Reference Summary: Most agentic systems rely on hardcoded heuristics to navigate execution decisions (e.g. From centralized to distributed: In the old world, organizations relied on one centralized

Ai Dev 26 X Sf Luke Kim The Agent Data Stack Why Every Ai Agent Needs Its Own Data Stack - Topic Summary

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Most agentic systems rely on hardcoded heuristics to navigate execution decisions (e.g. From centralized to distributed: In the old world, organizations relied on one centralized

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  • Most agentic systems rely on hardcoded heuristics to navigate execution decisions (e.g.
  • From centralized to distributed: In the old world, organizations relied on one centralized

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AI Dev 26 x SF | Luke Kim: The Agent Data Stack—Why Every AI Agent Needs Its Own Data Stack

AI Dev 26 x SF | Luke Kim: The Agent Data Stack—Why Every AI Agent Needs Its Own Data Stack

From centralized to distributed: In the old world, organizations relied on one centralized

AI Dev 26 x SF | Adit Abraham: Better Agents with Better Data

AI Dev 26 x SF | Adit Abraham: Better Agents with Better Data

Read more details and related context about AI Dev 26 x SF | Adit Abraham: Better Agents with Better Data.

AI Dev 26 x SF | Paul Everitt: The Shift to Agentic Engineering

AI Dev 26 x SF | Paul Everitt: The Shift to Agentic Engineering

More code, fewer staff — the industry is on a bender. But what about quality? At

AI Dev 26 x SF | Andi Partovi: Why Every Agent Needs a Simulation Sandbox

AI Dev 26 x SF | Andi Partovi: Why Every Agent Needs a Simulation Sandbox

Read more details and related context about AI Dev 26 x SF | Andi Partovi: Why Every Agent Needs a Simulation Sandbox.

AI Dev 26 x SF | Or Dagan: Optimizing Accuracy, Cost, and Latency in Real-World Agents

AI Dev 26 x SF | Or Dagan: Optimizing Accuracy, Cost, and Latency in Real-World Agents

Most agentic systems rely on hardcoded heuristics to navigate execution decisions (e.g. which models, tools, and test-time ...

AI Dev 26 x SF | Diamond Bishop: The Next 100 Agents. Building the Agent Native Office

AI Dev 26 x SF | Diamond Bishop: The Next 100 Agents. Building the Agent Native Office

Read more details and related context about AI Dev 26 x SF | Diamond Bishop: The Next 100 Agents. Building the Agent Native Office.

AI Dev 26 x SF | Brandon Waselnuk: Building the Context Engine AI Agents Need

AI Dev 26 x SF | Brandon Waselnuk: Building the Context Engine AI Agents Need

Read more details and related context about AI Dev 26 x SF | Brandon Waselnuk: Building the Context Engine AI Agents Need.

AI Dev 26 x SF | Nyah Macklin: The AI Said So? How to Build Auditable AI Agents Using Context Graphs

AI Dev 26 x SF | Nyah Macklin: The AI Said So? How to Build Auditable AI Agents Using Context Graphs

Read more details and related context about AI Dev 26 x SF | Nyah Macklin: The AI Said So? How to Build Auditable AI Agents Using Context Graphs.

AI Dev 26 x SF | Pratik Verma: Observability Agent to Find & Fix Issues in AI Agents

AI Dev 26 x SF | Pratik Verma: Observability Agent to Find & Fix Issues in AI Agents

Read more details and related context about AI Dev 26 x SF | Pratik Verma: Observability Agent to Find & Fix Issues in AI Agents.

AI Dev 26 x SF | Matthew Xu: The 4-Legged Identity Challenge

AI Dev 26 x SF | Matthew Xu: The 4-Legged Identity Challenge

As MCP systems scale from local setups to shared infrastructure,