AI Engineering
Reliable agents need operating boundaries
A capable model is one part of a dependable system. The harder work is defining what success, recovery, and a safe stop actually mean.
Metrosion / Articles
A closer look at the decisions behind dependable AI. Research, engineering, and a considered point of view.

Featured perspective / AI Engineering
A capable model is one part of a dependable system. The harder work is defining what success, recovery, and a safe stop actually mean.
Read the articleThe reading room
Engineering insight.
Useful beyond the headline.
AI Engineering
A capable model is one part of a dependable system. The harder work is defining what success, recovery, and a safe stop actually mean.
Quality & Evaluation
An AI evaluation should tell you whether a business task succeeded, where it failed, and whether a change is safe to release.
Security
Connecting an agent to tools is easy to demonstrate. Making those connections accountable requires careful identity, authorization, and isolation.
Software Delivery
When producing code becomes faster, trustworthy review depends on smaller changes, clearer evidence, and attention to consequential decisions.
Data & Architecture
A useful answer is only trustworthy when every source behind it was available to the person asking the question.
Human Systems
A confirmation button provides little protection if the person cannot understand the action, its evidence, or what will happen next.
Reliability
Token counts and response times are useful signals. They become actionable when connected to task outcomes, dependencies, and human recovery.
AI Economics
The cheapest model call can create the most expensive workflow when retries, review, and incorrect actions are included.
Governance
Policies become useful when teams can show how a real AI workflow is owned, evaluated, authorized, and changed.
Architecture
An agent that waits, retries, and touches external systems needs durable state and explicit recovery semantics as much as it needs reasoning.
Our editorial approach
We connect primary research and technical developments to decisions that matter in practice. Each article links to its sources and separates reported findings from our analysis.