Web3 in Travel

I could not find how to cancel limit orders in my Safe wallet. Claude Code built a JSON transaction file; I imported it, ran a simulation and signed the cancellation myself.
I also share my loss-making Token Trade experiment, why I prefer chat to complicated dashboards, and the possibilities for agent payments. The closing discussion explores AI wallet risks, decentralized travel and Trips Community, and a future where we express our intent to an agent. I am not claiming AI wallets are safer or right for every use case.

Collaborations: info@web3intravel.com
CHAPTERS
0:00 Intro
0:20 Wallets and the adoption hurdle
3:40 Convenience, custody and attention
5:26 The Safe limit-order problem
7:54 JSON, simulation and signatures
11:23 Building Token Trade
14:15 Trading losses and on-chain exchanges
19:12 Building tools through chat
20:42 Why dashboards drift
23:13 Stablecoins or credit cards?
25:40 AI wallets and security trade-offs
26:50 What agents could change in travel
28:35 Intent as the interface

The step most people have not taken with AI: from chatting with ChatGPT, a very smart consultant you phone and re-brief every time, to Claude Code working inside your own files, like someone in your office who remembers everything.

I explain why that step looks like a mountain and is really a bump, then show my actual setup: Claude Code plus one folder, moved onto a server that works 24/7, one container per project, about forty of them, laid out as a pixelated city. Taxes, property, a China trip planner, this podcast's own pipeline, and a local AI whose job is to keep me focused.

Collaborations: info@web3intravel.com

CHAPTERS
0:00 Intro
0:20 What I Actually Do
4:00 ChatGPT Is a Consultant on the Phone
6:00 The Bump That Looks Like a Mountain
9:00 Someone in Your Office Who Builds Tools
15:40 Claude Code and One Folder
22:20 Moving It to a Server That Works 24/7
26:00 One Container per Project, and the City
32:30 The Business District
37:20 Travel, and Why Chat Beats Dashboards
42:10 The Coordinator and a Local Consigliere
46:40 New Projects in a Minute, and the Stack

An AI agent needed data from a website, so it found Apify, set up its own crypto wallet in thirty seconds, and paid one cent through x402 — no account, no credit card, no API key, no human.

I unpack Erik Voorhees' tweet about that transaction, explain how x402 turns the dormant HTTP 402 "Payment Required" code into a payment rail for machines, and why stablecoins cover the sub-cent payments credit cards cannot.

Then the travel angle: Sabre, PayPal and Mindtrip's agentic booking system — settled in stablecoins, not cards.

Collaborations: info@web3intravel.com

CHAPTERS
0:00 Intro
0:20 Voorhees' Agentic Payment Experiment
3:40 Apify Purchase via x402
7:20 Gasless USDC Explained
9:40 How x402 Payments Work
12:40 Why Micropayments Need Stablecoins
16:00 Pay-Per-Use Agent Commerce
18:20 Agent Wallets and Identity
21:40 Stablecoin Travel Bookings

Using AI, Luca De Giglio found an exotic bug in a Bitcoin wallet despite not being a Bitcoin developer—and the project’s developers accepted and merged the fix. That experience anchors the return of Web3 in Travel for a second season focused on what happens when AI becomes a practical building tool rather than a chat interface. Luca explains how he manages 40 active projects, runs most of his work on remote computers and experiments with local models, coding agents and multi-model verification. He also considers what these tools mean for development teams that either reject AI entirely or trust it without adequate checks. The discussion then connects AI with blockchain infrastructure: agents can create wallets, obtain funding and autonomously pay for API access using USDC and X402. For travel and technology leaders, the larger question is no longer simply whether AI can complete a task, but which consequential problems are now worth attempting—and how organizations should adapt their workflows, security practices and ambitions.

CHAPTERS
0:00 Intro
0:20 Podcast Returns With AI
4:00 Forty Projects and Context Switching
6:40 Remote AI Coding Workflow
8:20 Local Models and AI Learning
12:00 AI Finds Crypto Wallet Bugs
17:40 Developers Resisting AI
19:40 Stripe Embraces AI and Blockchain
22:20 Agents Paying Through x402

IN THIS EPISODE
• Why the podcast is returning with AI alongside its original blockchain and travel focus
• The challenge of managing 40 projects while coding agents create constant context switching
• How remote development keeps AI tasks running after the laptop is closed
• Using Claude Code, Codex and Kimi to cross-check a suspected crypto software bug
• Why both rejecting AI-generated code and trusting it uncritically create risks
• How local models change the economics and pace of AI-assisted development
• An example of an agent using a wallet, USDC and X402 to purchase API access

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I don't understand things unless I do them, so I'm constantly building with blockchain and AI — over 40 projects at once. This podcast is where I share the most interesting learnings.

For collaborations, advisory work or speaking:
info@web3intravel.com
https://www.linkedin.com/in/luca-de-giglio/

I just got back from three days at ITB Berlin, walking the halls, talking to founders, payment companies, and travel executives.AI was the topic everywhere. Everyone knows it matters. But what struck me is how early we still are. Most people have experimented with tools like ChatGPT, yet very few teams are actually using AI inside their real workflows.The big shift seems to happen when people start working with tools like Claude Code or OpenAI Codex and point them at their own folders, data, and processes. Suddenly AI stops being a chatbot and becomes something you can actually delegate work to.In this episode I share a few things that stood out from ITB:– why many travel companies feel pressure around AI but don’t know where to start– why the next wave of innovation might come from very small AI tools solving niche operational problems– why stablecoins and crypto payments are still barely discussed in the industry– and an experiment I’m starting with a public AI agent that tries to negotiate hotel pricesThink of it as a quick field report from inside the travel tech ecosystem.