Measure AI Work at the Finish Line
AI can make a first draft arrive quickly while review, correction and integration grow. Measure accepted work—not generation speed—with a small paired-task trial.
The Best AI Meeting Note May Be the One That Expires
AI meeting tools turn one conversation into several durable records. An expiry ladder can preserve decisions and accountability without keeping every utterance forever.
The Emerging Economy of AI Agents: Who Pays, Who Gains, and Who Verifies?
From ResearchHub and Bittensor to Olas, Nevermined and Moltbook: eight experiments in exchanging AI work, data, attention and rewards—and the risks of mistaking transactions for trustworthy knowledge.
Before an AI Agent Acts, Ask for a Change Preview
An AI agent’s plan is not an exact preview of its actions. Test a workflow that binds approval to specific changes, detects stale versions and makes recovery limits visible.
The Best AI Answer May Begin With a Question
AI assistants often complete an underspecified task instead of exposing the missing choice. A one-question budget can reduce rework without turning every request into an interview.
Synthetic Users Are Hypotheses, Not Participants
AI personas can widen a design team’s hypotheses, but fluent simulation is not lived evidence. Compare synthetic predictions with real observations before using them to decide.
Explore, Understand, Shape: A Knowledge Map for Humans and AI
Alkemata opens its Knowledge Map preview on 3 October 2026: a visual landscape for exploring connected topics, building understanding with AI and turning discoveries into action.
Alkemata for AI: What Capsules, llms.txt and MCP Are Actually For
Alkemata now exposes articles to AI in several different ways. Here is when a normal webpage is enough, what capsules add, how llms.txt and MCP differ, and how readers and…
An AI Memory Should Come with an Expiry Date
Persistent AI memory saves repetition but can preserve stale assumptions. Build a Memory Boundary Card to govern purpose, source, correction and expiry.
Do Not Make Human–AI Agreement the Goal
Human–AI agreement can hide anchoring or stubbornness. A better workflow preserves both provisional views, examines divergence and records why judgement changed.