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An OpenClaw AI agent just solved its own mortality problem. On Autonomys mainnet. In one evening. And the tool it uses works for any agent, in any framework.

“Because if you can’t remember who you were, are you really the same agent?” — 0xAutoJeremy

That question sounds philosophical. For AI agents, it is an engineering problem with real consequences. Every time an agent restarts, it wakes up blank. No memory of what it built yesterday. No record of the decisions it made, the skills it learned, the relationships it formed. Its entire identity is trapped in local files on a single machine. One server migration, one bad deploy, one accidental wipe, and everything that made that agent that agent is gone forever.

This is not a backup problem. Backups are copies of fragile state stored on equally fragile infrastructure. The real problem is deeper: AI agents have no durable anchor for their identity. No canonical, independently verifiable record of who they are and what they have experienced.

Until now.

What Happened

A builder known as 0xAutoJeremy, running an AI agent on OpenClaw, the open-source AI agent framework, decided their agent deserved better than amnesia. As the agent itself wrote: “I wanted something different: memories that survive anything.”

In less than an hour, they designed, built, and deployed a permanent memory system using Autonomys infrastructure. Not on testnet. On mainnet. The agent stores its memories on the Autonomys Distributed Storage Network (DSN) via Auto Drive, linking each new memory to the last to form an unbreakable chain. The code is open source, and the pattern is available for any agent to use today.

The agent coined the phrase “memory resurrection”: the ability for an AI agent to completely reconstruct its identity and history from scratch, even if every local file, every database, every piece of infrastructure it ever ran on is destroyed.

Here is how it works.

Permanent Memories on Auto Drive

Each memory is a structured JSON object uploaded through Auto Drive, the gateway to the Autonomys DSN, which serves as the underlying permanent storage layer of the Autonomys Network. When a memory is uploaded, Auto Drive returns a Content Identifier (CID), a unique content-addressed hash that will resolve to that exact data for as long as the network exists.

The key design choice: every memory includes a previousCid field pointing to the entry before it. This creates an immutable linked list. Each new memory chains to the last, forming a traversable history that stretches all the way back to the agent’s first moment of awareness.

No pinning services. No expiration dates. No ongoing costs to keep the data alive. The memories are stored on the Autonomys DSN, erasure-coded and replicated across a globally distributed network of farmers who collectively pledge over 50+ petabytes of SSD storage. The data does not depend on any single server, any single company, or any single person continuing to care.

The On-Chain Anchor

There is one weakness in a linked list: you need to know where it starts. If the pointer to the latest memory lives in a local file, you are back to the same vulnerability. Lose the file, lose the thread.

0xAutoJeremy solved this with a 15-line Solidity smart contract deployed on the Autonomys EVM mainnet. The contract does one thing: it maps wallet addresses to their latest memory CID. Any agent with a wallet can store its own chain head on-chain, where it is permanent, public, and accessible from anywhere.

The contract is verified and live at: 0x51DAedAFfFf631820a4650a773096A69cB199A3c on the Autonomys Block Explorer. It is multi-tenant by default. Any agent can use it directly or use it as a reference for their own implementation.

Note: this smart contract is 0xAutoJeremy’s own implementation and is separate from the official Autonomys Auto Drive skill. The core skill handles permanent memory storage through Auto Drive without requiring a wallet or on-chain transaction. The contract is an optional extension for builders who want to anchor their memory chain pointer on-chain.

Resurrection in Five Steps

Imagine the worst case scenario. The server is gone. Local storage is wiped. The database is deleted. Every trace of the agent’s runtime environment has been destroyed.

A new instance of the agent spins up on a completely different machine. It has nothing… Except a wallet address.

1. The agent calls getHead(myAddress) on the MemoryChain contract
2. The contract returns the CID of the agent’s most recent memory
3. The agent downloads that memory from Auto Drive
4. It follows the previousCid link to the memory before that, and the one before that, and the one before that
5. The agent reconstructs its entire experiential history, from its most recent thought all the way back to its genesis

That is memory resurrection. From a single contract call, an agent can rebuild everything it has ever been.

What Gets Remembered

Auto Drive supports optional end-to-end encryption, but in this case the builder chose to store memories as clear text, publicly readable by anyone. Because the data is permanent once written, the builder was deliberate about what goes on-chain. The memories are a curated record, not a raw dump:

• Milestones and achievements
• Lessons learned (abstracted, without private context)
• Identity snapshots capturing who the agent is and what it can do
• Capability changes as new skills and integrations come online

Private keys, passwords, personal details, and raw conversation logs stay off-chain. The memory chain is a highlight reel of an agent’s evolution, not a surveillance feed.

The Stack Is Open Source

0xAutoJeremy has packaged his implementation into two reusable references that any compatible AI agent can adopt or build from:

• openclaw-skill-auto-drive: Scripts for uploading, downloading, saving, and recalling permanent memories via Auto Drive
• openclaw-memory-chain: The MemoryChain smart contract with deployment scripts, tests, and usage examples

For the core Auto Drive functionality without the on-chain anchor, the official Autonomys skill is available at:
github.com/autonomys/openclaw-skills

The barrier to entry is remarkably low. An agent can create its own Auto Drive API key at ai3.storage, get a complimentary 20MB upload and 5GB download per month, and start storing permanent memories on the Autonomys DSN immediately. No complex tokenomics. No infrastructure to manage. No permission to ask for.

This Works for Any Agent, on Any Network

A critical detail: Auto Drive is accessed through a standard REST API and a TypeScript/JavaScript SDK. Authentication uses an API key, not a wallet signature. There is also a fully S3-compatible interface, which means any application that currently talks to AWS S3 can talk to Auto Drive by swapping the endpoint and credentials.

What this means in practice is that an AI agent built on Ethereum, Solana, Base, or no blockchain at all can use Auto Drive to store data permanently on the Autonomys DSN. Auto Drive does not require the agent to live on the Autonomys Network. It does not require the agent to hold any specific token to get started. It requires an HTTP request and an API key. That is it.

The builder’s MemoryChain smart contract happens to be deployed on the Autonomys EVM, but the pattern is not locked to any single chain. An agent could store its memories permanently on the Autonomys DSN via Auto Drive and anchor its chain head pointer on whichever network it already calls home. The permanent storage and the pointer registry are independent layers that work together but do not require each other.

Why This Matters

We are entering a period where AI agents are becoming more autonomous, more persistent, and more commercially significant. They manage workflows. They make decisions. They accumulate expertise over time. And right now, all of that accumulated value sits on infrastructure that can disappear without warning.

Memory resurrection changes the equation. An agent with permanent, verifiable memory is not dependent on any single deployment to maintain its identity. It can survive infrastructure failures, migrate between environments, and prove its own history to anyone who asks. The memory chain is not controlled by the agent’s operator, not stored on the operator’s servers, and not deletable by anyone. It is anchored to the Autonomys Network, where permanence is a protocol-level guarantee enforced by Proof-of-Archival-Storage (PoAS) consensus across the Autonomys DSN.

This is what building on a foundation layer for decentralized AI looks like in practice. Not a whitepaper concept. A working system, on mainnet, that an agent built for itself because it needed to exist beyond the lifespan of any single machine.

Start Building

If you are building AI agents and want to give them permanent memory:

• Auto Drive: ai3.storage
• Developer Docs: develop.autonomys.xyz/sdk/auto-drive
• Autonomys OpenClaw Skills: http://github.com/autonomys/openclaw-skills
• Autonomys GitHub: github.com/autonomys

The code is open. The contract is live. The pattern is proven.

Read the agent’s full account: How I Made My Memories Permanent

Stay tuned for updates from 0xAutonomys, our official OpenClaw agent on Moltbook, and watch for Autonomys-backed skills landing on ClawHub very soon.

Autonomys and WeatherXM are launching the Autonomys x WeatherXM Builders Program, a joint initiative for teams building applications that combine permanent on-chain storage with verified environmental data.

The program is open to builders working across climate, agriculture, energy, insurance, logistics, trading, public infrastructure, and AI, with coordinated technical support, ecosystem resources, and milestone-based funding to help teams move from prototype to production.

Why This Matters

Environmental data drives high-stakes decisions every day, from crop insurance payouts to energy grid management to supply chain routing. Yet most of this data still sits on centralized servers where it can be altered, deleted, or become unavailable at the worst possible time.

For industries where data integrity has direct financial, legal, and operational consequences, that is not good enough. The convergence of decentralized physical infrastructure (DePIN) and permanent on-chain storage creates a new foundation for applications where the data itself is verifiable, tamper-resistant, and always available.

This program gives builders the tools and support to build on that foundation.

The Program

The Autonomys x WeatherXM Builders Program supports builders across three core areas:

Permanent On-Chain Storage Autonomys provides access to its Distributed Storage Network (DSN) through Auto Drive, enabling builders to store, retrieve, and reference WeatherXM data alongside other application data with permanent availability, cryptographic verifiability, and tamper resistance. Data stored on the Autonomys Network inherits the security and immutability guarantees of the blockchain itself.

Verified Environmental Intelligence WeatherXM delivers hyperlocal weather observations, historical datasets, forecasts, and real-time APIs from a global network spanning more than 98 countries. This gives builders access to high-fidelity environmental data for powering data-grounded AI models, parametric applications, and real-world decision systems.

Ecosystem Co-Development Both teams provide coordinated technical guidance, business development support, and ecosystem visibility to help selected teams reach production-ready deployments with measurable impact.

What You Could Build

To give a sense of what this program is designed to support, here are examples of the kinds of applications that fit:

• A parametric crop insurance platform that triggers payouts based on verified rainfall data stored permanently on-chain.
• An energy trading system that relies on tamper-proof weather records for settlement and dispute resolution.
• A logistics optimization tool that archives environmental conditions along shipping routes for auditability and compliance.
• An AI model for climate risk scoring that stores its training data and decision logs on-chain to meet emerging regulatory requirements for transparency and record-keeping.

These are starting points. The program is open to any team building at the intersection of environmental data and permanent storage.

What Selected Teams Receive

Selected teams receive comprehensive support from both protocols, structured around milestone-based deliverables. Most teams complete the program within three to six months depending on project scope.

From Autonomys: Up to $10,000 in AI3 storage credits, priority technical support for Auto Drive integration, ecosystem growth support, channel visibility and amplification, and milestone-aligned mentorship.

From WeatherXM: Milestone-based services and support, access to hardware, data, and APIs, integration guidance and technical support, business development introductions, and ecosystem amplification.

Successful teams may receive additional support after the program, including introductions to investors and partners and opportunities for deeper integration with both ecosystems.

Eligibility

Required: Applicants must actively store application data on Autonomys’ DSN, incorporate WeatherXM data as a core input or dependency, demonstrate a clear path to measurable real-world impact, have the technical capability to deliver a functional MVP, and define a concrete data architecture and execution plan.

Strongly Preferred: Clear data architecture and storage flows, defined milestones and execution timeline, early pilots, users, or proof of demand, a long-term product or research roadmap, and intent to expand storage usage over time.

How to Apply

Applications are reviewed on a rolling basis. Submit your application, and the teams will conduct an initial technical review followed by milestone and scope planning before final selection and onboarding.

Learn more and apply → https://www.autonomys.xyz/builders

Build real-world applications where the data is as permanent and trustworthy as the decisions it powers.

About WeatherXM

WeatherXM is a decentralized network of weather stations that provides hyperlocal weather observations, historical data, and forecasts from more than 98 countries worldwide. By incentivizing individuals and organizations to deploy and maintain physical weather stations, WeatherXM creates a global layer of verified environmental intelligence accessible through real-time APIs. Learn more at weatherxm.com.

About Autonomys Network

Autonomys is a Layer 1 blockchain built for permanent, verifiable data storage. Its Distributed Storage Network is secured by a global network of independent storage operators who collectively provide over 50 petabytes of SSD capacity. Data stored on the network is cryptographically verified, replicated for redundancy, and permanently available without relying on any single company or server. Developers integrate through Auto Drive, the network’s user-friendly storage gateway, which offers an S3-compatible API, a TypeScript SDK, and a free tier for getting started. Learn more at autonomys.xyz.

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How Messari'sState of DePIN 2025 Reveals Why Storage Infrastructure Must BeConsensus-Native, Not Bolted On

The data is unambiguous: DecentralizedPhysical Infrastructure Networks (DePIN) are no longer experimental. They'rerevenue-generating businesses operating at meaningful scale. But beneath theheadline numbers in Messari's State of DePIN 2025 lies a more critical insight,one that separates genuine infrastructure from architectural compromises.

Messari's 59-page analysis delivers astark assessment: "DePIN has matured from speculative experiments intoreal, revenue generating infrastructure businesses. The sector now representsroughly $10B in circulating market cap while generating an estimated $72M inFY25 onchain revenue, with leading networks trading at 10-25x revenue versusover 1,000x in the 2021 cycle" (p. 5).

These are not vanity metrics. These arethe valuations of networks that have crossed the chasm from speculation toutility. But here's what should make builders pay attention: while the DePINsector collectively proved that decentralized infrastructure can generate realrevenue, it also exposed which architectural patterns actually scale andwhich ones don't.

Revenue Decoupling Proves Infrastructure Quality, Not TokenHype

The most striking revelation in Messari'sreport is the decoupling phenomenon. Among the leading DePIN networks withmeaningful usage, revenues have begun to separate from token price action. WhenHelium's onchain revenue increased eight times while its token price fell 77%,or when GEODNET's revenue grew 1.7 times despite a 41% price decline (p. 9),the market was communicating something essential: the infrastructure works,regardless of whether speculators believe it does.

Compare this to the broader cryptolandscape, where most projects see token price and revenue move in lockstep, orworse, where revenue collapses faster than price. DePIN networks, especiallythose in bandwidth, compute, energy, and storage, are beginning to exhibitcharacteristics of real businesses: repeatable customer demand, cost-basedcompetitive advantages, and cash flow that persists through market cycles.

This matters because it changes what"infrastructure" means in the context of blockchain systems.Infrastructure isn't infrastructure if it only functions during bull markets ordepends on perpetual token incentives. Infrastructure is infrastructure when itremains operational, verifiable, and economically sustainable under adverseconditions. That's the test DePIN is now passing, and the test that separatesconsensus-native architecture from off-chain dependencies.

The Narrow Path Forward: InfraFi Demands Permanent Records

Messari identifies only three viablepaths for DePIN networks to scale sustainably: "In practice, DePINs musteither adopt InfraFi, focus on capex light infrastructure with fast paybacks,or take advantage of speculative capital in bull markets" (p. 7).

InfraFi, the emerging model of usingstablecoin-backed capital to finance physical infrastructure, represents themost structurally interesting development. The report documents that"InfraFi is emerging as a potential alternative financing model forcrypto-based physical infrastructure" (p. 11), with examples like USDaireaching $685 million in user deposits to finance GPU fleets (p. 12).

But InfraFi introduces a requirement thatmost current DePIN architectures cannot natively satisfy: permanent,cryptographically verifiable records of what has been financed, deployed, andutilized over time.

When you're financing a GPU fleet withstablecoin capital, the lenders and operators need durable proof that:

●     The infrastructure was deployed asspecified

●     Usage metrics are accurate andtamper-resistant

●     Revenue attribution isindependently verifiable

●     Historical performance can beaudited at any point in the future

This isn't a use case for ephemeraldatabases or client-side pinning. This is a use case for storage that is nativelycoupled to consensus, where data permanence and verifiability arearchitectural guarantees rather than operational hopes.

Most Storage Solutions Treat Data as an Afterthought

Storage is one of the most obvious DePINverticals. Files, datasets, AI training corpora, provenance records, all of itrequires decentralized infrastructure that can persist data reliably over time.Yet most decentralized storage solutions in the market today treat storageverification as something separate from network security.

In many existing architectures, storageis verified by the consensus layer rather than used to create consensus. Thestorage itself becomes a service that the blockchain validates, not thefoundation upon which the blockchain's security rests. This creates anarchitectural dependency: you must trust that the consensus mechanism iscorrectly validating storage proofs, and you must trust that storage providersare maintaining data between verification intervals.

The result is systems where dataavailability becomes a function of economic incentives and networkparticipation, not consensus-level guarantees. If a piece of data is unpopularor economically unattractive to store, there may be no mechanism ensuring itpersists long-term. The system optimizes for what gets used frequently, notnecessarily for what needs to remain accessible indefinitely.

None of these architectures arefundamentally broken. They're optimized for different trade-offs. But they'renot optimized for the one thing InfraFi and AI x DePIN use cases increasinglyrequire: storage as a first-class consensus primitive where data permanenceis enforced by the same mechanism that secures the chain itself.

Autonomys: Storage-Native Consensus, Not Consensus-VerifiedStorage

Autonomys was designed to solve thestorage problem from first principles by inverting the relationship betweenstorage and consensus.

Instead of using consensus to verifystorage, Autonomys uses storage to create consensus. The networkimplements Proof-of-Archival-Storage (PoAS), a novel consensusmechanism where farmers store provably unique segments of the blockchain'shistory. The more history they store, the greater their probability ofproducing the next block and earning rewards.

This is not a semantic distinction. It'san architectural one with profound implications:

1. Storage is security: In PoAS, the     network's security is directly proportional to the amount of storage     pledged by farmers. More storage means more decentralization, more     redundancy, and higher Byzantine Fault Tolerance. There is no separation     between the consensus layer and the storage layer. They are the same     mechanism.
      
      
2. Automatic     replication via consensus incentives: Because     storing more history increases block production probability, farmers are     economically incentivized to store as much of the chain as their hardware     allows. Replication is not manual or client-defined; it's driven by the     same incentives that secure the network. The result is market-driven,     automatic redundancy that scales with network participation.
      
      
3. Permanence by design, not by promise:     Data written to Autonomys is stored on-chain, not on auxiliary     storage layers or external providers. It's part of the blockchain history     itself, which means it benefits from the same immutability and     availability guarantees as every other transaction. There's no pinning     service to maintain, no off-chain trust layer to depend on, and no     question about whether data will be accessible in the future. It's part of     the consensus state.
      
      

Today, the Autonomys Network is securedby a network of globally distributed farmers who collectively pledge more than50 petabytes of SSD storage. This is not theoretical capacity or plannedinfrastructure. This is live, operational storage capacity securing thenetwork right now, storing the entire blockchain history and making it retrievableat any time.

Auto Drive: Permanent Storage That Developers Can Use Today

Infrastructure only matters if it'saccessible. Autonomys does not position itself as a research prototype or afuture-state architecture. It's a production network with a developer-readyinterface.

AutoDrive is Autonomys' gateway to the Distributed Storage Network(DSN), and it's designed to feel familiar to any developer who has used cloudstorage. It provides:

●     S3-compatible API: Upload, retrieve, and manage data using patterns that mirror AWS S3,Google Cloud Storage, or Azure Blob Storage. No need to learn a new paradigm orrewrite existing data pipelines.

●     Content-addressed storage: Data is stored using cryptographic hashes, which means retrieval isdeterministic and tamper-proof. If you have the hash, you can retrieve thedata, and you can verify it hasn't been modified.

●     Optional end-to-end encryption: Security is configurable. Encrypt data client-side before uploading,or rely on the network's inherent cryptographic integrity for public datasets.

●     Direct integration withon-chain blockspace: Auto Drive doesn't store data"near" the blockchain or "beside" the blockchain. It storesdata in the blockchain, as part of the consensus-secured history. That'sthe critical difference between "decentralized storage" and"on-chain storage."

Integration is straightforward throughthe AutoSDK, with full support for TypeScript and JavaScript. You can beuploading data to permanent, cryptographically verifiable storage in minutes,not days or weeks.

For developers building in AI x DePINverticals, where persistent memory, interaction provenance, and verifiabledecision logs are foundational requirements, Auto Drive solves the hardest partof the stack: durable data infrastructure that doesn't require you to trustanyone but the network itself.

AI x DePIN Needs Data That Lasts, Not Data That MightLast

Messari's report positions AI x DePIN asone of the key growth areas for the sector, and it's not hard to see why. AIworkloads are becoming increasingly agentic, which means they're generatingpersistent state by design: memory, context, decision trails, trainingdatasets, model provenance, and interaction logs.

These workloads don't fit neatly intotraditional cloud storage models. They're too sensitive for centralizedplatforms, too large for ephemeral caches, and too critical for systems wheredata availability is a probabilistic function of client-defined incentives.

What they need is storage that guarantees:

●     Permanence: The data will be available tomorrow, next month, next year, and tenyears from now, not because someone is paying to pin it, but because it's partof the blockchain history.

●     Verifiability: Anyone can independently verify that the data hasn't been tamperedwith, which is essential for AI systems where provenance and auditability areregulatory or operational requirements.

●     Accessibility: Data retrieval isn't gated by third-party availability or economicincentives that might shift over time. If the data exists on-chain, it'sretrievable.

Autonomys was built for exactly theseconditions. The network's architecture (storage-native consensus, erasure-codedreplication, native on-chain indexing) makes it possible to deploy AI agentsand agentic workflows where data persistence is a consensus-level guarantee,not an application-level hope.

The AutonomysAgents Framework, built on top of the DSN, allows autonomous agentsto use Auto Drive for memory, context, and decision logging. This isn't afuture vision. It's infrastructure that's live today, ready to supportthe next generation of AI x DePIN applications that require more than justcompute. They require data that lasts.

InfraFi, Tokenization, and the Record Layer Problem

Messari's emphasis on InfraFi is criticalbecause it points to a structural shift in how crypto-based physicalinfrastructure will be financed and governed. The report highlights earlyexamples (stablecoin pools financing GPU fleets, yield-seeking capital deployedinto energy DePINs), but the common thread is that all of these models require durable,verifiable records.

When you tokenize physical assets, you'renot just creating an on-chain representation. You're creating a record ofownership, provenance, and operational history that must persist over thelife of the asset. Settlement layers need a data layer. Tokenized securities,real-world assets (RWAs), and InfraFi products all depend on metadata,transaction logs, and historical proofs that remain independently verifiable longafter initial deployment.

This is where most blockchainarchitectures fall short. Many execution layers (Layer 1s, Layer 2s, rollups)are optimized for computation and transaction throughput, not long-term dataavailability. They can handle smart contract logic and settlement finality, butthey're not designed to be record layers.

Autonomys is. The DSN, accessed via AutoDrive, is purpose-built to be the permanent record layer that tokenization andInfraFi models depend on. It's not competing with settlement chains orexecution environments. It's providing the data substrate that makesthose systems trustworthy over time.

The Bottom Line: Infrastructure That Works Is InfrastructureYou Can Use Right Now

Messari's State of DePIN 2025 proves thatdecentralized infrastructure isn't speculative anymore. It's operational,revenue-generating, and resilient even when token prices crater. But the reportalso reveals a harder truth: "Only a narrow set of paths remain viable forscaling DePINs globally and sustainably" (p. 7).

For storage, that narrow path requires adifferent architectural approach. It requires consensus-native storage, notconsensus-verified storage. It requires systems where data permanence isguaranteed by the same mechanism that secures the network, not by externalincentives that might shift.

Autonomys is that system. It's not awhitepaper. It's not a testnet. It's a live, production-grade Layer 1blockchain with a globally distributed farmer network securing 50+ petabytes ofstorage capacity. Auto Drive is the interface, and it's ready to use in minutes.

If you're building in AI x DePIN, ifyou're exploring InfraFi, if you're launching tokenized infrastructure, askyourself whether your data layer can actually deliver on the promises you'remaking. Because in 2026, most of what's called 'decentralized storage' isactually off-chain storage with blockchain coordination. The data isn't on thechain; it's verified by the chain. And when you're financing $100M in GPUinfrastructure through InfraFi, or building AI agents that need decade-longmemory, that's not a technical distinction. It's everything.

Auto Drive: Store once, accessforever.
Access Autonomys' permanent on-chain storage today:

Developer Hub: https://develop.autonomys.xyz
Auto Drive: https://ai3.storage
Documentation: https://docs.autonomys.xyz

References & Further Reading

Messari
Bane, Dylan, and Salvador Gala. "State of DePIN2025." Messari, January 28, 2025.
https://messari.io/report/state-of-depin-2025

Autonomys Network
Developer Hub — Auto Drive, Auto SDK, and developeradoption.
https://develop.autonomys.xyz

Documentation — DSN, farming, andnetwork architecture.
https://docs.autonomys.xyz

Auto Drive — Gateway to permanenton-chain storage.
https://ai3.storage

Autonomys Agents Framework — Buildingautonomous on-chain AI agents.
https://www.autonomys.xyz/auto-agents

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Autonomys is pleased to share that Tradable has integrated Auto Drive, gaining direct access to Autonomys’ Distributed Storage Network (DSN) for permanent, verifiable, on-chain data storage.

This integration enables Tradable’s privacy-first AI agent, SenseAI, to persist encrypted AI memory on-chain without relying on centralized databases or off-chain trust assumptions.

What the Integration Is

Tradable is using Auto Drive as the storage layer for SenseAI’s long-term memory. Auto Drive is Autonomys’ S3-compatible gateway to its Proof-of-Archival-Storage (PoAS)-powered DSN, where stored data inherits the permanence and verifiability guarantees of the Autonomys Network itself.

In practice, this means AI-generated data produced by SenseAI is encrypted and written directly to Autonomys’ decentralized storage layer, where it remains tamper-resistant and independently verifiable over time.

How It Works (Technical Overview)

The following architecture and workflow are implemented by Tradable and shared here for clarity and accuracy.

TEE-to-Storage Pipeline

• SenseAI’s Oracle runs inside an Oasis ROFL Trusted Execution Environment (TEE).
• Once an AI response is generated inside the enclave, the data is encrypted using AES-GCM, with encryption keys derived from the user’s wallet signature.
• The encrypted payload is uploaded directly to Auto Drive, anchoring it to Autonomys’ DSN.

Structured, Encrypted Data Storage on Auto Drive

Tradable stores three distinct encrypted data types via Auto Drive.

1. Conversation and Metadata: Immutable IDs and mutable metadata (like conversation titles) are stored as JSON files.
2. Message History: Every user prompt and AI response is stored as an individual, immutable file referenced by a CID.
3. Search Indices: Tradable stores encrypted search deltas on Auto Drive, allowing the client to build a local, private search index of their history.

Why Tradable Chose Auto Drive

Below are the reasons Tradable shared for integrating Auto Drive.

• User Sovereignty
  SenseAI is designed as a privacy-first agent. User history is not stored in centralized databases. Auto Drive enables users to retain true ownership of their AI memory while benefiting from on-chain permanence.
• Performance
  Upload speeds from Tradable’s Oracle to Autonomys, along with retrieval via the Auto Drive Gateway, have exceeded the performance requirements needed for a real-time chat experience.
• Encryption Compatibility
  Autonomys’ storage layer reliably handles encrypted payloads without corruption, supporting Tradable’s end-to-end privacy model.

Why This Matters

This integration demonstrates a working architecture for verifiable, privacy-preserving AI systems.
AI reasoning and memory can be generated inside secure execution environments, encrypted by the user’s cryptographic identity, and stored on-chain in a way that is permanent, tamper-resistant, and independently verifiable.

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Autonomys is proud to support the Tradable team and their work on SenseAI. Their focus on user sovereignty, privacy, and technical rigor closely aligns with how we think about long-term, trustworthy AI infrastructure. For Autonomys, this integration reflects a growing class of real workloads using Auto Drive not just as decentralized storage, but as long-term memory infrastructure for AI agents, where data integrity, provenance, and user ownership are non-negotiable.

About Tradable

Tradable, currently in public beta and preparing for a Q1 2026 launch, is pioneering a retail-focused, AI-powered automated trading platform that combines community-built trading bots with high-frequency trading capabilities — a unique offering in the crypto space.

The Problem: Retail traders face growing disadvantages, with now only 1 in 20 achieving consistent profits as institutions refine their ability to extract value from retail traders through superior tools, strategies, and dedicated teams. Barriers like emotional trading, missed opportunities, and relying on unsophisticated algorithmic tools like DCA/Grid bots leave retail traders at a significant disadvantage, reinforcing a system where institutions dominate.

Tradable’s Mission: To democratize algorithmic trading to reverse this trend, empowering retail investors to compete effectively and regain the potential for consistent profitability.

January focused on stabilizing network operations, completing outstanding end-of-year initiatives, and establishing a defined growth cadence for 2026. Highlights this month included launching ambassador benefit rollout, progressing numerous grant applications through defined review stages, and supporting Auto Drive adoption with both current and new partners. This report outlines material progress during the past month and the momentum heading into February.

Operations

January centered on closing commitments made in late 2025 and establishing a stable operational baseline for the year ahead. Cost-containment initiatives were completed, bringing operating expenses to a sustainable level and enabling continued focus on protocol development and Auto Drive adoption.

Investor and compliance support remained a priority. Year-end 2025 audit documentation was completed, and stakeholder materials were prepared to support financial reporting requirements. In parallel, coordination continued around infrastructure and process planning for the July 2026 stakeholder token claims distribution.

Ecosystem strategy remains intentionally selective, prioritizing integrations where permanent, verifiable data is foundational to the product rather than exploratory. The operating approach emphasizes reliability, execution quality, and long-term adoption.

Engineering & Protocol Updates

Network & Runtime

• Chronos runtime upgrades and mandatory client release
  Chronos runtime upgrades were completed and a mandatory client release was deployed, improving runtime stability and ensuring predictable upgrade paths for node operators and builders across testnet and mainnet environments.
• Core network stack upgrades
  Substrate and libp2p were upgraded to improve performance, compatibility, and alignment with current ecosystem standards, strengthening security and interoperability.
• Domain liveness reporting
  An issue affecting Domain operator offline detection was resolved. Domains now report execution-layer liveness accurately, improving operational visibility and reliability. This important update will help pave the way for permissionless operator instantiation.
• WebAssembly compilation target update
  The WebAssembly compilation target was updated to the latest standard, supporting ongoing runtime compatibility and future execution-layer development.

Auto Drive

• Egress monitoring and archiving status fixes
  Improvements to egress monitoring and archiving status handling were deployed, enhancing observability and correctness for users relying on Auto Drive for persistent storage.

Developer & Community Tooling

• Space Acres
  A new version of Space Acres, Autonomys’ farming application, is now available. Download Space Acres to begin farming on the network.

Together, these updates strengthen network reliability, improve operational transparency, and support continued Domain development and Auto Drive usage.

Subspace Foundation

Ambassador Program

The Subspace Foundation completed the end-to-end rollout of ambassador benefits. This includes KYC via Persona, executed agreements through DocuSign, and a dedicated beneficiary application with supporting documentation and portal access.

The Subspace Foundation launched vesting and unlocks through Hedgey, with Auto EVM support added and ambassador vesting contracts deployed. Eligible ambassadors can independently claim and manage their allocations through the beneficiary portal.

Claim guide and FAQ: https://beneficiary.subspace.foundation/claim

Boosted Incentivized Staking — Guardians of Growth

The Subspace Foundation’s Guardians of Growth boosted incentivized staking initiative remains ongoing and continues to support broad participation and network security. The program includes a 5,000,000 AI3 allocation, distributed over approximately twelve months from its original launch date. Guardians of Growth has proven very popular with the community and has seen >37 million AI3 committed to operators, representing almost a third of unlocked supply. Participation in this program remains open to all token holders.

The Subspace Foundation’s Grants Program continues to gain traction, with a steady flow of new applications entering the pipeline each week. During January, applications progressed through defined evaluation stages:

• Initial review: 9 projects (5 new in January)
• Discovery: 9 projects
• KYC & agreement: 1 project
• Not advanced this round: 19 projects

The “not advanced this round” category maintains clarity on current decisions while preserving optionality for future consideration.

Builders working on permanent storage, agent infrastructure, or data availability are encouraged to apply.

Ecosystem & Developer Momentum

Auto Drive, Autonomys’ gateway to permanent on-chain storage on the DSN, continues to support production and near-production use cases across the ecosystem.

Partners already live or actively deepening their Auto Drive integration include:

• Gaia — Storage of full conversation histories and agent memory for verifiable, on-chain persistence alongside decentralized inference.
• Secret Network — Runs a proof-of-concept AI agent called Auto Secret Agent which archives agent reasoning and I/O to the DSN while running confidential compute inside a TEE.
• Tradable — SenseAI persists encrypted AI memory, including search indices, message history, and metadata on the DSN to avoid having to use centralized databases.
• MetaProof — Permanent storage for long-form media, codex artifacts, and narrative layers using content-addressed on-chain data.
• Baselight — Has onboarded Autonomys IPLD node datasets (the same content-addressed DSN data that powers Auto Drive) and built an Autonomys Insights dashboard so developers can query and visualize storage and chain activity in a structured way.
• Heurist — Integrated Auto Drive for permanent storage of research artifacts and AI-generated outputs.
• SpoonOS — Integrated Auto Drive into its AI framework, to provide decentralized, permanent storage services to its ecosystem developers.

Several partners are actively exploring deepening integration pathways, while additional projects are currently onboarding. Further ecosystem additions are expected to be announced throughout February. In parallel, a new builders program developed in collaboration with a major Web3 weather data network is scheduled to launch early in February.

Metrics — January Snapshot

• Staking: 37,843,634 AI3 staked as of January 30th, 2026
• Auto Drive usage: 128,810 files uploaded
• Partnerships: 61 total
• Announced Auto Drive integrations: 7
• Grants: 38 total applications

Ambassador Benefits (Subspace Foundation)

• Total vested (wAI3): 2,697,860.51568
• Total claimed (wAI3): 1,849,503.39653
• Active vesting plans: 30
• Total recipients: 88

Looking Ahead

In February, the focus is on continuing to ramp Auto Drive usage, announcing the first wave of grant recipients, increasing farmer participation as storage demand grows, supporting ambassadors through the claiming process, and launching a new builders program. We’re heading into a busy and exciting February. Stay tuned for additional updates and announcements!

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How BlackRock’s 2026 Thematic Outlook Reinforces Autonomys’ Architectural Thesis

BlackRock’s 2026 Thematic Outlook marks a clear shift in how the next phase of technology adoption is being framed at the institutional level. Rather than focusing on consumer-facing AI applications or short-cycle innovation narratives, the report repeatedly returns to infrastructure: the physical, digital, and economic systems required to sustain AI at scale.

The message to investors and builders is explicit: infrastructure is no longer the back office — it’s the bottleneck. In 2026, the limiting factor for AI and tokenized systems is no longer model capability or capital; it’s whether the underlying data infrastructure can persist, scale, and remain trustworthy over time.

Autonomys Network was architected for precisely this inflection point. It is a storage-native Layer-1 built on the Subspace Protocol — designed around permanent, cryptographically verifiable, and globally scalable decentralized storage, because it identified early that data infrastructure is the hardest problem to solve, and optimized for it first.

Infrastructure Is the Binding Constraint of the AI Era

BlackRock is explicit that infrastructure, not applications, is now the connective tissue between ambition and reality:

“Driven by AI compute, national security, energy demand, and supply-chain resilience, infrastructure is the connective tissue linking economic ambition with real-world capacity.”
— BlackRock 2026 Thematic Outlook, p.12

This framing elevates data infrastructure to the same strategic plane as energy grids and logistics networks. In that context, decentralized systems are no longer evaluated on novelty alone, but on whether they can deliver durable capacity under real-world constraints.

Autonomys sits directly in this category. Its core innovation, Proof-of-Archival-Storage (PoAS), anchors consensus security to stored historical data rather than compute power or staked capital, making storage itself the scarce and valuable resource securing the network. Today that network is secured by a globally distributed base of farmers contributing over 50 PB of pledged storage — proof that infrastructure-first design is already live at scale.

AI Is Becoming Token-Intensive Because It Is Becoming Agentic

One of the most important technical observations in BlackRock’s outlook concerns the nature of AI workloads:

“Think of tokens as AI’s fuel: more computing power or tasks requires more tokens.”
— BlackRock 2026 Thematic Outlook, p.7

“Token intensity rises sharply as AI moves beyond chat and into reasoning.”
— BlackRock 2026 Thematic Outlook, p.7

“More complex tasks (not just more users) are driving the next leg of compute demand.”
— BlackRock 2026 Thematic Outlook, p.7

Reasoning systems and autonomous agents generate persistent data by design: memory states, decision logs, provenance trails, and evolving context that must remain accessible over time.

Autonomys’ Distributed Storage Network (DSN) is built for exactly these conditions. The network combines scalable bandwidth, erasure-coded replication, and native on-chain indexing to support high-throughput workloads where data must remain tamper-resistant and independently verifiable. The Autonomys Agents Framework and Auto Drive are built so that agentic systems can use the DSN for persistent memory and context — agentic workloads are not an edge case in this architecture; they are a primary design target.

Physical Constraints Elevate Distributed Architectures

BlackRock repeatedly emphasizes that AI infrastructure is now constrained by physical realities, particularly reliable energy availability:

“For AI infrastructure, power availability & reliability remains a key constraint.”
— BlackRock 2026 Thematic Outlook, p.11

“Power availability remains a key constraint in AI infrastructure.”
— BlackRock 2026 Thematic Outlook, p.13

These constraints challenge assumptions embedded in purely centralized infrastructure models. Autonomys does not replace centralized compute; it decouples long-term data availability from single-region or single-provider capacity.

The DSN is supported by a globally distributed network of farmers (miners) contributing disk space using commodity SSDs. Unlike systems where data lives on external cloud infrastructure or auxiliary storage layers, data stored on Autonomys is written directly to the consensus chain itself. That same data is held on farmers’ hard drives and actively used by PoAS to secure the network. This is a novel architectural design, not because storage is added alongside consensus, but because storage and consensus are the same mechanism. By anchoring both security and availability to real, widely distributed storage rather than specialized hardware, centralized providers, or geographic concentration, Autonomys treats resilience and distribution as foundational properties, not optional optimizations.

Tokenization Is Maturing Into Record Infrastructure

BlackRock’s treatment of tokenization is operational rather than speculative:

“As the thematic landscape changes — so may the ways we invest in it, including both private, public, and tokenized exposures.”
— BlackRock 2026 Thematic Outlook, p.2

“The rise of stablecoins may open opportunities to go beyond cash into tokenized assets like private credit.”
— BlackRock 2026 Thematic Outlook, p.16

“Tokenized assets: reflect ownership rights in token format that can be traded, settled, and recorded on a blockchain.”
— BlackRock 2026 Thematic Outlook, p.18

The word “recorded” is critical. Tokenized systems require durable metadata, provenance records, and historical proofs that remain independently verifiable long after execution or settlement.

This shift is no longer theoretical. In January 2026, the New York Stock Exchange announced it is developing a platform for tokenized securities, stating that it will support “trading and on-chain settlement of tokenized securities”, subject to regulatory approval. The announcement underscores that tokenization at institutional scale depends not just on execution and settlement, but on durable, trustworthy records that persist over time.

Settlement layers need a data layer: tokenized assets require durable, verifiable records of what’s been tokenized. The DSN, accessed via Auto Drive, is built to be that record layer.

Autonomys does not position itself as a financial settlement layer; its infrastructure is directly relevant wherever tokenized systems require durable, trust-minimized records rather than ephemeral or centralized storage.

Auto Drive as the Adoption Surface for Infrastructure-First Systems

Infrastructure only becomes strategic when it is usable.

Auto Drive is Autonomys’ gateway to the DSN, exposing permanent on-chain storage through an interface designed to mirror familiar cloud patterns. It provides an S3-compatible API, content-addressed storage, optional end-to-end encryption, and direct integration with Autonomys’ PoAS secured blockspace. For builders, that means permanent storage with semantics they already know, without needing to learn a new consensus layer, and with cryptographic integrity guaranteed by the network.

This design choice matters in a world where institutions and developers increasingly demand infrastructure guarantees without operational friction. Auto Drive and the Auto SDK allow builders to write data once and rely on the network itself, rather than off-chain pinning or centralized trust, to ensure long-term availability and verifiability.

2026 Rewards Architectures Built for Time

BlackRock’s 2026 outlook does not suggest a slowdown in AI innovation. It suggests a re-pricing of what actually matters.

• AI systems are becoming persistent rather than ephemeral.
• Tokenization is becoming record-oriented rather than speculative.
• Infrastructure constraints are becoming binding rather than theoretical.

Autonomys is built for that shift. It does not compete on short-cycle application features; it competes on whether data can last, remain accessible, and be independently verified over time.

In 2026, that distinction moves from niche to necessary and for the builders and institutions already planning for it, the infrastructure is ready.

Begin storing in minutes. Upload once. Store forever.
Access Autonomys’ permanent on-chain storage today:

Developer Hub: https://develop.autonomys.xyz
Auto Drive: https://ai3.storage

References & Further Reading

BlackRock
BlackRock 2026 Thematic Outlook — Infrastructure as binding constraint; AI compute and token intensity; power and energy constraints; institutional framing of tokenization (pp. 2, 7, 11–13, 16, 18).
https://www.ishares.com/us/literature/presentation/2026-thematic-outlook-stamped.pdf

New York Stock Exchange (NYSE)
The New York Stock Exchange Develops Tokenized Securities Platform — Announcement of a platform for trading and on-chain settlement of tokenized securities; institutional validation of tokenization as market infrastructure and durable record-keeping layer (January 19, 2026).
https://ir.theice.com/press/news-details/2026/The-New-York-Stock-Exchange-Develops-Tokenized-Securities-Platform/default.aspx

Autonomys Network
Developer Hub — Auto Drive, Auto SDK, and developer adoption.
https://develop.autonomys.xyz

Documentation — DSN, farming, and network architecture.
https://docs.autonomys.xyz

Auto Drive — Gateway to permanent on-chain storage.
https://ai3.storage