A customer-service agent goes live and works through tens of thousands of conversations. Then an auditor asks one specific question: was this refund approved by the agent itself, or did someone authorise it?
Continue reading The Agent Economy: What Has to Be in Place Before Agents Act on Their Own
On the night before launch, the last load test most teams run is not for a benchmark; it is to answer one question: if traffic triples tomorrow, in what way does the system break?
Continue reading Parallel Chain Engineering: From Running to Enduring
Paralism took part in WebX 2026 in Tokyo. One shift in the programme was plain: AI-related topics moved from side sessions onto the main stage, and they no longer stayed at the level of model capability.
Continue reading At WebX 2026, Determinism Becomes the Shared Premise
The internet’s greatest success was making information nearly free: a piece of text, a photograph, a set of data can cross the globe in seconds. Its greatest failure lies in the same place — information can flow freely; value cannot.
Continue reading Value Interconnection: From the Information Internet to the Value Internet
Joining a network usually starts with a form: submit documents, wait for approval, accept a long list of terms. Once approved, you still do things its way — not because it is more reasonable, but because it holds the door.
Continue reading Permissionless, Customizable, and Order Without an Arbiter
A cosmetics package carries a QR code; scan it and a clean journey unfolds — ingredients, factory, testing, logistics, shelf. The information is complete and well presented. Anyone who knows the field still asks one more question: who wrote these words in, and can they still be changed afterwards?
Continue reading Supply Chain Traceability: Why On-Chain Data Can Be Trusted
A demo can be applauded; a decision has to be signed. In almost every review meeting about putting AI to work, the proposal is presented, the results are encouraging, and then someone asks — if it gets something wrong, who is responsible? The room goes quiet and the project stops there — a scene repeated often enough to be no longer technical but organisational: signing means having grounds, a responsible party and a record, and today’s large models are empty on all three.
Continue reading The Engineering Prerequisites of Trustworthy AI
Enterprises run AI pilots far faster than they put AI into production. The sticking point is usually one question — if it gets something wrong, who is responsible? A demo can be applauded; a decision has to be signed. A result that cannot be signed does not reach production.
Continue reading What Is Deterministic AI? From Demo to Sign-off
Paralism was invited to Consensus in Hong Kong. The most visible change from previous years is who was in the room: the share of institutions and industry participants rose sharply, and much of the discussion happened not on the exhibition floor but in meeting rooms and on compliance teams’ agendas.
Continue reading At Consensus Hong Kong, Institutions Vote for Trusted Infrastructure
Two institutions want to build a joint risk model. The proposal is elegant; legal reads it and sends back one line: the data cannot leave our systems. The project stops at the whiteboard.
Continue reading Data Sovereignty: Usable Without Being Exposed
