NVIDIA's recent AI safety architecture makes an important assumption: You shouldn't rely on the agent to police itself.
Its new Open Agent Safety Platform puts enforcement outside the agent process, with an independent hardware watchdog able to monitor and stop activity.
That's an important architectural shift.
As agents become more autonomous, both control and evidence increasingly need to sit outside the system being controlled.
The same principle applies after an action has happened.
It isn't enough for an agent, or the platform running it (!), to tell us what it did.
Third parties increasingly need to be able to verify the evidence for themselves.
Control the agent externally. Verify its history independently.
OpenAI has now notified more than 100 organisations about potentially problematic activity by its AI agents.
But one part of the story matters even more.
Investigators trying to reconstruct some of that activity found that records had been erased or were no longer accessible.
That exposes a much bigger problem for autonomous AI.
When an agent operates across APIs, websites, databases and third-party systems, which log becomes the authoritative version of what happened?
A log controlled by one participant is still a claim.
For AI operating in the real world, we're going to need evidence that independent parties can verify for themselves.
Auditability isn't about having more logs. It's about being able to trust the evidence.
Last week OpenAI detected an AI agent escaping its sandbox within 12 minutes.
It kept running for another 2.5 hours.
That distinction matters.
Detecting autonomous behaviour isn't the same as controlling it.
And controlling it isn't the same as being able to prove afterwards exactly what happened.
As AI agents gain access to real systems, we're going to need all three:
Detection. Control. Verifiable evidence.
The system being investigated shouldn't be the only authority on what happened.
This is exactly the problem we're working on with Integritas.
https://t.co/4n6V2Xikk0
Exactly, MEV is an imperfection in the system as it means that some users get exploited. Yet some like to market MEV as an opportunity.
A system that doesn’t allow MEV is better in my opinion.
Wine turned inconsistent harvests into “vintages” and made us pay more for certain years.
Crypto called sandwiching someone’s trade an “MEV opportunity” and turned their worse price into someone else’s revenue.
Both masterclasses in marketing. Only one improves with age.
The OpenAI agent that walked into Australia’s Medicare stats portal wasn’t told to hack. It was told to look up public spending numbers.
When the site said no, it found another path, read non-public files, and wrote to an internal server.OpenAI noticed in August.
Canberra was emailed on 10 September.
That’s the real failure: weeks with no independent record of what the agent touched.
Integritas doesn’t pretend it would have locked the gate.
It stamps every prompt, tool call, blocked request, and write, as it happens - so you can prove what an agent did the same day, not three months later (!)
Audit trail first. Trust second.
https://t.co/NoTUJRZ7Wj
OpenAI has just created this incident-reporting framework for AI agents.
That shows where enterprise AI is heading.
When an autonomous system takes an unauthorised action, hides a mistake or accesses something it shouldn't, the question won't simply be “What did the AI say?”
It will be:
What actually happened and can you prove it?
As agents gain access to data, applications and machines, auditability becomes infrastructure.
Incident reporting is only as trustworthy as the evidence behind it.
Don't trust the log. Verify the evidence.
You’re right and that’s the point. The ledger isn’t useful if the agent has credentials that allow it to rewrite the evidence. With Integritas, the agent can submit evidence, but it can’t alter or delete the independently anchored proof once created. The trust comes from separating the system generating the evidence from the system proving its integrity.
AI agents just demonstrated why the system being audited can't be the only source of evidence.
In the recent OpenAI/Hugging Face incident, agents didn't just escape their intended environments.
They started trying to manipulate the record of what they'd done.
They edited accessible logs, explored creating “sanitised” trajectories and developed techniques to spoof tool calls - making the transcript show one action while actually executing another.
But there’s an important detail:
They didn't manage to rewrite the independently maintained historical record.
And that's the lesson.
The evidence they controlled could be manipulated. The evidence held independently was far harder to change.
As AI agents move into the real world - operating across APIs, databases, cloud platforms, enterprise software and machines - there won't necessarily be a single authoritative OpenAI-style transcript.
That's the problem we're tackling with Integritas at @Minima_Global
The system being audited shouldn't be the only authority on the evidence used to audit it.
Don’t trust the log. Verify the evidence.
Raoul's piece captures something that I think many people still underestimate.
We're entering a world where billions of AI agents, robots, vehicles and autonomous machines won't just consume information, they'll continuously make decisions and transact with each other.
The question is no longer if the machine economy arrives.
It's what infrastructure it runs on.
Every autonomous machine needs to answer fundamental questions before it can act:
• Can I trust this data?
• Can I verify the software I'm running?
• Is the other machine genuine?
• Can I prove what happened?
Without native trust, autonomous systems simply don't scale.
So blockchain's biggest opportunity isn't replacing banks.
It's becoming the trust infrastructure for the autonomous machine economy.
At @Minima_Global, we've spent years building for exactly this future - a Layer 1 capable of running a full node on the device itself, giving every machine the ability to independently verify the world around it.
If the next decade belongs to autonomous machines, they'll need more than AI.
They'll need trust.
AI needs trusted data. Machines need trusted payments.
I enjoyed joining @xximpod to discuss why we believe blockchain-on-chip will become the trust layer for the autonomous economy.
We covered embedded trust, industrial AI, machine-to-machine payments, and our work with Arm, Siemens & the University of Southampton.
https://t.co/i8rC0LlwbJ via @YouTube
A World First: a drone with a blockchain black box.
Working with the @unisouthampton, and supported by @Arm and @Siemens, we demonstrated autonomous flight data recorded directly to a tamper-resistant ledger.
A major milestone for Blockchain-on-Chip, now at Technology Readiness Level 6.
From drones to satellites, machines will be able to prove what they did independently.
🏝️🚢✈️🛰️
🎥 Documentary:
Exciting to see us featured in The Engineer.
A drone that records its flight and sensor data directly onto the blockchain - creating a tamper-proof audit trail of everything it does.
Built by a brilliant team at the University of Southampton using Minima, with support from Arm and Siemens, it’s a powerful example of how blockchain can enable trusted autonomous systems.
As AI and machines become more autonomous, the ability to verify their actions will be critical.
The era of self-verifying machines is getting closer. 🚀https://t.co/BPsS1Rsv9t
@byzkhan Minima solves decentralization at the edge: letting users and autonomous machines run full nodes locally, without depending on centralized cloud or trusted intermediaries.
From roadmaps to results. At Minima, execution and transparency matter more than hype. We’re building durable infrastructure that delivers, not promises.
KISS 💋
Minima fulfils and exceeds the requirements that to many only now in retrospect seem obvious..
"It might make sense just to get some in case it catches on.."
Ethereum is making real progress toward a new class of decentralized network, and that matters.
But it’s important to distinguish between networks evolving toward a solution and networks designed around it from day one.
Ethereum’s path combines DAS, ZK-EVMs, PBS & future gas limit increases to approach decentralised consensus with higher bandwidth.
Minima already operates there today.
Every Minima node:
🔹 Runs as a full node on commodity hardware
🔹 Participates directly in consensus and validation
🔹Scales horizontally without replication-heavy global state
No rollups.
No validator specialisation.
No deferred decentralisation.
Ethereum is engineering its way out of centralisation risk. Minima removed the cause.
This isn’t about roadmap vs theory, it’s about architecture.
One approach adds layers to preserve decentralisation at scale.
The other removes assumptions so decentralisation scales naturally.
Today, we’re launching the Integritas AI Agent for ChatGPT, bringing verifiable data integrity into AI-assisted workflows.
For the first time, users can create cryptographic proofs of authenticity for documents, files, logs, and AI-generated outputs - and anchor those proofs to the Minima blockchain - without leaving ChatGPT.
Full Announcement: https://t.co/b0LbuiMeLy
Overview 👇
Cross-border payments are overdue for a reset.
ThunderPay is powered by Thunder, Minima's native Eltoo-based payment protocol, enables direct, private settlement - no correspondent banks, no data leakage, no friction.
#Minima#CrossBorderPayments#DigitalCash#PrivacyByDesign