A provider invoice shows what an API key spent. When five teams share one key, finance sees one bill. Domino’s LLM Gateway attributes calls to a project and model, with budgets per team and user. Blog: hubs.ly/Q04zZyCH0

The future of AI runs on systems combining mjany model types. Jev adds one that returns probabilities for a fixed set of answers. To see how this architecture works, Domino's Etan Lightstone built an open counterpart: the Domino Decision Model (DDM): hubs.ly/Q04zY8t70

44% of AI leaders expect regulatory sanctions from ungoverned outputs. Where does your coding assistant run? Domino now preinstalls Copilot, Claude Code, and Codex. Usage captured. Work logged. Blog: hubs.ly/Q04zHxTj0

Organizations with fully integrated governance are 3.9x as likely to run agentic AI in governed production. Who can trace which agent produced a wrong answer? Five patterns compared. Blog: hubs.ly/Q04zHN9P0

Which model should your coding agent use? With Cline on Domino, you can swap between frontier, open source, and local models mid-project. Domino platform context stays. Jobs submit from VS Code. Blueprint: domino.buzz/4xZ59LH

Justin Johnson's AI research agent, ARIA, finished a project before he even started it, three months earlier, while he slept. Johnson explains what it's like to become the "second mover" on your own work. 🎧 Listen now: hubs.ly/Q04yprlM0

Need enterprise persistent storage for AI workloads without granting cluster-admin access? Learn how to deploy Domino Volumes on Azure using NetApp Cloud Volumes ONTAP with minimum privileges for production-ready, snapshot-backed storage. Read the guide: hubs.ly/Q04yprm-0

On September 30th at 1 PM ET, we're making the case that apps are where data science finally meets the business. Building one is no longer the hard part. Getting a valuable one into production still is. Register here: hubs.ly/Q04xCWkd0

SR 26-2 leaves generative and agentic AI out of scope, and there's still no further guidance on how to govern them. Join our live discussion on September 29: SR 26-2 and the Agentic AI Governance Gap for MRM Leaders. Register now: hubs.ly/Q04xCWdm0

Heading to the CDAO Government Summit? Don’t miss Paul Jojy, Forward Deployed Engineering at @DominoDataLab, for: From Guardrails to Mission Outcomes: Defense in Depth for Agentic AI hubs.ly/Q04vNyDb0 #AgenticAI #AIGuardrails #MissionOutcomes

The people developing life-saving therapies, securing markets, and protecting citizens deserve recognition today and every day. Happy Labor Day from us at Domino. #LaborDay

Most enterprise AI is solving the wrong problem. @DominoDataLab CEO Thomas Robinson joined @TheCUBE to explain why end-user AI tools aren't where companies make or lose revenue. For that, look at high-consequence, core business processes. Full interview link in comments.

"We still believe that judgment is better than hallucination." @DominoDataLab CEO Thomas Robinson on building trust into high-consequence AI decisions. Watch his full interview with Dave Vellante of @theCUBE (link in comments).

AI is moving fast. Enterprise trust in it isn't. @DominoDataLab CEO Thomas Robinson on why "human-in-the-loop" is a core principle of enterprise AI transformation. Watch his full interview on @Nasdaq Exchange's Live from Market Site (link in comments).

Cost savings are a ceiling, not an AI strategy. @DominoDataLab CEO Thomas Robinson: "The maximum you're going to save is 100% of your cost." Watch his interview with Dave Vellante on The Cube to find out where AI's real return is.

At the @GovCIOmedia Health IT Summit, we’re looking forward to conversations about what it takes to make AI work in the real world. Come find the @DominoDataLab team to learn how health teams turn AI innovation into impact. See you there: hubs.ly/Q04vN2bS0

Big news out of NYC!! This week, we welcomed our new CEO Thomas Robinson, and seeing his name and our logo lit up across Times Square was a moment our team will never forget.

"The crossing is personal because somebody's got to do it." Justin Johnson explains why most data science teams are stuck on the copilot side of AI, and why no one can read or buy their way into building a harness. 🎧 Listen now: hubs.ly/Q04t-bDL0

Most teams treat single-package upgrades as a given. In a validated environment, that instinct is often the problem. We're covering this in a live session with Appsilon on how Axon.R and Domino keep R ecosystems consistent from CRAN to production. 🎟️ hubs.ly/Q04tHyGz0

“Excellent enabler for data science” is how a data scientist in the finance industry reviewed Domino on @Gartner_inc Peer Insights. Read the full review - hubs.ly/Q04txCzZ0