Tagged articles

AI Loop

3 articles · Page 1 of 1

Jul 9, 2026 · Artificial Intelligence

Why Enterprise AI Loops Fail: Avoid Amplifying Process Chaos by Defining Goals, Evidence, and Permissions

The article analyzes why many enterprises’ AI Loop implementations amplify workflow chaos, presenting Deloitte survey data, a clear distinction between Agents and AI Loops, a five‑element engineering foundation, risk classifications, and a step‑by‑step, low‑risk rollout framework to ensure safe, measurable AI adoption.

AI LoopAI engineeringAI governance

0 likes · 13 min read

Why Enterprise AI Loops Fail: Avoid Amplifying Process Chaos by Defining Goals, Evidence, and Permissions

Architect

Jul 4, 2026 · Artificial Intelligence

Enterprise AI Loops: Define Goals, State, Evidence, Permissions, and Feedback First

To make AI loops work in an enterprise, you must first make the surrounding work system explicit by documenting five engineering objects—goal, state, evidence, permissions and feedback—so that loops run on low‑risk, verifiable paths before scaling to more complex automation.

AI LoopAgentEnterprise AI

0 likes · 24 min read

Enterprise AI Loops: Define Goals, State, Evidence, Permissions, and Feedback First

DataFunTalk

Jun 26, 2026 · Artificial Intelligence

Why Prompts Are Obsolete and Loop Engineering Is the Next AI Paradigm

The article explains how the AI community is shifting from writing prompts to designing autonomous loops that iteratively execute, evaluate, and repeat tasks, detailing the technical differences from traditional agents, real‑world implementations like Claude Code and OpenAI Codex, and a step‑by‑step roadmap for building reliable loops.

AI LoopAgentAutomation

0 likes · 13 min read

Why Prompts Are Obsolete and Loop Engineering Is the Next AI Paradigm