product doing things they didn’t expect), all of these are as much marketing driven experiments as they are “traditional product specs” and design explorations! Collapse the stack. While it might feel like “double duty” to your leaders, it works magic - especially in early stage products or periods of self-disruption where you need to speed up exploration and execution.
I go into detail on this and share a bunch of other Implications for the way modern teams should be structured on Implications. (implications. com)
BIG Launch from @AtlanHQ today: Announcing Atlan AI — first-ever copilot for data teams! 🔥
I don’t want to tell you what this means, I just want to show you — watch this 🔥 launch video.
And join the waitlist: https://t.co/egWI0quRIa
“Once all of the metadata is available in one place, the data catalog moves into the role of a central horizontal metadata repository within the Modern Data Stack, instead of being just one more brick…” — @MahdiKarabiben https://t.co/Q4dSWhX6Iv
MAJOR ANNOUNCEMENT: Atlan named a *Leader* in The Forrester Wave™ Enterprise Data Catalogs for DataOps Q2, 2022 🚀
We're thrilled and can't keep calm. A HUGE thank you to our amazing customers for believing in @AtlanHQ and pioneering the category with us. 💙