CreativeVerse: The Countdown Clock That Restarted Every Midnight
A fictional founder discovers that a countdown clock can lift immediate sales while quietly teaching customers not to trust the brand behind it.
Before You Buy AI Bookkeeping Software, Test the Reconciliation and Audit Trail
A practical buying guide to testing AI bookkeeping software for reconciliation, correction history, human review, data controls, full cost and exportability.
AI Can Click Through Scientific Software—but the Artefact Still Has to Prove the Result
A new benchmark shows why scientific AI agents should be judged by the files, plots, structures and measurements they produce—not by convincing interface activity.
Before You Buy a Customer-Service AI Agent, Test the Refund and Complaint Boundary
Before buying a customer-service AI agent, test its refund, cancellation and complaint boundaries, human handover, evidence trail and full operating cost.
Not Every Objection Is Resistance: Review Change Load Before Adding Another Tool
Before introducing another workplace tool or process, map the live change load, distinguish constructive objections from overload and protect stabilisation time.
Before You Buy an Online Course Platform, Test the Learner Exit
Before choosing an online-course platform, test learner-data exports, accessibility, completion evidence, consumer workflows and the real cost of leaving.
MentalHealthBench Tests More Than Crisis Safety—But It Cannot Measure a Therapeutic Relationship
OpenAI’s MentalHealthBench evaluates context, agency, urgency and empathy across 1,215 synthetic conversations—but a benchmark score is not proof of therapy or clinical outcomes.
Before You Buy an AI CRM, Test Consent Evidence, Exportability and Human Control
A practical buyer’s guide to testing whether an AI CRM preserves consent evidence, exports complete records, supports human review and reveals its full operating cost.
CreativeVerse: The Green Crown That Had No Receipts
A fictional founder learns that a beautiful green identity becomes fragile when its promise extends beyond the evidence beneath it.
AI Reliability Is Not One Accuracy Score: What Reliability Engineering Adds
A new preprint argues that reliable AI needs defined failures, operating conditions, repeated tests, exposure data, monitoring and recovery—not one benchmark score.