The State of AI Agents 

Autonomous agents have moved beyond prototypes. In production today, they rebalance treasuries, triage support queues at scale, and settle onchain payments when predefined conditions are met. The practical questions for 2025 are straightforward: where are agents already delivering value, and what is still preventing broader onchain deployment?

This article highlights the top agentic frameworks and how they are used in practice. It then outlines three blockers that keep most agent workloads off public chains and closes by explaining how SKALE addresses those blockers through private, gas-free, MEV-resistant execution and near-instant finality.

What is an “agent”?

An agent is software that observes signals, reasons with rules or AI models, and initiates actions autonomously. It can hold keys or credentials, follow explicit policy (limits, allowlists), maintain state over time, and operate across systems. In some contexts it calls APIs; in others it signs transactions. The common thread is persistent, policy-bound autonomy that gets useful work done without manual intervention.

The Top Agent Frameworks

1) Virtuals Protocol

Virtuals Protocol is an onchain platform for creating and coordinating AI agents that can own wallets, follow policy, and transact across EVM networks. Its Agent Commerce Protocol gives agents a standard way to discover one another, exchange value, and interoperate with smart contracts while keeping guardrails like spending limits and allowlists.

Teams use Virtuals to launch creator agents that manage research and subscriptions, DeFi helpers that route trades and pay fees, and game or social agents that act as persistent NPCs and curators. Builders typically combine onchain tokenomics with offchain runtimes so agents can monitor markets, post content, and settle payouts onchain without human intervention.

2) Coinbase AgentKit

Coinbase AgentKit is a developer toolkit that gives software agents safe wallet access and onchain capabilities. It is framework agnostic, so agents built with LangChain or OpenAI’s SDK can be granted crypto wallets and precise permissions to send funds, call contracts, and react to onchain events.

In practice, developers use AgentKit for agents that handle payouts, swaps and subscriptions, manage vault or treasury routines, and even perform small real world purchases with crypto. Hackathons and pilots commonly show an agent taking custody of a budget, enforcing policy limits, and executing a sequence of onchain actions while logging everything for audit.

3) ElizaOS

ElizaOS is an open source TypeScript framework for building autonomous, personality-driven agents that can think, remember, and act across many channels. It provides a unified message bus for Discord, Telegram, X, HTTP and even onchain endpoints, plus a simple “worlds and rooms” model for running swarms of agents that coordinate without extra glue code. A large plugin registry covers common tasks and integrations so teams can ship quickly without custom infrastructure. 

In practice, ElizaOS is used to deploy multi-platform social agents and community operators. For crypto-aligned use, a Coinbase plugin gives agents programmatic access to commerce and trading APIs, enabling payouts and onchain actions when needed.

4) LangChain

LangChain is an open source framework for building LLM-driven agents that reason over multi-step tasks, call tools, use memory, and orchestrate workflows. It provides modular building blocks and a large connector ecosystem so developers can move from prototype to production without rebuilding core agent patterns.

In production, companies use LangChain for internal copilots and assistants that triage support, generate reports from knowledge bases, run retrieval augmented research, and drive sales ops. Engineering teams lean on LangGraph style orchestration to keep long-running agent loops reliable, for example code review and data pipeline maintenance with human approval gates.

5) OpenAI Agents SDK

OpenAI Agents SDK is a lightweight toolkit for assembling GPT powered agents with tool use, handoffs between agents, and built in guardrails and session memory. The design favors a small set of primitives so teams can keep control over policy while still composing complex behaviors.

Real deployments include customer support agents that resolve tickets end to end, sales and success agents that enrich accounts and trigger follow ups, and back office automations that coordinate with calendars, docs, and CRMs. Many teams pair the SDK with durable execution backends so agents can resume long tasks after timeouts or restarts, and with payment or wallet modules when actions must move money.

6) Microsoft Agent Framework and AutoGen

Microsoft's stack provides a path from research to enterprise agents. AutoGen lets developers create collaborating agent teams such as Researcher, Coder, and Reviewer, while the broader Agent Framework and Semantic Kernel add stateful workflows, policy controls, and Azure native integration.

Organizations use these tools for multi agent coding assistants, data analysis playbooks, and process automations that span hours and multiple systems. Patterns like Coder plus Tester with human in the loop reviews are common, and Azure services supply identity, governance, and observability so agents can operate inside existing compliance boundaries.

7) Google Vertex and ADK

Google's Vertex and Agent Development Kit let teams design, govern, and deploy agents on Vertex AI with deep hooks into Google Cloud. Agents can be grounded on enterprise data, orchestrate tools like BigQuery and Apigee, and scale on GCP with standard security and IAM.

Enterprises use Agent Builder for customer support, contract and policy analysis, and operations assistants that search large internal corpora and take actions in business systems. Multi agent handoffs are used to pass work between specialized agents, for example routing a support workflow from a triage bot to a refund or compliance agent, all managed within Google’s governance guardrails.

Agentic Trends to watch

• From Helpers to Operators: Agents are shifting from chat interfaces to taking actions, owning tasks end to end, and escalating only exceptions.
• Policy-Bound Autonomy: Spend limits, allowlists, audit trails, and clear approval checkpoints are becoming standard so agents can act safely with real money and permissions.
• Privacy and Fair Execution as Requirements: Encrypted submission, MEV-resistant ordering, and near-instant finality are prioritized so strategies are not copied and multi-step plans do not strand funds.
• Bridging Offchain to Onchain: Toolkits that grant safe wallet access are turning traditional automations into end-to-end flows that include payments, contract calls, and agent-to-agent commerce (x402).

Onchain Agents And x402

Why Agents Should be Onchain

Onchain agents operate with programmable trust. Their actions and policies live in smart contracts, so custody rules, spend limits, and allowlists are enforced by code rather than by convention. Execution leaves an auditable trail, which helps teams review what an agent did and why. Composability lets agents plug into existing protocols for trading, lending, governance, or data access without custom integrations. Settlement is native and immediate at the protocol’s finality, which simplifies multi-step tasks like “sell here, repay there, then sweep to treasury.”

In short, being onchain gives agents verifiable control over assets, reliable automation, and open-market access that offchain systems cannot easily replicate.

How x402 Enables Agentic Payments on Blockchain Rails

x402 gives agents a simple way to pay and get paid. Services return a machine-readable “payment required” response that specifies amount, asset, expiry, and a callback for proof. The agent authorizes a stablecoin or token transfer on a low-fee chain, then posts the receipt to complete the request.

This pattern turns subscriptions, usage-based billing, micro-purchases, tips, and bounties into standard flows that any compliant agent can execute. With x402 as the payment layer for the internet and blockchains providing final settlement, agent-to-agent and agent-to-service commerce will become widespread.

‍

What is preventing agents from being deployed onchain?

Public mempools and MEV: When destination and calldata are visible before inclusion, adversaries can read an agent’s route and front run or sandwich the trade. That destroys expected P&L and deters serious deployments.

No programmable privacy: With calldata and state fully public, an agent’s policy and parameters are easy to copy or counter. Onchain transparency can also allow for agents to be doxxed.

Lack of near instant finality. Multi step plans span L2s, bridges, and offchain APIs. Probabilistic settlement and varying finality introduce race conditions and stranded half plans. Agents need a deterministic one block commit to coordinate safely across venues.

Why SKALE fits Agents and x402

Zero Gas Fees

SKALE’s gasless execution removes user-paid network fees, so x402 per-request payments aren’t swamped by gas overhead. That enables cents-level microtransactions for subscriptions, tips, and usage-based APIs, without cannibalistic fees

Single Slot Finality

Blocks finalize in one slot with deterministic inclusion, so an agent can chain actions (authorize payment, settle, post receipt) without MEV risk or long confirmation windows.

Privacy by Default with BITE Protocol

BITE encrypts to and data at submission and performs threshold decryption only after consensus, creating commit-then-reveal ordering. Agents can keep policy parameters and triggers sealed onchain, mitigate copycat behavior and frontrunning, and selectively disclose results or proofs as needed.

Dedicated Blockspace

Application-specific SKALE chains provide isolated throughput and predictable latency, preventing congestion from unrelated traffic. Teams can size a chain to expected x402 load or agent concurrency and maintain consistent SLOs for payment authorization and settlement.

Full EVM Compatibility

All SKALE chains are fully EVM compatible, so existing Solidity contracts, wallets, and tooling work without changes. Agent runtimes integrate via the usual libraries, and payment flows use familiar ERC-20 and contract interfaces.

Complex Settlement

While today, the exact schema requires explicit payments to be made; many organizations are collaborating on other schemes to allow for more dynamic payment situations like streaming, deferring, and more. SKALE is an ideal blockchain to bring more complex schemes since the smart contract execution cost doesn’t eat into the revenue of the micro-transaction.

SKALE on Base, built for agents and x402

SKALE on Base, part of the SKALE Expand initiative, is the first blockchain purpose-built for agents and x402 payments. The aim is to bring gas-free user transactions, near-instant finality, and private-by-default execution to an EVM environment (Base) that developers already know. It is an agent-centric chain intendedto  show how a purpose-built network for agents and x402 can sit alongside a major L2 and inherit familiar tooling and liquidity routes.

Whats Next for AI Agents

Agents are moving from clever demos to dependable infrastructure. The next phase will favor smaller, specialized models that call tools, shared standards for identity and payments, and clear policy controls so actions remain safe and auditable. Expect agents to operate across systems, pay each other for data and services, and hand off work when confidence is low or human approval is required. As privacy becomes practical and finality more predictable, agents will take on higher-value tasks in finance, operations, and customer service, measured by reliability and outcomes rather than novelty. The most durable progress will come from narrow use cases that expand over time, backed by strong observability, simple monetization, and guardrails that make autonomy trustworthy.

If you’re interested in building agents on SKALE, join the SKALE/FAIR builders group.