_This is the first post in a series featuring ideas for autonomous services from Autonolas community members. It’s brought to you today by guest author and community member_ [_Odin.THOR_](https://twitter.com/ODIN_Thorchain)_. Odin.THOR has been doing some impressive thinking about compelling ideas for autonomous services and we wanted to share them with the community. Let us know what you think, and feel free to also share your own ideas with everyone on_ [_Twitter_](https://twitter.com/autonolas) _or_ [_Discord_](https://discord.com/invite/z2PT65jKqQ)_–you might be the next author featured on the blog!_

### Introduction

Welcome to the first volume of Autonomous Augmentations!

With more and more of the Autonolas stack being released, this series hopes to provide new (and existing) members of our growing community a ‘feel’ for application types uniquely suited for the robust, fault-tolerant and highly flexible nature of our framework. Each installment of Autonomous Augmentations will aim to introduce a novel project idea to the community with the goal of fostering an atmosphere of open collaboration and continual innovation.

We encourage anyone intrigued, excited or even wary of the ideas discussed here to visit our [Discord](https://discord.com/invite/z2PT65jKqQ) and share their thoughts and/or suggestions! As always, anyone interested in building with Autonolas should feel free to reach out to our core team on [Twitter](https://twitter.com/autonolas)/Discord!

Without further ado, let us dive in!

### Ideas

#### **#1** : Dynamic ‘Real’ CPI Oracle

**Purpose**: To provide inflation-resistant stablecoins with a transparent, reliable & customizable alternative to Government-issued CPI statistics.

**Overview**: Inflation-resistant stablecoins have seen growing adoption as a simple recourse to avoid the ever-pervasive effects of inflation.

[VOLT](https://www.voltprotocol.io/) & [FPI](https://docs.frax.finance/frax-price-index/cpi-peg-and-inflation-hedge), the two predominant options, both update their peg on the basis of CPI data published by the US [BLS](https://www.bls.gov/cpi/).  Many have raised [concerns](https://whitepaper.truflation.com/background/problem) regarding the accuracy of this CPI data, suggesting those responsible for its publication have motive to misrepresent the reality of inflation. Frameworks like Autonolas can allow DeFi to avoid inheriting the opaque nature of the current system by deriving a price index using information drawn from open-source price-monitoring APIs. The product categories and sources used can be weighed dynamically to develop a variety of index types (Eg: An index which mainly tracks the purchase price of fuel). This data can then be packaged into a multi-chain [Autonolas Oracle](https://medium.com/autonolas-oracles-technical-details-b53d7568484e).

Additionally, both VOLT & FPI draw their CPI data from  the same Chainlink Oracle (See: [1](https://fraxfinancecommunity.medium.com/frax-finance-using-chainlink-to-bring-u-s-cpi-data-on-chain-in-support-of-the-frax-price-index-737ea893ab73),[2](https://medium.com/volt-protocol/volt-protocol-integrates-chainlink-data-feeds-to-help-power-its-inflation-resistant-stablecoin-b61cb276f4ee)), making them susceptible to attack and/or hostile [manipulation](https://www.youtube.com/watch?v=OObhqgDZO5Y) via centralized vectors. An Autonolas Oracle can potentially provide a more decentralized publication mechanism for otherwise excellent open-source inflation estimators such as [Truflation](https://truflation.com/), which is also primarily published through Chainlink. Truflation’s openly available methodology could act as a solid template for anyone attempting to build their own inflation estimator on Autonolas.

**Path to Implementation**: A network of Autonolas agents is configured to interact with open-source web-scraping [services](https://www.zyte.com/blog/how-to-build-your-own-price-monitoring-tool/) which collect price data for everyday goods from online storefronts. Agents themselves could be trained via machine learning to expand the sources they draw from through intelligent identification. Price data for universal goods such as grain and medication could also be collected from storefronts that cater to different socioeconomic demographics to add further nuance to calculations (Eg: Whole Foods vs Walmart). Product categories could also be weighted differently based on protocol demand to develop a range of specialized inflation estimators.

#### **#2** : Active Bridge Sentry

**Purpose**: To allow quick, automatic responses to hacks/rug-pulls in relation to wrapped tokens & real-world backed assets.

**Overview**: Some of the largest hacks in DeFi history have involved wrapped tokens and bridges. The sheer quantity of constantly shifting components involved with bridges make them vulnerable to a particularly wide [surface of attack](https://quantstamp.com/blog/the-dark-side-of-defi-cross-chain-bridge-hacks). In the case of the recent [Axie Infinity hack](https://cointelegraph.com/news/the-aftermath-of-axie-infinity-s-650m-ronin-bridge-hack), the attack itself was not noticed for [6 days](https://www.thismorningonchain.com/newsletter/600m-stolen-no-one-noticed-for-6-days/), allowing the perpetrators ample time to redirect compromised funds.

Taking the Axie Infinity hack as an example, imagine a similar situation involving a service which bridged ETH from Ethereum to Avalanche. On Day 1, an exploit was carried out, the keys on the Ethereum side of the bridge were compromised, and all ETH was stolen. Like the Axie hack, news of the exploit did not spread until Day 6.

Between Day 1 — Day 6, the wETH market on Avalanche remained unchanged since the effects of the hack were not widely known. (Until Day 6, wETH = ETH)

If a user had tasked an Autonolas service with monitoring the bridge for unusual activity and enabled it to take action on Avalanche, any wETH the user owned would likely have been entirely salvaged without additional input. The Autonolas agents would have noticed the emptying of the bridge’s ETH wallet on Ethereum and would have quickly converted the wETH on Avalanche for a different wrapped version or stablecoin, before a market response to the hack.

Conversely, if the bridge provider had enlisted an Autonolas network to monitor the bridge, they could have been notified via a Web2 notification the moment Autonolas agents detected unauthorized activity, allowing for a much faster response to the attack.

![0_etROeTR5qDshLuZ4.png](/uploads/0_et_R_Oe_TR_5q_Dsh_Lu_Z4_1fe86b11f6.png)
_Even non-DeFi users have begun to notice bridge hacks._

A similar system could also be designed for BUSD and USDC, since [Binance](https://paxos.com/attestations/) and [Circle](https://www.circle.com/en/usdc#transparency) publish attestation reports regarding the solvency of their stablecoins. In the unfortunate event either BUSD or USDC becomes under-collateralized, and this information is included in the Binance/Circle report, an Autonolas service could begin converting any BUSD/USDC under management for a different stablecoin before the rest of the market starts to panic.

**Path to Implementation**: A network of Autonolas agents is configured to monitor bridge wallets on both involved chains and tally data collected from both sources to search for discrepancies. In the event of a major discrepancy, the agents will initiate the conversion of affected assets they manage (on behalf of a user/DAO) to a predetermined ‘safe asset’ (Eg: USDC).

In the case of BUSD/USDC solvency monitoring, Autonolas agents will be instructed to compare the value of assets listed by Binance/Circle in their report to the quantity of BUSD/USDC in circulation. If major under-collateralization is detected, the agents will begin converting managed BUSD/USDC to a ‘safe asset’ (Eg: USDT/BTC/ETH).

In both cases, a Web2 notification will be pushed to the user as soon as unusual data is identified.

#### **#3** : Single Step Speech-to-Contract Transmutation

**Purpose:** To allow users without a programming background to independently design and deploy smart contracts in a trustless manner.

**Overview:** This idea was originally inspired by Valve’s [Proton](https://github.com/ValveSoftware/Proton). Proton enables the direct translation of DirectX game code to Vulkan, allowing it to be run natively on non-Windows systems, all while retaining the nuance of the programmed instructions.

In Autonolas’ case, the goal would be to extend similar ‘logic-extraction’ to cover plain-speech descriptions of DeFi functions such as loans and token-issuance. Imagine if a user could simply write out their design for a new product or primitive and feed it to an Autonolas service for deployment. The service could then be forced to come to consensus regarding the ‘logic-map’ the plain-speech input describes, transcode it to Solidity, and seamlessly deploy it as a smart contract.

Such a service will undoubtedly require extensive effort to design and bring to fruition. However, successful execution could open the development of DeFi to a massive demographic of talented people who do not possess either the skillsetor inclination to learn Solidity.

**Path to Implementation:** Autonolas agents are trained via machine learning to identify relationships between the documentation and smart contracts used by several popular projects. The results of the training can be periodically reviewed by a team before updates are pushed to the stable version of the tool.

On the user side, example instructions can be provided to suggest ideal pattern types for different genres of plain-speech instructions. Users can also be given a graphical representation/flow-chart of how their smart contract will behave prior to deployment to ensure accuracy.

#### **#4 :** Inputless Arbitrage Income in Inefficient Markets

**Purpose**: To allow DAOs to expand their holdings by filling arbitrage opportunities generated by unusual market activity.

**Overview:** This use case is mainly targeted at large-capital investors (DAOs/Whales) who already make use of a low-risk yield-farming strategy.

Large arbitrage opportunities appear with surprising frequency among popular assets as they change hands and management decisions are made. Those who profit from these openings are typically experienced arbitrageurs with dedicated bots aimed at specific asset types. Services such as [White Whale](https://whitewhale.money/) have made considerable headway in democratizing access to arbitrage to anyone willing to devote capital to fund shared arb-bots.

DAOs generally search for low-volatility yield-generation opportunities in order to keep their assets productive but not expose them to unnecessary risk. Consequently, the yield-generation strategies they employ tend to be relatively low-reward. Arbitrage, also being particularly low-risk, has the capacity to complement DAO-centric yield-generation strategies and enhance returns, making it a prime opportunity for Autonolas to capitalize on.

The issue with high-frequency arbitrage is that large quantities of capital can only be made fully productive when significant divergences occur in the price of an asset across separate markets. These opportunities are relatively rare. Furthermore, the decentralized element of the Autonolas Stack is not particularly suited for high-speed trading. Therefore, shared arb-vaults would need to be used from a service like White Whale. Since such vaults share profits between all depositors, they result in somewhat low income when all funds in the vault are not actively used (as is the case without a significant price divergence).

Arguably the simplest solution in this situation is optimization — to make use of traditional yield-farming ordinarily and to shift funds to arb-vaults when the market becomes particularly conducive. Autonolas agents can be used to detect such openings and move funds when appropriate.

**Path to Implementation**: Autonolas agents identify large divergences in the price of a managed asset across chains and/or DEXs. Agents may even be designed to predict price divergences by monitoring the activity of the largest holders of a token and pre-emptively reacting to behavior associated with large purchases and sales. After identification, the agent network deposits managed assets into the corresponding arb-vault on a service like White Whale. After the divergence has been corrected, funds can be returned to the original yield strategy.

Thank you for taking the time to read through these ideas! Once again, if you find any of them to be of interest to you or your team, visit our [Discord](https://discord.com/invite/z2PT65jKqQ) to start a conversation with the community.

Written by [Odin.THOR](https://twitter.com/ODIN_Thorchain) — follow them [on Twitter](https://twitter.com/ODIN_Thorchain)!


Community Ideas for Autonomous Services

Autonomous Augmentations — Volume One

_This is the second post in a series featuring ideas for autonomous services from Autonolas community members. It's brought to you today by guest author and community member Odin.THOR. Odin.THOR has been doing some impressive thinking about compelling ideas for autonomous services, and we wanted to share them with the community. Let us know what you think, and feel free to also share your own ideas with everyone on Twitter or Discord–you might be the next author featured on the blog!_

### Introduction
Welcome to the second volume of Autonomous Augmentations!
Before we begin, we'd like to thank everyone who took the time to read and share our first post of ideas for autonomous services. It was gratifying to see our users actively discussing and engaging with the ideas put forward and collaborating to enrich the Autonolas ecosystem!
As always, we encourage anyone intrigued, excited, or even wary of the ideas discussed here to visit our Discord and share their thoughts and suggestions! Also, anyone interested in building with Autonolas should feel free to reach out to our core team on Twitter, Discord, or directly.

### Ideas

#### **#1**: Automated Reputation Mirroring (TradFi <-> SBTs)
**Purpose:** Allow DeFi lenders to reliably access borrowing history from existing financial systems and enforce reputational incentives off-chain.

**Overview:** The topic of DeFi-native under-collateralized lending has received significant attention over the past few months.
A proposed solution to translate the TradFi model of under-collateralized lending to DeFi is to employ a similar reputation-based incentive system to promote responsible borrowing, accompanied by public reputational repercussions in the event of default. One of the leading avenues for publishing freely verifiable reputational data on-chain is through the use of Soulbound Tokens (SBTs).

Unfortunately, a considerable issue exists with the introduction of SBTs that are informed solely by on-chain transactions - new DeFi entrants will not be able to make practical use of decentralized borrowing without first establishing a history in a wholly unfamiliar financial system. At the current stage of global economic maturity, this requirement could easily deter potential users, particularly institutions, from migrating their borrowing and/or lending activities to the DeFi space.

However, what if it were possible to 'carry over' existing TradFi borrowing data and write it to SBTs in a transparent and reliable manner? This idea occurred to me when reading about NovaCredit, a FinTech service that draws data from international borrowing histories to establish US-native credit scores for foreigners.

Autonolas' decentralized agents, with their ability to interact with both Web2 APIs and Web3 SBTs, enable the unique possibility of offering a similar service to transmit borrowing history between systems, both on & off-chain.

**Path to Implementation:** Corporations and businesses, like individuals, are given credit ratings and scores.

When a corporation sets up a wallet on-chain, an Autonolas service can be initialized to verify the ownership of the wallet using the publicly registered contact information for the company. Following this step, once the company provides consent, the Autonolas service will access the company's credit information and write it to the corresponding SBT and/or attest to its authenticity. Unlike for individuals, a business' credit information is typically openly available. This suggests that the information should be publishable to an SBT, without the fear of privacy violations.

When the wallet associated with the SBT performs any borrowing (either under or over-collateralized), the Autonolas service can write this information to the company's off-chain credit report on behalf of the decentralized lender. This will prove especially valuable as a deterrent to default, as it allows for the borrowing company's credit rating to be irreparably damaged.

This process can be modified to fit the privacy-preserving needs of individual users. For individuals, only credit scores will be published to SBTs with zero-knowledge proofs to verify computational integrity. Credit scores will be formulated using both on and off-chain activity through a publicly available algorithm. Since SBTs are linked to a wallet, the user's identity will remain private, provided the wallet is not used for interpersonal transactions.

For a lender to access the borrower's full off-chain credit history, they will first need to send the amount of the loan to the Autonolas service where it will be held for a fixed 'review' period (7 to 14 days) to prevent abuse. The transaction will include a memo with the lender's business email address to which the report will be sent. The report will not include any personal information. If the lender elects to proceed with the loan, they will send another transaction to the Autonolas service with a corresponding memo. If this transaction is not received, the funds held by the autonomous service will be automatically returned.

Once the loan is extended, details will be transmitted to credit bureaus in the borrower's financial region. In the event the Autonolas service detects a default, the lender will be able to request the borrower's identity to facilitate legal action.

**Note:** If the lender is required to be registered off-chain in certain jurisdictions, the Autonolas service could play the role of the lender in the eyes of the law. Since Autonolas services already require an on-chain bond for economic security, the decentralized lender could 'lend' the amount of the loan to the Autonolas service. The service could then, in turn, 'lend' the amount to the borrowing company.

(Unfortunately, none of us at Autonolas are lawyers. This idea may require a few modifications to meet the specific legal requirements of the jurisdictions where it acts.)

#### **#2**: Conditional Payouts for Legal Services
**Purpose:** Allow DAOs to employ legal representation and trustlessly release 'escrowed' payments, after public records confirm the completion of defined tasks.

**Overview:** As decentralized actors step into the realm of off-chain assets and contracts, the need for legal representation will begin to rear its head as agreements are inevitably broken. However, if a governance vote is required for each action, verifying and making payments for those legal tasks could quickly become quite cumbersome. While it is possible to assign the responsibility to a DAO member(s), doing so would represent a poor use of manpower and would require an expensive bond to prevent theft by the member(s).

Autonolas can provide a fairly straightforward solution by first interpreting the outcomes of the DAO's legal battles from public records and then making pre-negotiated payments on-chain.

**Path to Implementation:** Prior to employing legal representation for a specific case, governance polls can be held to decide upon the firm to be hired and the maximum funds which can be allocated.

The funds can then be given to an Autonolas service to hold in 'escrow' until the case's outcome has been reached. Once an outcome has been declared and the autonomous service has verified it using the public record, notarized receipts will be accepted from the legal firm. These receipts will detail the billable hours devoted to the case. 

Autonolas agents can be assigned to verify the authenticity of a few notarized documents at random. This can be achieved by contacting the notary via their registered email address and intelligently interpreting their responses with respect to different document IDs.
Following this process, the appropriate payment amount will be sent to the legal firm's on-chain wallet.

If some DAOs find billable hours too complex to manage, a different approach can be taken. Governance polls can be held to decide upon two sums - one which will be paid if the case is won and one if the case is lost. Once it has verified the outcome of the case via the public record, the Autonolas service will release the appropriate payment amount to the legal firm's wallet.

For those unsure as to whether AI platforms can consistently parse convoluted legal language to determine outcomes, here are some examples of what OpenAI is capable of now. We are not far from making such a service possible.

#### **#3**: Autonomous Alliances: DAO-to-DAO Alignment
**Purpose:** Allow DAOs to amass diverse treasuries, while maintaining competitive strategic partnerships with leading organizations in peer industries.

**Overview:** Frequently, partnerships between two DAOs take the form of the transfer of the respective governance tokens of both organizations via a 'DAO Swap'. Such swaps undoubtedly demonstrate concrete levels of commitment between the two communities involved. However, they provide somewhat poor motivators to ensure both parties receive consistent and capital-efficient returns.

As markets evolve and financial models mature, instances occur wherein one party gradually fails to receive efficient returns on the resources they contributed to the partnership. In such cases, imbalances in strategy can often appear, generating higher returns for the one party, at the cost of the other partner's resources.

Consequently, when the unsatisfied partner contemplates reassigning resources away from the venture, they can be met with significant friction due to the counterparty's possession of valuable governance tokens. Additionally, negotiating a one-sided restructure would require manpower from the side proposing changes to convince both communities. As a result, inefficient partnerships usually continue to exist in their initial form, unless massive imbalances occur to trigger change.

**Note**: This example assumes unusually rational actors on both sides who interact only through the mentioned partnership. The example means to highlight the resistance in resolving resource inefficiency within partnerships.

Considering this background, what if the economic barrier of withdrawing from a partnership could be lowered while simultaneously allocating treasury resources to more diverse and productive strategies?

Let us consider an example with two organizations, DAO α and DAO β:

**1. Organization Type:**

1.2 DAO α is a stablecoin issuer (Eg: Frax, MakerDAO)
1.3 DAO β offers a service with an accompanying utility token (Eg: ShapeShift, GMX)

**2. Organization Needs:**

2.2 DAO α requires CRV/CVX votes to secure liquidity for its stablecoin on Curve, one of the largest decentralized stablecoin markets.
2.3 DAO β requires TOKE votes to secure liquidity from a Tokemak reactor to pair with its token for low-slippage trades.

To meet these needs, a few options exist:

**1. Purchase CRV/TOKE tokens with treasury funds**

**Issue:** The value of tokens like CRV/CVX closely correlate to their native market. As overall stablecoin adoption increases -> Curve volume increases -> CRV demand increases -> CRV price increases & vice versa.

If regulators crack down on non-CBDC stablecoins in the future and (even temporarily) attempt to outlaw them, the CRV price may fall as a result.

If economic conditions/inflation cause users to shift to DeFi-native currencies such as BTC/OHM/RAI, CRV prices could fall. (Since BTC & OHM can't be easily paired on Curve due to impermanent loss, Curve users may gradually move to a more suitable DEX with impermanent loss protection)

In such situations, the stablecoin issuer would also be badly affected. However, in these extreme circumstances, if part of the issuer's treasury consisted of an asset from an unrelated industry, it would go a long way to ensuring the DAO's survival. Now, what if it were possible to leverage unrelated assets for CRV votes instead of purchasing CRV outright?

**2. Rent CRV/TOKE votes from a bribe marketplace (Eg: Votium/Hidden Hand)**

**Issue:** The cost of renting CRV/TOKE at the market rate is not constant. In fact, costs may see a gradual increase as DeFi becomes more saturated and new projects compete for resources such as liquidity.

**3. DAO α and DAO β form a flat rate voting partnership: DAO β holds CRV and DAO α holds TOKE; Both DAOs vote to fulfill the other DAO's needs**

**Advantages:**
Both DAOs are able to diversify by holding assets from separate industries.
Both DAOs will have a closely monitored line of communication since each plays an important role for the other. This can allow for mature inter-community relationships.
If either DAO feels their CRV/TOKE can be put to better use in a different partnership long-term, there are few barriers to withdrawing and reallocating.

So, how does Autonolas enable the implementation of option 3? Autonolas can act as a trustless intermediary, reading the results of DAO α's governance polls and seamlessly making corresponding votes using DAO β's CRV tokens. 

Also, if Autonolas detects votes from DAO α's TOKE tokens do not align with DAO β's governance polls, it can autonomously halt the agreement and notify DAO β.
In effect, DAO α's community will retain a long-term lease on a sum of CRV without exposure to CRV price-action. (The same for TOKE in DAO β's case.)

**Path to Implementation:** DAO α and DAO β both purchase the same value of CRV and TOKE tokens. As long as the relative value of CRV and TOKE do not diverge significantly long-term, the agreement can remain in place.

Following this step, the CRV and TOKE should be delegated to an Autonolas service. The service will monitor the results of governance polls from both DAOs and make corresponding votes using the appropriate tokens.

If the Autonolas service finds that either DAO has not upheld their end of the agreement or has withdrawn token access, the partnership can be halted. Both DAOs can then be notified to either revise or exit from the venture.

This strategy applies specifically to forming partnerships while diversifying treasuries. It would be inadvisable for DAO α to depend fully on DAO β for extremely important CRV votes. (DAO α should own most of the CRV it needs & DAO β should own most of the TOKE it needs.)

Thank you for taking the time to read through these thoughts! Once again, if you find any of them to be of interest to you or your team, visit our Discord to start a conversation with our community!

Written by [Odin.THOR](https://twitter.com/ODIN_Thorchain) - follow them on [Twitter](https://twitter.com/ODIN_Thorchain)!

Autonomous Augmentations — Volume Two 

_This is a guest post from the team behind El Collectooorr - the world's first autonomous NFT collector DAO, built by Academy grads and operated by independent agent operators._

**Introduction** 

El Collectooorr recently opened up the whitelist - which makes it the first autonomous service on Autonolas - built by graduates from the [Autonolas Academy](https://www.autonolas.network/academy), using Autonolas technology. At Autonolas, we wanted to provide a bit of information on what it is and how to find out more.

**What is El Collectooorr?**

El Collectooorr is a DAO and an autonomous NFT collector service - the service is designed to watch ArtBlocks drops and collect pieces using its built in algorithmic smarts. 

Collecting NFTs using El Collectooorr is designed to save depositooorrs time (the service monitors Artblocks around the clock), reduce the cost (through pooling funds), expand exposure (by collecting fractions of work, rather than single pieces) and take advantage of autonomous intelligence by collecting only the pieces that represent the best opportunities. 

**Join Us**

To see more of El Collectooorr and [join the whitelist](https://forms.gle/xqL94WxJLumcWa689), check out [our website](https://www.elcollectooorr.art/).  You can also get up to speed fast by reading this [introductory thread](https://twitter.com/elcollectooorr/status/1552563787290517504?s=20&t=SYuniZpd9kAD3NUVpM612A) or watching [this intro video ](https://bit.ly/3zQNSJW)and [this UI/UX demo](https://bit.ly/3QeKxK6). 

If you'd like to learn how to build your own apps and services with the power of Autonolas, check out the [Academy](https://www.autonolas.network/academy), and don't forget to [follow El Collectooorr on Twitter](https://twitter.com/elcollectooorr) for all the latest updates. 

The first community built, Autonolas-based service is now live

Community Showcase: El Collectooorr

We recently announced that Valory, the team creating Autonolas has made [a successful application through the Balancer Grants program](https://medium.com/@BalancerGrants/valory-is-building-smart-managed-pools-on-balancer-1b03a2f4cc89). If you'd like, you can [view the entire proposal](https://drive.google.com/file/d/1_WuEODpEKV7BR3LMKVLxyZUWjcGhHNRS/view) or read on for a quick summary of the project.

For this grant, the Valory team will be using Autonolas technology to build an MVP called a "Smart Managed Pool". These SMPs will be powered using autonomous services—you can learn [what those are](https://www.autonolas.network/education-articles/1) and [how they work](https://www.autonolas.network/education-articles/2) in these short education articles.

We're very excited to see these SMPs and their forks come to life, and many thanks go to the Balancer Grants committee for the selection!

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