dBOOK Whitepaper
  • Introduction
    • Overview
    • Why dBOOK?
    • Architecture
  • Service lifecycle
  • Core Components
    • Intelligence Engine
      • LLM
      • Model Context Protocol
    • Settlement Engine
      • Home Chain
      • Operators
      • Validators
      • Path Finder
      • Accounts
    • Recommendation Engine
      • Protocol & Metadata Registry
      • Context Module
  • Core Concepts
    • Hybrid Ranking System
    • Challenge Flow
    • Asset Accounting
    • Endpoints
    • Threshold Signatures
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  • Reframing Web3 Through a Supply Chain Lens
  • dBOOK: Fixing Discovery and Distribution in Web3
  1. Introduction

Reframing Web3 Through a Supply Chain Lens

When we think of Web3 as a supply chain, it becomes clear where the bottlenecks are. Protocols and blockchains represent the supply, while wallets serve as the primary channel of distribution. Unfortunately, this “supply chain” faces two major obstacles:

Fragmented vs. Integrated Discovery

In Web2, discovery happens within the flow of everyday behavior—TikTok, for instance, integrates product recommendations right into the scrolling experience. By contrast, Web3 lacks a solution that weaves product discovery into users’ normal routines.

Complex Distribution

Even after discovering a protocol, users must wrestle with multiple wallets, bridges, and chains to actually interact with it. This convoluted workflow often causes drop-offs before a transaction is finalized. It’s like trying to ship a product through multiple carriers and checkpoints—extra steps that introduce unnecessary friction.

dBOOK: Fixing Discovery and Distribution in Web3

If there’s one application every Web3 user interacts with, it’s their wallet. dBOOK embeds a chat intelligence system directly into any wallet, enabling users to work across any chain without juggling multiple wallets or worrying about network specifics. They simply specify what they want to do, and dBOOK determines the best execution path.

On top of that, dBOOK delivers stateless recommendations deriving context from actions at exactly the right time. If a user bridges funds to Solana, for instance, they’ll see relevant airdrop opportunities on Solana. If they’re swapping a meme token for stablecoins, dBOOK suggests stable yield protocols—maximizing the chance of conversion. By integrating both discovery and execution into a single flow, dBOOK eliminates fragmentation, reduces friction, and makes Web3 as seamless as it was always meant to be.

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Last updated 2 months ago