AI
Models, agents and the decisions that turn AI research into useful products.

Data Provenance in RAG Answers: What a Citation Proves
A citation points to a passage. Provenance also records which document version was used and who published it.

MCP authorization: who can access an agent's tools
A closer look at access tokens, operation permissions and user consent in MCP connections.

The AI Research Stack: What Small Teams Actually Need
A source library, a repeatable question and a way to check the answer are a useful place to start.

Agentic Workflows: Where They Earn Their Keep
An agent earns its place when the task needs decisions that a fixed sequence cannot sensibly anticipate.

When an AI Product Needs a Human in the Loop
Human review works best when it happens at a decision someone can still understand and change.

The Cost of Intelligence Is Moving to Operations
The useful unit is the cost of an accepted result, including the work needed to correct and maintain it.

Open Models, Closed Advantages: What the New Divide Looks Like
A downloadable model changes what a team can control. It does not settle who owns the rest of the system.

GPT-5.6 Makes Model Choice a Workload Decision
OpenAI's three-model launch puts task difficulty and the cost of checking results into the same conversation.

Gemini Omni Makes the Video Edit a Conversation
Google's new video model accepts mixed references and follow-up edits, changing how a creative brief can develop.

Claude Opus 4.6 Takes on Longer Pieces of Work
A larger context window and new agent features expand the work Claude can attempt, with review still essential.

Gemini 3 Arrives With a Wider Research Brief
Google's new model preview spans text, images and video. The useful test is whether its answers stay traceable.
The AI desk explains how models and agents behave inside real products and workflows, what they cost to run and where human review still matters, with sources linked beside each claim. Dated events are collected under AI news.
