Ethereum’s transparency has lengthy been one in every of its best strengths, however for a lot of real-world purposes, it has additionally turn into a structural limitation. From MEV-driven buying and selling inefficiencies to information leakage in DeFi, gaming, and AI-driven workflows, the idea that all the things should be public with a purpose to be verifiable is more and more being challenged.
TEN Protocol is constructed round a special 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.
Fairly 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 consumer expertise, mitigates MEV, allows sealed-bid markets and hidden order movement, and unlocks new classes of purposes, from verifiable AI brokers to provably honest 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 slightly than silently catastrophic.
Collectively, the Q&A affords an in depth have a look at how selective confidentiality may redefine belief, composability, and value 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 drawback TEN is definitely fixing that present Ethereum L2s don’t?
At its easiest, “compute in confidence” means you should use 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 stage of openness is highly effective for verification, however in follow it creates very actual issues. Trades get front-run or sandwiched. Wallets and dapps leak behavioural and financial information. Video games and auctions wrestle to remain each honest and personal. And plenty of real-world or enterprise workflows merely can’t function if inputs and logic need to be public by design.
That is the core structural limitation TEN addresses. Ethereum was constructed on the idea that information should be seen with a purpose to be verifiable. TEN retains verifiability intact, however removes the concept that information itself needs to be uncovered. With the fitting privateness know-how, you possibly can show computation is right with out revealing the underlying inputs or logic.
What meaning in follow 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 consumer inputs.
You continue to get Ethereum-grade safety and verification. You simply don’t need to put all the things on show to get it.
There are different privacy-focused and TEE-oriented tasks in crypto; what’s concretely completely 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 objective could be very slim and really intentional: run EVM-style purposes with selective confidentiality, whereas retaining settlement, composability, and liquidity anchored to Ethereum itself.
That design selection is what actually units TEN aside in follow.
For those who have a look at privateness L1s, they usually ask builders to maneuver into a brand new world. New tooling, new execution semantics, and completely different assumptions round composability are widespread. TEN takes the alternative method. It’s meant to really feel like Ethereum, not exchange it. Builders hold the EVM, the requirements they already use, and entry to present liquidity, whereas gaining confidentiality solely the place it really issues.
ZK-based personal execution affords extraordinarily robust privateness ensures, however these ensures often include trade-offs for general-purpose purposes. Circuit complexity, efficiency constraints, and developer friction could make on a regular basis app improvement more durable than it must be. TEN makes use of TEEs as a substitute, concentrating on general-purpose confidential compute with a really completely 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 consumer expertise for regular purposes. TEN accepts a hardware-rooted belief assumption, after which focuses on mitigating it by way of 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 movement, 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 appear to be from a UX perspective, and the way will utilizing a TEN powered dapp really feel completely different from utilizing a typical Ethereum dapp at present?
At a consumer stage, it removes the fixed feeling that all the things you do is seen and probably 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 need to depend on defensive workarounds like personal RPCs or handbook 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 routinely public, as a result of in most software program, they aren’t.
The shift itself is delicate, however it’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 special form of belief assumption, specifically reliance on {hardware} distributors and enclave safety; how do you handle 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 express in regards to the menace mannequin and designing the system so {that a} compromise is rarely silently catastrophic.
TEN assumes enclaves present confidentiality and integrity inside outlined bounds, after which builds round that assumption slightly than pretending it doesn’t exist. The objective is to make failures detectable, contained, and recoverable, not invisible.
From a safety perspective, this reveals up as defense-in-depth. There are robust 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 doable working inside it.
Redundancy and fail-safe design are simply as vital. TEN avoids architectures the place one enclave successfully guidelines the system. The place doable, 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 facet, how do sealed-bid auctions, hidden order books, and MEV-resistant routing really work on TEN in follow, and the way can customers or regulators acquire confidence in techniques the place the core buying and selling logic and order movement are deliberately encrypted?
At a excessive stage, 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 might solely be revealed at settlement, or not revealed in any respect, with solely the ultimate end result 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 means 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 actual fact.
MEV-resistant routing follows naturally from this mannequin. As a result of consumer intent is rarely 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 movement 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 principles aren’t. Anybody can verify that the matching engine adopted the revealed algorithm, that clearing costs had been computed accurately, and that no hidden choice or manipulation passed off.
On high of that, there are clear audit surfaces and mechanisms for selective disclosure. Regulators or auditors might be granted entry underneath outlined situations, whereas the general public nonetheless sees cryptographic commitments and on-chain proofs that execution was right.
The result’s a mix that’s uncommon in at present’s DeFi: confidentiality of order movement paired with accountability of outcomes.
Verifiable AI brokers are one in every of your flagship use circumstances; are you able to stroll by way of 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 totally off-chain?
A easy means to consider that is an AI-driven treasury rebalancer for a protocol.
When that agent runs on TEN, plenty of what makes it useful stays personal by design. The mannequin weights or prompts, which are sometimes the core mental property, by no means need to be uncovered. Proprietary alerts and paid information feeds stay confidential. Inner threat limits, intermediate reasoning, and resolution 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 can be publicly verifiable on-chain. Anybody can verify that the authorized code really ran, through 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 normal.
That mixture is what makes this meaningfully higher than working the identical agent totally off-chain. Off-chain brokers finally ask customers to belief logs, operators, or unverifiable claims that “the bot adopted the principles.” TEN removes that blind belief. It lets brokers hold their aggressive edge personal, whereas nonetheless proving to customers, DAOs, and counterparties that they acted strictly inside their mandate.
iGaming has traditionally been stricken by belief points, bots, and opaque RNG; how does TEN allow provably honest video games whereas nonetheless retaining RNG seeds, anti bot logic, and sport methods personal, and the way do you see this becoming into present regulatory frameworks for on-line gaming?
iGaming has all the time 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 by way of selective confidentiality. Delicate elements keep personal, whereas the principles and outcomes stay provable.
On randomness, this enables “provably honest” to be literal slightly than aspirational. Video games can use commit-reveal and verifiable randomness schemes the place randomness is dedicated to upfront, 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 threat 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. Preserving them personal preserves their effectiveness whereas nonetheless permitting the system to provide verifiable outcomes.
Extra broadly, this permits 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 present 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” good contract on TEN appear to be, how do they mark features 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 simplest means to consider TEN is that you just’re constructing with two execution zones.
There’s a public zone, which seems like regular Ethereum improvement: commonplace EVM logic, public state, and composable contracts that behave the way in which you anticipate on any L2.
Then there’s the confidential zone, the place particular features and items of state execute inside TEEs, with encrypted inputs and tightly managed disclosure.
In follow, builders explicitly resolve what ought to run “in confidence” and what ought to stay public. The confidential facet is the place you’d put issues like commerce matching, RNG, technique analysis, or secret storage, whereas all the things else stays within the open for composability and settlement.
The workflow shift reveals up most in testing and debugging, as a result of you possibly can’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 improvement. And slightly than counting on public logs, you validate behaviour by way of verifiable commitments and invariants, proving that the system stayed throughout 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 software patterns do you anticipate to emerge from this hybrid mannequin, and the way can present Ethereum protocols combine TEN with out utterly rewriting their stack?
TEN’s hybrid mannequin unlocks software patterns which can be both extraordinarily tough or just not doable on chains which can be clear by default.
One apparent sample is personal execution with public settlement. Delicate logic like commerce matching, technique analysis, RNG, or threat 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 doable to run fairer markets, whereas nonetheless producing outcomes which can 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. Arms, methods, prompts, or mannequin internals can stay personal, whereas equity, correctness, and settlement keep provable. That mixture could be very exhausting to attain in a totally clear execution surroundings.
You additionally begin to see selective disclosure purposes emerge. Issues like identification, status, 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 present Ethereum good contracts deploy on TEN out of the field and behave precisely as builders anticipate. The distinction is that they instantly acquire the choice to run elements of their logic in confidence.
For a lot of protocols, integration might be easy. Groups can deploy the identical contracts to TEN alongside Ethereum, hold the general public model unchanged, after which progressively allow confidential execution the place it provides probably the most worth.
That naturally creates two adoption paths. Some groups will take the minimal-effort route, deploying present contracts unchanged and gaining each a public and confidential occasion with virtually no further work. Others will take a progressive method, selectively shifting high-value flows like order movement, auctions, video games, or agent logic into confidential execution over time.
The important thing level is that TEN doesn’t pressure builders to decide on between composability and confidentiality. It lets them hold Ethereum’s ecosystem, liquidity, and tooling, whereas making privateness a first-class functionality slightly 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 appear to be 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 focus squarely on reliability and safety. The objective at this stage isn’t maximal decentralization on day one, however ensuring the system works predictably and safely as builders begin constructing actual purposes 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 robust attestation necessities so operators can show they’re working the fitting code in the fitting surroundings. Financial incentives are designed to encourage many impartial operators slightly than a small cartel, and there’s an express emphasis on geographic and organizational variety. On high of that, efficiency and safety standards are clear, and the protocol itself is structured to stop 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 strong, the main focus shifts to transport flagship purposes 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 by way of 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 affords capabilities they’ll’t get elsewhere.
The breakout app thesis is easy. The primary really profitable TEN-native software can 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.
