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Intuition: Building the Missing Trust Layer in Web3

Summary: The vision of Intuition is to add a "trust layer" to Web3 in the form of a decentralized, token-incentivized knowledge graph.
Project Trends
2025-09-01 14:04:02
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The vision of Intuition is to add a "trust layer" to Web3 in the form of a decentralized, token-incentivized knowledge graph.

Source: 0xIntuition

Compiled by: Zhou, ChainCatcher

In the cryptocurrency space, "Don't trust, verify" is a common mantra. Blockchain technology was born from the idea that we can replace human trust with objective code—creating trustless systems where mathematics and algorithms can enforce honesty. In an ideal world, Web3 would allow us to transact and collaborate without having to take anyone's word for it. But in reality, the cryptocurrency ecosystem is far from completely trustless. As anyone who has spent time in the financial "wild west" knows, we rely on people, sources of information, and social consensus at almost every turn.

The fact is, while blockchains can eliminate certain intermediaries, they cannot completely eliminate trust. Some key layers of the Web3 "stack" still operate on trust—trust in people, in data, in the chain of custody. In fact, as cryptocurrency becomes increasingly complex, trust and distrust are equally important. This article explores why trust remains crucial in cryptocurrency, where our current trust gaps are, and how we can make Web3 more "trustworthy" by adding better information and incentives. We will introduce Intuition, an ambitious approach that brings trust to trustless systems through a decentralized, token-driven knowledge graph.

Let’s delve into why even trustless networks need a layer of trust and how Intuition builds that trust layer.

The Myth of Complete Trustlessness in Cryptocurrency

Blockchain enthusiasts often tout Web3 as "trustless." By design, blockchain networks do not require trust in a central authority; consensus algorithms like proof of work or proof of stake allow strangers to agree on the state of a ledger without knowing each other. In theory, code and cryptography replace human subjective trust.

However, the term "trustless" is somewhat misleading. Even in "trustless" systems, trust does not disappear—it shifts to different parts of the system. Let’s consider some ways trust still plays a role in today’s cryptocurrency:

Trust in protocols and code: You may not trust banks, but you do trust the code of smart contracts or the rules of blockchain protocols. Unless you can personally audit every contract you interact with (an impossible task for most), you implicitly trust the developers who wrote the code and the auditors who reviewed it. When you use a DeFi platform, you trust that the smart contracts won’t fail or be malicious. History shows that this trust can be misplaced—countless hacks and exploits (due to faulty code or hidden backdoors) have led to loss of funds.

Trust in people and governance: Decentralized networks are operated by communities, which have leaders or core contributors. For example, proof of stake blockchain consensus—often considered "trustless"—actually requires trusting that the majority of validators (who are individuals or organizations) will act honestly. If a small number of large stakers collude, they could compromise the network. Additionally, key upgrades or emergency decisions (like how to handle a major hack) often come down to social consensus—the community must trust each other and agree on a solution. In practice, every blockchain ultimately relies on a layer of social trust between its users and node operators. It has been said that for blockchains, "it’s social consensus." In other words, humans still decide which chain or version of the truth to accept.

Trust in off-chain data and services: Most real-world applications require data from outside the blockchain (prices, weather information, identity verification, etc.). This data often comes from oracles or external sources that users must trust to be accurate. Similarly, if you use a cryptocurrency exchange or wallet application, you trust that their interface will show you real data and that their servers are secure. Even something as simple as a blockchain explorer—we trust it to accurately report transactions and balances.

Trust in institutions and intermediaries: Despite the spirit of "everything decentralized," the cryptocurrency space still relies on many centralized entities. Think of custodial exchanges (where users deposit funds), stablecoin issuers (whose reserves we trust to maintain value), or developers who control the keys for managing protocol upgrades. The collapse of major exchanges and projects due to mismanagement (like exchange hacks or founder fraud) highlights that blind trust in code is insufficient; we ultimately also trust the people behind the code, which can sometimes lead to disastrous consequences.

In short, the ideal of "trustlessness" has its limitations. We can eliminate certain trust requirements (like not needing to trust a bank's ledger), but we inevitably introduce other forms of trust (trust in code, governance, data feeds, etc.). Cryptocurrency is still in its infancy, full of unknowns, with bad actors exploiting information gaps. Scams, rug pulls, and misinformation are rampant, precisely because there is no robust Web3 equivalent that provides the protections and verified information we expect in traditional environments. To move forward, we must acknowledge that certain layers cannot yet be completely trustless—but rather focus on making them more trustworthy.

Why Web3 Needs a "Trustworthy" Interaction Layer

If we accept that not everything in Web3 can be purely trustless, the question becomes: how do we inject more trust into those inevitable gaps? The answer lies in better information and transparency. In a sense, knowledge is the antidote to blind trust. The more we know about a person, a contract, or a project, the less we need to rely on blind trust. Better data can clarify risks, verify claims, and expose fraud before it traps users.

Unfortunately, the current information landscape in cryptocurrency is fragmented and unreliable. Important facts are hard to find, and due diligence often means spending hours searching various sources. Let’s analyze where our information (and trust) currently comes from:

1. Data is scattered across the internet: There is a wealth of cryptocurrency-related data online—forum posts, news articles, Twitter threads, blockchain records, audit reports, and more. In theory, everything needed to evaluate a project or person could exist. In practice, this data is highly fragmented and isolated. Each exchange, social platform, or analytics site holds a piece of the puzzle, but there is no unified method to sift through it all. Even if you gather data, attribution is a challenge: is this source credible? Who wrote this comment, and can we verify their identity or reputation? Online information is easily manipulated—fake reviews, scam accounts, biased reports—making it tricky to trust. Moreover, much valuable data is hidden behind closed doors (think private chats, proprietary databases, or simply not indexed by search engines). The bottom line: the data is out there, but it is chaotic, disorganized, and hard to trust.

2. Knowledge is locked in people's minds: The most reliable information often isn’t publicly available—it lives with experienced individuals. In the cryptocurrency space, reputations and danger signals spread through informal channels: one investor warns another about a rough founder, or a developer gives a thumbs-up privately before working with someone. Human insight is incredibly valuable, but it is mostly exchanged in ad-hoc ways (private messages, phone calls, closed groups). If you want to know the real story behind a project, you often have to ask around. For example, due diligence on a new token might require manually reaching out to contacts: "Hey, have you heard of this team? Any red flags?" This process is inefficient and exclusive—only those with the right networks can access insights. Most people won’t share their full knowledge publicly, so a lot of "trust data" simply doesn’t get captured online.

Given these issues, it’s no wonder newcomers feel lost, and even veterans can fall victim to scams. Cryptocurrency needs a better way to aggregate and verify information—a system that transforms subjective trust (reputation, opinions, private knowledge) into objective data that anyone can use. In other words, we need to make the untrustworthy parts of Web3 more "trustworthy."

Trust doesn’t mean going back to blind faith; it means creating structures that earn trust and are verifiable. If certain layers (like understanding a project’s credibility) can’t be purely handled by code, then let’s find ways to inject rich, reliable information into these layers so that users can trust in an informed manner. This is especially important now: the openness of cryptocurrency gives us unparalleled freedom, but this freedom comes with personal responsibility. Without better trust signals, many people will either get burned or completely avoid the space. To welcome the next wave of users (and institutional investors), we must tame the chaos with transparent collective knowledge.

Intuition: Bringing Trust to Trustless Systems

Intuition is a new project born from this realization—trustlessness alone is not enough; what’s missing is an open system for managing trust and knowledge. The vision of Intuition is to add a "trust layer" to Web3 in the form of a decentralized, token-incentivized knowledge graph. This sounds convoluted, so let’s break it down in simpler terms:

At its core, Intuition aims to build a crowdsourced database of claims and reputations—a universal "who said what" ledger that exists on the blockchain. The idea is to transform weak, subjective trust points (opinions, proofs, comments, context) into structured data that anyone can verify and contribute to. Importantly, Intuition not only collects this information but also curates it. It rewards people for providing honest, useful input with a native token (aptly named $TRUST). Think of it as a living knowledge network where data about people, projects, and any concept is continuously updated and ranked based on community confidence.

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