Web3 Wallets with AI Personalization explores the emerging class of cryptocurrency wallets that embed AI-driven personal assistants and agent features directly in the wallet UX. As of early 2026, the field is shaped by two converging trends: LLM-powered agent frameworks (e.g., LangChain, Claude, Google Gemini) that make task automation and conversational workflows practical, and decentralized AI infrastructure (e.g., Tensorplex Labs) and blockchain-native developer stacks that prioritize on-chain data privacy, tokenized incentives, and verifiable compute. Wallet projects such as Solflare/theMiracle represent frontline examples of in-wallet AI: they surface transaction recommendations, contextualized portfolio insights, and guided DeFi operations while integrating secure key management and signatures. Complementary developer offerings — for example, Fire Bee’s Aptos-focused AI wallet development tooling — accelerate construction of these features for different chains. Payments and commerce are also evolving: Visa Intelligent Commerce (2025) foreshadows secure agent-driven purchasing flows that could be mirrored by wallets acting on users’ behalf. Enterprise assistants (IBM watsonx) and open LLMs (Claude, Gemini) provide the conversational backbone, while LangChain-style agent orchestration standardizes how wallets call models, on-chain data, and external services. Key considerations in comparing experiences include where models run (on-device vs cloud), how private keys and transaction intent are secured, whether model outputs are auditable, and how decentralized compute and incentives are governed. For users and developers, evaluating Solflare/theMiracle versus alternative in-wallet AI means weighing UX readiness, regulatory/compliance posture, data privacy, interoperability with DeFi and payments rails, and the underlying AI stack’s openness and latency. Together these elements define a pragmatic, cross-disciplinary landscape for personalized AI in Web3 wallets.