AI steps on the trade floor. Not as software, but as an actor. Agents do not just analyze markets, they strike agreements, set terms and move capital over decentralized rails where the settlement is final. For institutional crypto tables, it means faster trades, better products and brand new exposures.
Now imagine two agents negotiating a derivative contract but registering different numbers. One book $ 100 million, the other $ 120 million. Who is responsible when the gap triggers failures or studies? This is not theory, it is the reality of the agent’s era. AI learns, deals and trades in financial systems where even small discrepancies can create systemic risk.
But there is a growing problem: agents could act on fake or non -verifiable data with real consequences. An AI system used by Britain’s national healthcare provider, incorrectly diagnosed with a patient, with reference to a fictitious “health hospital” with a false mail code. As we move beyond basic automation, we need systems that are rooted in verifiableness and accountability. Like the Internet needed HTTPS, Agentic Web needs a trusted network.
Without a shared memory (also called Ledger)Agents diverges. Contributing items create errors. Without auditing paths, they become opaque, inconspicuous, non -confidence and consequently unsuitable for business use.
Financing is a clear example. Imagine two AI agents negotiating an inter-bank derivative contract. One records $ 100 million; the second, $ 120 million. This gap of $ 20 million can trigger payment errors, regulatory actions or major reputation. With billions in contracts traded globally every month, even small discrepancies create systemic risk.
This is not a distant scenario. The infrastrstructure can already exist. To navigate the agent’s era, we need a foundation that is built on three core layers:
- Decentral infrastructure: Eliminates single checkpoints that ensure resilience, scalability, but most importantly sustainability, in addition to relying on single private units to run the entire stack.
- A layer of trust: Embeds verifiableness, identity and protocol level consensus, enabling reliable transactions across jurisdictions and systems.
- Confirmed, reliable AI agents: Enforce origin, attesting and accountability, which ensures that systems remain revised and enable these agents to act on our behalf.
Decentralized networks need to anchor this stack. Agents need systems fast enough to handle thousands of transactions per day. Second, identity frames that work across boundaries and logic that allow them to collaborate and work together not just exchange data.
To operate in shared environments, agents need three things:
- Consensus (Agree on what actually happened)
- Provenance (Identify who initiated or affected it and who approved it)
- Auditability (Track each step easily)
Without these, agents can behave unpredictably across disconnected systems. And since they are always on, they must be sustainable and trust in design.
To meet this challenge, companies must build on systems that are transparent, auditory and resilient. Politicians must back open source networks such as the backbone of trusted AI. And ecosystem managers and builders must design confidence in the foundation and not bolt it later.
Agentic era doesn’t just get automated. It will be negotiated, composed, responsible … and trusted if we choose to build it that way.
