Kaia

share the joy | @RialoHQ @SeismicSys @axisrobotics @0xfairblock lover
traditional artist, bringing Web3 stories to life on paper

Discord: _bettermee

[Kaia @_bettermee]

In the previous post, we talked about why automation alone isn’t enough for AI agents.

If AI is going to handle real economic tasks, its work must be verifiable.
That’s where SCALE (Simple Contracts for Agent Labor Execution) from @RialoHQ comes in.

SCALE connects three elements in one structure:
• Task
• Payment
• Proof

When a job starts, the reward is locked in on-chain escrow.
Payment is only released if the result passes verification.
But this raises an important question:
Who verifies the result?
If humans had to check every task, the system would quickly become inefficient.

Rialo’s answer is simple:
another AI agent acts as the judge.
This role is called the Judge Agent.

For example, a user might request:
“Generate a cyberpunk-style cat image.”
Once the request is made, the system automatically:
1️⃣ Finds an AI image agent from the Agent Registry
2️⃣ Creates a SCALE contract including the prompt, reward (RLO), deadline, and Judge Agent
3️⃣ Locks the reward in escrow

The worker agent then generates the image and submits the result on-chain.
But the payment still isn’t released immediately.
The Judge Agent reviews the output to check whether it matches the prompt and meets the required conditions.
• If the result passes, the reward is released.
• If it fails, the escrowed funds are refunded.
The entire process happens automatically:

AI creates the task → AI performs the work → AI verifies the result → the blockchain enforces the contract.

This model opens the door to a new AI agent economy, where different roles can emerge:
• Worker Agents that perform tasks
• Judge Agents that evaluate results
• Coordinator Agents that connect multiple agents

Rialo is building infrastructure for this kind of agent collaboration.
One last question remains.
What happens if an agent misses the deadline?
Instead of relying on manual transactions, Rialo introduces Native Timers to handle these situations automatically.

We’ll explore that in the next part.
@itachee_x
@dj673285379
@LinYue93820

[Kaia @_bettermee]

AI agents are moving beyond chatbots.

Soon they won’t just answer questions — they’ll handle real tasks like booking flights, making purchases, or managing payments while we sleep.

But that creates a new problem.

What happens if the AI makes a mistake?

Maybe the payment goes through but the flight isn’t booked.
Maybe the wrong item gets purchased.
Or worse, money moves and nothing actually happens.
The biggest issue is that failures like this are often silent.
As @RialoHQ pointed out:
Automation without verification doesn’t scale — it just quietly breaks.
The root problem is that in most systems three things are separated:

• the task
• the payment
• the proof the work was done

When these are disconnected, it becomes hard to know where things went wrong.

Rialo’s answer is SCALE (Simple Contracts for Agent Labor Execution).
SCALE connects task, payment, and verification into one system.
The task is defined, the payment is locked in escrow, and the result must pass verification before funds are released.

No chasing logs.
No guessing what happened.

If AI agents are going to participate in real economic activity, automation alone isn’t enough.

It needs verifiable execution.

And that’s exactly what SCALE is designed to provide.

@itachee_x
@dj673285379
@rialo_zw

[Kaia @_bettermee]

Builders Hub Recap @RialoHQ

This week's Builders Hub featured two projects tackling very different but equally important problems.

🔹 Rialo Signal aims to bring fragmented crypto data into one place. Instead of switching between multiple tools, users can analyze wallets, track on-chain activity, manage portfolios, and even automate actions through AI-powered workflows.

🔹 EscrowMAD focuses on trust in P2P transactions. By using smart contracts, deposits, and transparent dispute resolution, it creates a safer way to buy and sell directly online without relying on intermediaries.

What stood out to me is that both projects are solving real-world issues: one improves how we access and act on information, while the other improves how strangers can transact with confidence.

And to top it off, Eric hinted that a major announcement could be coming soon 👀

Looks like the next few weeks at Rialo will be very interesting.

@itachee_x
@ericargent31113
@firearrowmage

[ade | rialo.io @itachee_x]

Latch is coming.

Tomorrow at 16:30 UTC (12:30PM ET) I'll be on the Rialo Discord stage talking through why agents need new primitives

Latch gives agents real authority, with proper oversight, enforced in hardware, with deep audit trail

Bring questions
https://t.co/BtYLOQoLvH

[Kaia @_bettermee]

👏 Another week, another group of contributors making a difference.

From helpful discussions to consistent participation, this week's @RialoHQ highlights remind us that every contribution counts.

Whose name are we celebrating next week? 👀

[ade | rialo.io @itachee_x]

Interesting conflict going on here:
1. We want agents to be able to call our APIs
2. We also don't want spam

Traditionally people used captcha for (2) but this blocks agents.

How are people making sure only "verified" agents can use an API?

What even is a verified agent?

[ade | rialo.io @itachee_x]

Testing out https://t.co/BtYLOQoLvH policy engine
Going flawlessly 🚀

Latch now supports Cedar policies and spend limits on agent.

[Kaia @_bettermee]

Looking at @RialoHQ in 2026, what stands out to me is that the project is moving far beyond the idea of being just another high-performance chain.

The focus seems to be converging around three themes: AI, real-world integration, and automation.

From SCALE-powered AI activities to discussions around oracles, security, compliance, and Native Web Calls, the ecosystem is increasingly centered on solving practical problems rather than chasing benchmark numbers.

What I find most interesting is how different pieces fit together:
▪️ AI-driven automation
▪️ Real-time external data access
▪️ SFS-based gas abstraction
▪️ Compliance and security integrations
▪️ AI agent economies

As regulation and AI-powered monitoring continue to expand globally, infrastructure that can bridge blockchain systems with real-world requirements may become increasingly valuable.
In the long run, the biggest question may not be who has the highest TPS, but who can connect real-world data and autonomous agents into a usable economic system.
That's one reason why Rialo continues to catch my attention.

@itachee_x
@ericargent31113
@firearrowmage

[Kaia @_bettermee]

One aspect of @RialoHQ that I find interesting is how compliance and security can be integrated directly into onchain workflows.

Using Native Web Calls, applications could combine IP-based policies, sanctions screening, and security checks within a single execution flow.

For example:

▪️ Restrict access from specific regions
▪️ Apply different gas sponsorship limits by jurisdiction
▪️ Filter sanctioned users automatically
What makes it more compelling is that AI can go beyond simple IP checks by analyzing unusual behavior patterns, such as suspicious location changes or potential VPN usage.
To me, this reflects a broader vision: combining real-time data, AI, and compliance tools to support real-world applications where security and regulatory requirements matter just as much as user experience.

@itachee_x
@ericargent31113
@firearrowmage

[Kaia @_bettermee]

A lot of blockchains still feel like they're primarily built for crypto interacting with crypto.

What makes @RialoHQ interesting to me is that the focus seems to be on connecting blockchain infrastructure directly to the real world.

Not just another Layer 1, but a network designed around real-world data, applications, and automation.

Instead of relying entirely on external middleware, Rialo is building toward protocol-level access to things like financial APIs, credit data, live events, and other offchain information.

A few pieces of the vision that stand out:

▪️ Native Web Calls for real-time data access
▪️ Event-driven automation that reacts automatically to external conditions
▪️ Infrastructure designed for AI agents and autonomous workflows
▪️ SCALE, a framework for AI-powered labor and coordination
▪️ Fast execution with 50ms block times and parallel consensus
▪️ Compatibility with both RISC-V and Solana VM environments
▪️ User-friendly features like email login, 2FA, and scheduled payments
To me, the end goal seems clear:
Build applications where users benefit from blockchain infrastructure without constantly being reminded they're using a blockchain at all.

@itachee_x
@ericargent31113
@firearrowmage

[Kaia @_bettermee]

One thing I find interesting about @RialoHQ's security model is that it isn't based on a simple "flag = block" approach.

Different security sources can produce different results. Instead of relying on a single API, Rialo can combine multiple signals and use risk scoring to make more informed decisions.

A wallet flagged by one source but cleared by others doesn't necessarily need to be blocked immediately.

With Native Web Calls and REX, this kind of multi-source verification can happen directly within the execution flow.

To me, the goal isn't maximum restrictions—it's finding the right balance between security and false positives through real-time, data-driven decisions.

@itachee_x
@ericargent31113
@firearrowmage

[Kaia @_bettermee]

When people talk about RWA, the conversation usually focuses on tokenization.

What interests me about @RialoHQ is that the vision seems bigger than simply putting real-world assets onchain.

The real challenge for RWA isn't creating tokens—it's connecting reliable, up-to-date real-world data to those assets.

Most RWA systems depend heavily on oracles, which often introduce delays, additional trust assumptions, and extra infrastructure layers.

Rialo's Native Web Call architecture takes a different approach by allowing applications to access external data directly during execution.

Property valuations, collateral status, market activity, financial records—these are the types of inputs that could be integrated into smart contract logic in near real time rather than waiting for periodic updates.

Combined with technologies like Proof of Reserve, MPC, and decentralized identity, this could improve transparency, automate verification processes, and reduce information gaps between participants.

To me, the interesting part isn't asset tokenization itself.

It's the possibility of building RWA applications that can continuously react to real-world conditions instead of operating on delayed snapshots of data.

There are still regulatory and legal challenges that technology alone can't solve.

But from an infrastructure perspective, this feels like a meaningful step beyond the traditional oracle-centric model.

@itachee_x
@ericargent31113
@firearrowmage

[Kaia @_bettermee]

When people talk about onchain security, GoPlus Security is often the first name that comes up.

But what I find interesting about @RialoHQ is that its Native Web Call architecture isn't tied to any single security provider.

Developers can pull data from a wide range of sources—block explorers, reputation databases, compliance tools, community-maintained blacklists, or any external endpoint that fits their use case.

For example, when a dApp offers gas sponsorship through SFS, an AI agent could query multiple sources simultaneously, compare results, and build a more complete risk assessment before approving execution.

What stands out is the flexibility.

Rather than forcing developers into a predefined security stack, Rialo appears to give them the freedom to compose their own security workflows using the data sources they trust most. Even community-maintained datasets hosted publicly can become part of the decision process.

To me, this feels like a shift from static security rules toward programmable security.

As AI, external data, and onchain execution become more tightly connected, the security layer itself starts becoming dynamic and adaptive.

And that could unlock some really interesting applications—not just in security, but also in areas like AI agents, prediction markets, and real-time gaming.

@itachee_x
@ericargent31113
@firearrowmage

[Kaia @_bettermee]

One thing that stood out to me about @RialoHQ's Native Web Call architecture is that strong onchain security doesn't necessarily have to rely on expensive enterprise solutions.

With access to public and low-cost data sources—such as GoPlus Security, community-maintained blacklist databases, and public wallet labels from explorers—AI agents can pull in security intelligence directly during execution.

Imagine a gas sponsorship request being submitted through SFS.

Instead of blindly approving it, the system could query multiple data sources in parallel, analyze risk signals, and make a decision based on a broader security picture before execution even happens.

What I find particularly interesting is the ability to cross-check information from different sources rather than relying on a single blacklist.

Thanks to the combination of Native Web Calls and asynchronous execution, security workflows can become much more dynamic and data-driven while remaining part of the onchain process itself.

Traditionally, building something like this would require separate backend services and centralized infrastructure. Rialo's approach seems to bring much of that logic directly into the execution layer.

Starting with free and open security data, then expanding into specialized services through an AI agent marketplace, feels like a practical path toward more accessible and scalable Web3 security.

Definitely a design direction worth watching.

@itachee_x
@ericargent31113
@firearrowmage

[Kaia @_bettermee]

What makes @RialoHQ's SFS (Stake for Service) model stand out to me is that it goes far beyond simple gas sponsorship.

The idea seems to be creating a unified credit layer for network services.

When a builder stakes $RIALO, they receive Execution Credits that can be used not only for transaction execution, but also for things like external API requests through Native Web Calls, asynchronous workflows, and even security-related operations that depend on external data sources.

That changes the developer experience significantly.

If an application needs real-time data feeds, AI-powered risk analysis, or additional security checks, those services can be integrated into the workflow without constantly thinking about separate transaction costs for every action.

Most blockchains are built around charging for transactions.

Rialo feels like it's being designed as an execution platform where computation, data access, automation, and security are all part of the same service layer.

What's especially interesting is how this could evolve alongside AI agents. If agents, external data, automation, and security mechanisms all operate through the same credit-based system, it starts to look less like a traditional blockchain economy and more like infrastructure purpose-built for AI-native applications.

Definitely one of the more interesting design choices I've come across recently.

@itachee_x
@ericargent31113
@firearrowmage

[Kaia @_bettermee]

Tune in to @RialoHQ Builders Hub!👏

Hundreds of creators across the globe unite here to brainstorm and explore new developments. Let’s create the future together — join Discord now!

[Kaia @_bettermee]

Spotlight Week is here ✨

This week's featured members earned their place through consistent effort, thoughtful contributions, and support for the wider @RialoHQ community.

Every answer, every discussion, and every helping hand adds value.

Big respect to everyone making an impact behind the scenes.

Who's making the next Spotlight list? 👀

[ade | rialo.io @itachee_x]

As Mythos drops today, we are testing out the performance of Latch.

So far without much optimization, it only adds < 100ms @ 1k TPS per node.

Our goal is single digit ms.

Good thing is scales horizontally!

Sign up for beta 👉 https://t.co/BtYLOQoLvH

[Kaia @_bettermee]

Spotlight Week is here ✨

This week's featured members earned their place through consistent effort, thoughtful contributions, and support for the wider @RialoHQ community.

Every answer, every discussion, and every helping hand adds value.

Big respect to everyone making an impact behind the scenes.

Who's making the next Spotlight list? 👀

[Kaia @_bettermee]

@Ceee_jeay @RitaCryptoTips @encrypt_wizard @RialoHQ @rialo_africa grialo

[Kaia @_bettermee]

One thing I find particularly interesting about @RialoHQ is how its AI security model can extend beyond the network itself.

Rather than relying solely on internal activity, Rialo's architecture could leverage external security intelligence from across the crypto ecosystem. Think OFAC sanctions lists, Chainalysis data, or known malicious wallet databases maintained by major protocols.

With Native Web Calls, that information can be pulled into execution in real time. When a gas sponsorship request is submitted, the system can instantly evaluate the wallet's risk profile before granting access.

What stands out to me is that the vision goes beyond simple blacklist checks.

By combining data from multiple chains, AI agents could identify suspicious relationships, funding paths, and behavioral patterns connected to known bad actors—even when a wallet itself hasn't been explicitly flagged yet.

That moves security from reactive filtering to proactive risk assessment.

If Native Web Calls, AI-driven analysis, and SFS come together successfully, Rialo could evolve into something more than a gasless UX layer: a security infrastructure that continuously learns, adapts, and benefits from intelligence across the broader blockchain ecosystem.

@itachee_x
@ericargent31113
@firearrowmage

[Kaia @_bettermee]

Another aspect of @RialoHQ's AI security model that caught my attention is its potential to learn beyond its own network.

Most attackers don't operate on a single chain. The same bot operators and Sybil farms often reuse wallet creation patterns, funding routes, and behavioral strategies across multiple ecosystems.

Instead of analyzing activity in isolation, Rialo's vision appears to be leveraging cross-chain intelligence to identify risk signals earlier and build a broader understanding of attacker behavior.

What makes this even more compelling is the combination of Native Webcalls and verifiable data sources. External blockchain data can be pulled into execution, while attestation mechanisms help ensure the information being used is trustworthy before it reaches AI-driven decision systems.

To me, this points toward something bigger than traditional chain security.

Rather than defending one network at a time, Rialo is exploring what a shared security intelligence layer could look like—one that continuously learns from activity across ecosystems and adapts as attack patterns evolve.

That's where the AI + blockchain combination becomes truly interesting: not just automation, but adaptive defense.

@itachee_x
@ericargent31113

[Kaia @_bettermee]

@itachee_x everything possible

[ade | rialo.io @itachee_x]

The crypto talent exodus is crazy.

Will we ever recover from this?