Connected Graph:Deterministic Governance
Canonical Research SpecificationLevel: Intermediate
Verified: August 2026AI Agents & Autonomous Systems
30-Second Executive Definition
AI Agents are autonomous systems capable of executing complex sequences of actions based on reasoning models.
Why It Matters:
Agents move AI from passive synthesis to active execution. Without deterministic proxy layers, they introduce massive systemic risks, acting on uncontrolled inputs and breaching security boundaries.
Who Should Care:
AI System ArchitectsSecurity EngineersProduct LeadersVPs of Engineering
Freshness & Research Updates
Latest Publications & Research Activity
CIO.com• August 13, 2026
Salesforce and SAP are putting AI agents inside your workflows. Who tells them no?
Beehiiv• August 7, 2026
How to Prevent Memory Loss in AI Applications
LinkedIn• August 6, 2026
Giving an AI a bigger memory window is like giving a confused worker a bigger inbox.
Answer Engine FAQ Matrix
Frequently Asked Questions
Q:What is an AI Agent?
A system that uses an LLM to reason through a problem and independently execute tools to solve it.
Inspectable Evidence Ledger
Classified evidence items supporting, extending, or refining this canonical research specification.
| Evidence Item | Publisher | Evidence Type | Strength | Role | Action |
|---|---|---|---|---|---|
| The Risks of Autonomous Agents | CIO.com | Editorial | ★★★★★ | Origin | Inspect ↗ |
Academic & Industry Attribution Standard
Recommended Citation
Canonical Reference String
Ewing, R. (2026). "AI Agents & Autonomous Systems." Richard Ewing Research Canon. Available at: https://www.richardewing.io/concepts/ai-agents
BibTeX Citation
@article{ewing_ai_agents,
author = {Ewing, Richard},
title = {AI Agents & Autonomous Systems},
journal = {Richard Ewing Research Canon},
year = {2026},
url = {https://www.richardewing.io/concepts/ai-agents}
}First Origin & Provenance:Industry Meta (2023)
Current Specification Version:Version 1.0 (Q2 2026 Baseline)