DMS.LABS / AUTONOMY & CODEEngineering & transformation
Optical study03 / Refraction

Agentic Era

AI moves from tool to colleague. Autonomous agents, the future of work, and creativity within everyone's reach.

13 articles
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13 of 13 articles

2026. 03. 28

An Agent Team’s Trust Budget: Operational Design to Reduce Escalation Latency

As automation expands, recovery of trust matters more than performance alone. Managing escalation latency prevents small incidents from becoming widespread distrust.

2024. 05. 20

Getting the Most Out of N8N Workflows

An in-depth guide to N8N architecture and practical applications that go beyond no-code limitations. The ultimate guide to business automation.

2026. 01. 04

The Democratization of Creativity, or the End of Art?

An age in which everyone can become an artist may paradoxically be one in which nobody can.

2026. 01. 07

From Tools to Colleagues: The Rise of AI Agents

AI is no longer content simply to answer our questions. Now agents set goals, execute them and create on their own.

2026. 03. 02

Operating an Agent Team: From One Agent to Multi-Agent Orchestration

A team with separated roles delivers results more reliably than a capable agent working alone.

2026. 03. 05

The Real Standard for Multi-Agent Operations: Failure Budgets and Approval Gates

Agent-team performance is determined more by operating rules than model performance. The key is allowing failures while controlling losses.

2026. 03. 05

Agentic Era CH6. You Cannot Protect What You Cannot See: Runtime Observability and Safe Operations

Agent systems need visibility before performance. Bringing logs, traces and policy events onto one screen reduces incidents and builds trust.

2026. 03. 06

Agentic Era CH7. Hand Off Without Stopping: Human Handoff and Escalation Design

Good agents do not handle everything alone. Operational quality comes from a loop that detects failure quickly, hands it to people precisely, and returns to automation.

2026. 03. 09

Memory Is Harder to Retrieve Than Store: Designing Agent Memory Layers

Agent performance depends more on retrieving the right context at the right time than on model size. Well-designed memory layers improve cost, quality, and operational stability together.

2026. 03. 12

Good Agents Filter First: Context Firewalls and Policy Routing

Most performance degradation and dangerous automation arise from disordered context intake rather than inadequate models. Context firewalls and policy routing can improve quality, speed and safety together.

2026. 03. 15

Automation Is a Contract, Not a Permission: Operator Agreements by Autonomy Layer

As agent automation expands, operator agreements matter more than model performance. Separate autonomy layers and specify authority, verification, and recovery responsibilities in each to gain speed and safety together.

2026. 03. 18

A Turning Point in Agent Operations: Change Control Windows for Runtime Changes

When models, prompts and tool configurations change daily, stability requires designing the timing and validation windows for changes rather than preventing change itself.

2026-09-01

Should an Agent Have the Authority to Refuse?

An agent that does as it is told is easy to manage. But it also faithfully executes flawed instructions. The real boundary of autonomy lies in what it can choose not to do, rather than only what it can do.