If you’re in NYC today, come find us at the Data Management Summit. Edge & Node CEO @rodventures takes the stage for a keynote at 3:05 PM, followed by our very own Craig Tutterow joining a panel at 3:25 PM. We also have a booth in The Gallery, we’d love to meet you. Secure your delegate pass here: #DMSNYC# #DataManagementSummitNYC# #DataManagement# #DataStrategy# #CapitalMarketsTech# #InstitutionalTrading#

The Data Management Summit NYC is tomorrow 🗽 3:05 @rodventures keynotes on more data at lower cost, and the case for AI-enabled specialization. 3:25 Craig Tutterow joins the panel on building a defensible audit trail for agentic workflows. @ Ease, 605 Third Ave, 7th floor. Come find us 🤝 #DMSNYC#

Our CEO @rodventures is keynoting the Data Management Summit New York on Sept 17. More Data, Lower Costs: The Case for AI-Enabled Specialization. AI is making more data. AI is also making the systems that handle it cheaper to build. He'll show how those two things meet at scale. 3:05 PM. NYC. Hope to see you there

The Edge & Node team will be at the Data Management Summit NYC this Thursday. 3:05 : @rodventures keynotes on more data at lower cost, and the case for AI-enabled specialization. 3:25 : Craig Tutterow joins the panel on building a defensible audit trail for agentic workflows. @Ease, 605 Third Ave. #DMSNYC# We hope to see you there!

Craig Tutterow, our Director of Data, takes the stage at 3:25 PM on September 17th at the Data Management Summit New York. The panel: Proving Your AI: Building a Defensible Audit Trail for Agentic Workflows in a Regulated Environment. Regulators are asking firms to show their work on AI decisions. Most governance frameworks were built for a different era. Craig and the panel get into what a defensible audit trail looks like now. 40 minutes, moderated by Pete Harris of the A-Team Group.

# Practical and Useful Patterns with ADK State manages your agent's "current situation." With dynamic prompts and scoped data management, build truly intelligent conversations 🎯 📌 **Title**: State 🔗 **URL**: ## 🧩 Overview State is the working memory accessible via `session.state`. It holds "data needed right now in this conversation" -- like shopping cart contents or information gathered step by step during a booking flow. State's key feature is **prefix-based scoping**: - `app:` - Data shared across the entire app (global settings for all users) - `user:` - Data shared per user (user preferences, persisted across sessions) - `temp:` - Temporary data valid only within the current session - No prefix - Standard session scope Additionally, embedding `{state_var}` in agent instructions enables dynamic prompts that adapt in real time. ## 🛠 How to Use Set values on `session.state` using dictionary-style access -- for example, `session.state["booking_date"] = "2026-07-15"`, `session.state["party_size"] = 4`, and `session.state["seat_type"] = "window"` for standard session-scoped data. For scoped state, use the `user:` prefix (e.g., `"user:preferred_language"`) for per-user persistent data, `temp:` (e.g., `"temp:search_results"`) for data that disappears when the session ends, and `app:` (e.g., `"app:maintenance_mode"`) for data shared across all users. Additionally, embed placeholders like `{booking_date}`, `{party_size}`, and `{user:preferred_language}` in the `Agent`'s `instruction` parameter to dynamically inject state values into the agent's prompt at runtime. ## 🏗 Practical Usage **Restaurant booking flow:** Gather information progressively through conversation, accumulating in State: 1. "I'd like a reservation for 4 tomorrow evening" → Save `booking_date`, `party_size` to State 2. "Window seat please" → Add `seat_type` 3. "I'm allergic to nuts" → Add `allergies` 4. At final confirmation, pull all info from State to generate a confirmation message With `{booking_date}` embedded in instructions, the agent always responds with awareness of the latest booking status. **Persisting user preferences:** Using the `user:` prefix, carry forward information like "this person prefers English" or "this person is vegetarian" even when sessions change. ## 💡 Use Cases - 🛒 E-commerce: Manage cart contents in State. `temp:` for search filters, `user:` for shipping address - ✈️ Travel booking: Progressively accumulate dates, party size, seat type in State - 🤖 Personalization: Learn and persist user preferences via `user:` scope - 📊 Dashboards: Share system-wide status via `app:` scope ## ⚠️ Caveats - Storing large amounts of data in State degrades performance. Consider Artifacts for bulky data - Changes to `app:` scope affect all users. Use with caution - When embedding `{state_var}` in instructions, unset values may display the placeholder as-is. Provide defaults - Establish key naming conventions to avoid collisions ✨ Leverage State's scoped management and dynamic prompts to build context-aware, intelligent agents. Perfect for booking flows and personalization! #ADK# #AIAgent#

Supermicro is simplifying Edge AI deployments with validated Kubernetes solutions powered by @RedHat and @EverpureData! By combining Supermicro's edge computing infrastructure with Red Hat OpenShift and the Portworx by Everpure data management platform for AI workloads, organizations can more easily deploy, manage, scale, and secure AI applications across distributed edge environments. Check out the full post by @storagereview:

Open Storage Summit continues! Tune in to hear KIOXIA's Anders Graham in this panel discussion on Architecting AI Inference and Data Management for Maximum Scale . Watch now: #StorageSummit2026# #OpenStorageSummit# #SupermicroStorage2026#

【#OpenDataSpaces】# Interview Part 2 is live! AI adoption is accelerating — but why does agentic AI fail in enterprise? Part 2 gets to the root cause: the #context# scarcity. And distributed data management is the missing piece. Watch the full version on🔗