Ethereum’s transparency has lengthy been one among its best strengths, however for a lot of real-world functions, it has additionally turn out to be a structural limitation. From MEV-driven buying and selling inefficiencies to information leakage in DeFi, gaming, and AI-driven workflows, the idea that every thing should be public with the intention to be verifiable is more and more being challenged.
TEN Protocol is constructed round a unique premise: that computation can stay provably right with out forcing customers, builders, and companies to reveal delicate inputs, methods, or logic to the complete market.
On this CryptoSlate Q&A, the staff behind TEN Protocol explains its idea of “compute in confidence” and why they consider privacy-first execution is a lacking primitive in Ethereum’s scaling roadmap.
Moderately than launching a separate privateness ecosystem, TEN is designed as a full EVM surroundings anchored to Ethereum settlement and liquidity, permitting builders to selectively select what ought to stay public and what ought to execute confidentially.
The dialogue explores how this hybrid mannequin reshapes person expertise, mitigates MEV, allows sealed-bid markets and hidden order move, and unlocks new classes of functions, from verifiable AI brokers to provably truthful iGaming.
It additionally addresses the safety and governance trade-offs of utilizing Trusted Execution Environments, and the way TEN’s structure is designed to make failures detectable, contained, and recoverable reasonably than silently catastrophic.
Collectively, the Q&A provides an in depth take a look at how selective confidentiality might redefine belief, composability, and usefulness throughout the Ethereum ecosystem. 
For readers who’re new to TEN Protocol, how do you clarify in easy phrases what “compute in confidence” means and what downside TEN is definitely fixing that current Ethereum L2s don’t?
At its easiest, “compute in confidence” means you should utilize a dapp with out broadcasting your intent, your technique, or your delicate information to everybody watching the chain.
On most Ethereum L2s at present, transparency is the default. Each transaction, its parameters, the intermediate execution steps and sometimes even the “why” behind an motion are seen. That degree of openness is highly effective for verification, however in observe it creates very actual issues. Trades get front-run or sandwiched. Wallets and dapps leak behavioural and financial information. Video games and auctions battle to remain each truthful and personal. And plenty of real-world or enterprise workflows merely can’t function if inputs and logic should be public by design.
That is the core structural limitation TEN addresses. Ethereum was constructed on the idea that information should be seen with the intention to be verifiable. TEN retains verifiability intact, however removes the concept information itself needs to be uncovered. With the proper privateness know-how, you’ll be able to show computation is right with out revealing the underlying inputs or logic.
What meaning in observe is confidence. Confidence that node operators can’t front-run you. That video games aren’t quietly rigged. That bids aren’t being copied in actual time. That opponents aren’t spying on technique. That dapps aren’t extracting or monetising personal person inputs.
You continue to get Ethereum-grade safety and verification. You simply don’t should put every thing on show to get it.
There are different privacy-focused and TEE-oriented tasks in crypto; what’s concretely totally different about TEN’s structure and menace mannequin in comparison with issues like privateness L1s, rollups with off-chain proving, or MPC-based approaches?
TEN is constructed as privacy-first Ethereum execution, not as a parallel ecosystem. The purpose may be very slender and really intentional: run EVM-style functions with selective confidentiality, whereas holding settlement, composability, and liquidity anchored to Ethereum itself.
That design selection is what actually units TEN aside in observe.
If you happen to take a look at privateness L1s, they usually ask builders to maneuver into a brand new world. New tooling, new execution semantics, and totally different assumptions round composability are widespread. TEN takes the other method. It’s meant to really feel like Ethereum, not substitute it. Builders preserve the EVM, the requirements they already use, and entry to current liquidity, whereas gaining confidentiality solely the place it really issues.
ZK-based personal execution provides extraordinarily sturdy privateness ensures, however these ensures normally include trade-offs for general-purpose functions. Circuit complexity, efficiency constraints, and developer friction could make on a regular basis app growth more durable than it must be. TEN makes use of TEEs as a substitute, concentrating on general-purpose confidential compute with a really totally different efficiency and developer-experience profile.
MPC-based approaches keep away from trusting {hardware} distributors, which is an actual benefit, however they introduce their very own challenges. Coordination overhead, latency, and operational complexity can shortly translate right into a poor person expertise for regular functions. TEN accepts a hardware-rooted belief assumption, after which focuses on mitigating it via governance, redundancy, and rigorous safety engineering.
On the core, the differentiator is that this hybrid mannequin. Issues that must be public, like finality, auditability, and settlement, keep public. Issues that should be personal, like inputs, order move, methods, and secret state, stay confidential.
You speak about TEN making crypto really feel like “regular apps” for finish customers, personal, easy, reliable; what does that seem like from a UX perspective, and the way will utilizing a TEN powered dapp really feel totally different from utilizing a typical Ethereum dapp at present?
At a person degree, it removes the fixed feeling that every thing you do is seen and doubtlessly exploitable.
In a TEN-powered dapp, that reveals up in small however significant methods. There’s no mempool nervousness and no watching your trades get sandwiched in actual time. Intent is personal by default, whether or not that’s bids, methods, or execution thresholds. Customers don’t should depend on defensive workarounds like personal RPCs or guide slippage hacks simply to really feel secure utilizing an app.
What you’re left with is a a lot cleaner psychological mannequin, one which’s nearer to Web2. You assume that your inputs and the appliance’s enterprise logic aren’t mechanically public, as a result of in most software program, they aren’t.
The shift itself is refined, but it surely’s basic. Privateness stops being a bolt-on characteristic or a complicated setting solely energy customers perceive, and as a substitute turns into a core product primitive that’s merely there by default.
Trusted Execution Environments introduce a unique type of belief assumption, particularly reliance on {hardware} distributors and enclave safety; how do you tackle issues about side-channel assaults, backdoors, or vendor-level failures in your safety and governance mannequin?
That’s precisely the proper of skepticism. TEN’s place isn’t that TEEs are magic or risk-free. It’s about being specific in regards to the menace mannequin and designing the system so {that a} compromise isn’t silently catastrophic.
TEN assumes enclaves present confidentiality and integrity inside outlined bounds, after which builds round that assumption reasonably than pretending it doesn’t exist. The purpose is to make failures detectable, contained, and recoverable, not invisible.
From a safety perspective, this reveals up as defense-in-depth. There are sturdy distant attestation necessities, managed code measurement and reproducible builds, and strict key-management practices, together with sealed keys, rotation, and tightly scoped permissions. The enclave assault floor is intentionally minimized, with as little privileged code as potential working inside it.
Redundancy and fail-safe design are simply as essential. TEN avoids architectures the place one enclave successfully guidelines the system. The place potential, it depends on multi-operator assumptions and constructions protocols in order that even a compromised enclave can’t rewrite historical past or forge settlement on Ethereum.
Governance and operational readiness full the image. Safety isn’t solely about cryptography; it’s additionally about how shortly and transparently a system can reply. That features patching, revocations, enclave model pinning, and clear incident playbooks that may be executed with out ambiguity.
The underside line is that this: TEN isn’t asking customers to “belief nothing.” It’s about lowering the sensible belief it’s essential to place in operators and counterparties, and concentrating the remaining belief right into a a lot narrower, auditable floor.
On the DeFi aspect, how do sealed-bid auctions, hidden order books, and MEV-resistant routing really work on TEN in observe, and the way can customers or regulators achieve confidence in techniques the place the core buying and selling logic and order move are deliberately encrypted?
At a excessive degree, TEN works by altering what’s public by default.
Take sealed-bid auctions. As an alternative of broadcasting bids within the clear, customers submit them in encrypted kind. The public sale logic runs inside a TEE, so particular person bids are by no means uncovered throughout execution. Relying on how the public sale is designed, bids could solely be revealed at settlement, or not revealed in any respect, with solely the ultimate consequence revealed on-chain. That single change eliminates bid sniping, copy-trading, and the strategic leakage that plagues open auctions at present.
The identical thought applies to hidden order books. Orders aren’t seen in a method that lets others reconstruct intent or technique in actual time. Merchants are protected against being systematically copied or exploited, whereas the system nonetheless produces execution outcomes that may be verified after the very fact.
MEV-resistant routing follows naturally from this mannequin. As a result of person intent isn’t broadcast to a public mempool, the traditional MEV pipeline of see, copy, and sandwich merely doesn’t exist. There’s nothing to front-run within the first place.
That naturally raises the belief query. If the core logic and order move are encrypted, how can customers or regulators be assured the system is behaving accurately?
The reply is that TEN separates privateness of inputs from verifiability of outcomes. Even when inputs are personal, the foundations are usually not. Anybody can verify that the matching engine adopted the revealed algorithm, that clearing costs have been computed accurately, and that no hidden desire or manipulation came about.
On prime of that, there are clear audit surfaces and mechanisms for selective disclosure. Regulators or auditors may be granted entry beneath outlined circumstances, whereas the general public nonetheless sees cryptographic commitments and on-chain proofs that execution was right.
The result’s a mixture that’s uncommon in at present’s DeFi: confidentiality of order move paired with accountability of outcomes.
Verifiable AI brokers are one among your flagship use instances; are you able to stroll via a concrete instance of an AI agent working on TEN, what stays personal, what’s publicly verifiable on-chain, and why that’s higher than working the identical agent completely off-chain?
A easy method to consider that is an AI-driven treasury rebalancer for a protocol.
When that agent runs on TEN, a variety of what makes it worthwhile stays personal by design. The mannequin weights or prompts, which are sometimes the core mental property, by no means should be uncovered. Proprietary alerts and paid information feeds stay confidential. Inner danger limits, intermediate reasoning, and choice logic aren’t leaked to the market. Even the execution intent stays personal till the second it’s dedicated.
On the identical time, there’s a transparent set of issues which might be publicly verifiable on-chain. Anybody can verify that the accredited code really ran, by way of attestation. They will confirm that a licensed coverage module enforced the related constraints, and that the ensuing actions revered the outlined invariants. The ultimate state transitions and settlement nonetheless occur on Ethereum, within the open, as ordinary.
That mixture is what makes this meaningfully higher than working the identical agent completely off-chain. Off-chain brokers finally ask customers to belief logs, operators, or unverifiable claims that “the bot adopted the foundations.” TEN removes that blind belief. It lets brokers preserve their aggressive edge personal, whereas nonetheless proving to customers, DAOs, and counterparties that they acted strictly inside their mandate.
iGaming has traditionally been suffering from belief points, bots, and opaque RNG; how does TEN allow provably truthful video games whereas nonetheless holding RNG seeds, anti bot logic, and sport methods personal, and the way do you see this becoming into current regulatory frameworks for on-line gaming?
iGaming has at all times been constructed round a basic battle: transparency is required to show equity, however secrecy is crucial to guard RNG techniques, safety controls, and anti-bot logic. Expose an excessive amount of, and the system is gamed. Conceal an excessive amount of, and belief collapses.
TEN resolves that battle via selective confidentiality. Delicate elements keep personal, whereas the foundations and outcomes stay provable.
On randomness, this enables “provably truthful” to be literal reasonably than aspirational. Video games can use commit-reveal and verifiable randomness schemes the place randomness is dedicated to prematurely, outcomes are independently verifiable by gamers, and RNG seeds stay personal till it’s secure to reveal, or are solely partially revealed. Gamers get confidence in equity with out attackers gaining a usable blueprint.
The identical precept applies to anti-bot and danger controls. Bot-detection heuristics and fraud techniques run confidentially, which issues as a result of as soon as these mechanisms are public, subtle actors adapt instantly. Protecting them personal preserves their effectiveness whereas nonetheless permitting the system to supply verifiable outcomes.
Extra broadly, this allows provable sport integrity. Gamers can confirm {that a} sport adopted its revealed guidelines and that outcomes weren’t manipulated, with out exposing delicate internals like safety logic, thresholds, or technique parameters.
From a regulatory perspective, this maps cleanly onto current frameworks. Regulators sometimes care about auditability, equity ensures, and enforceable controls, not about forcing each inner mechanism into the open. TEN’s mannequin of verifiable outcomes mixed with selective disclosure aligns naturally with these necessities.
From a developer’s viewpoint, what does constructing a “selectively personal” sensible contract on TEN seem like, how do they mark capabilities for TEE execution, and the way do they take a look at and debug logic that they can’t simply log off to a public mempool?
From a developer’s viewpoint, the best method to consider TEN is that you just’re constructing with two execution zones.
There’s a public zone, which looks like regular Ethereum growth: customary EVM logic, public state, and composable contracts that behave the best way you count on on any L2.
Then there’s the confidential zone, the place particular capabilities and items of state execute inside TEEs, with encrypted inputs and tightly managed disclosure.
In observe, builders explicitly resolve what ought to run “in confidence” and what ought to stay public. The confidential aspect is the place you’d put issues like commerce matching, RNG, technique analysis, or secret storage, whereas every thing else stays within the open for composability and settlement.
The workflow shift reveals up most in testing and debugging, as a result of you’ll be able to’t deal with the general public mempool as your always-on debug console. As an alternative, testing and debugging sometimes leans on native devnets with enclave-like execution, deterministic take a look at vectors, and managed debug modes throughout growth. And reasonably than counting on public logs, you validate behaviour via verifiable commitments and invariants, proving that the system stayed inside the guidelines even when the inputs are personal.
The important thing change is shifting away from mempool introspection as a debugging crutch, and designing for provable correctness from the beginning.
You spotlight composability between personal and public elements as a key differentiator; what new utility patterns do you count on to emerge from this hybrid mannequin, and the way can current Ethereum protocols combine TEN with out utterly rewriting their stack?
TEN’s hybrid mannequin unlocks utility patterns which might be both extraordinarily tough or just not potential on chains which might be clear by default.
One apparent sample is personal execution with public settlement. Delicate logic like commerce matching, technique analysis, RNG, or danger controls can run confidentially, whereas the ultimate outcomes nonetheless settle publicly on Ethereum. You get privateness the place it issues, with out giving up verifiability or composability.
One other space is protected value discovery and darkish liquidity. Sealed bids, hidden order books, and personal routing make it potential to run fairer markets, whereas nonetheless producing outcomes which might be verifiable on-chain. The market will get integrity with out turning each participant’s intent into public information.
Video games and AI brokers are one other pure match. Palms, methods, prompts, or mannequin internals can stay personal, whereas equity, correctness, and settlement keep provable. That mixture may be very laborious to attain in a totally clear execution surroundings.
You additionally begin to see selective disclosure functions emerge. Issues like identification, fame, compliance, or eligibility checks can keep personal, whereas nonetheless imposing public guidelines and producing auditable outcomes.
What makes TEN distinct is that none of this requires abandoning Ethereum. TEN is a full EVM, so current Ethereum sensible contracts deploy on TEN out of the field and behave precisely as builders count on. The distinction is that they instantly achieve the choice to run elements of their logic in confidence.
For a lot of protocols, integration may be simple. Groups can deploy the identical contracts to TEN alongside Ethereum, preserve the general public model unchanged, after which progressively allow confidential execution the place it provides essentially the most worth.
That naturally creates two adoption paths. Some groups will take the minimal-effort route, deploying current contracts unchanged and gaining each a public and confidential occasion with virtually no additional work. Others will take a progressive method, selectively shifting high-value flows like order move, auctions, video games, or agent logic into confidential execution over time.
The important thing level is that TEN doesn’t drive builders to decide on between composability and confidentiality. It lets them preserve Ethereum’s ecosystem, liquidity, and tooling, whereas making privateness a first-class functionality reasonably than a bolt-on.
Who operates the enclaves and infrastructure that energy TEN, how do you keep away from centralization round a small set of operators, and what does the roadmap seem like for decentralizing the community, bootstrapping the ecosystem, and attracting the primary breakout apps on TEN?
Like most new networks, TEN begins with a sensible bootstrap section. Early on, meaning a smaller, extra curated set of operators and infrastructure, with the main target squarely on reliability and safety. The purpose at this stage isn’t maximal decentralization on day one, however ensuring the system works predictably and safely as builders begin constructing actual functions on it.
Avoiding long-term centralization is the place the structure and incentives actually matter. The roadmap is constructed round permissionless operator onboarding, paired with sturdy attestation necessities so operators can show they’re working the proper code in the proper surroundings. Financial incentives are designed to encourage many unbiased operators reasonably than a small cartel, and there’s an specific emphasis on geographic and organizational range. On prime of that, efficiency and safety standards are clear, and the protocol itself is structured to forestall any single operator from dominating execution.
By way of how the roadmap unfolds, the primary section is about bootstrapping reliability and developer tooling. As soon as that basis is stable, the main target shifts to delivery flagship functions that genuinely want confidentiality, issues like iGaming, protected DeFi workflows, and verifiable AI brokers. From there, operator participation expands, governance decentralizes, and the safety posture continues to harden as extra worth flows via the community and the stakes rise.
That’s what units up the ecosystem flywheel. Builders don’t come to TEN simply because it’s one other EVM; they arrive as a result of it provides capabilities they’ll’t get elsewhere.
The breakout app thesis is easy. The primary actually profitable TEN-native utility might be one thing that both can’t exist, or can’t be aggressive, on transparent-by-default chains. In that case, confidentiality isn’t a checkbox characteristic. It’s the product itself.
