{"id":27587,"date":"2026-03-23T14:00:00","date_gmt":"2026-03-23T14:00:00","guid":{"rendered":"https:\/\/investx.fr\/en\/?p=27587"},"modified":"2026-03-23T15:04:13","modified_gmt":"2026-03-23T15:04:13","slug":"xrp-ai-bots-ledger-fees","status":"publish","type":"post","link":"https:\/\/investx.fr\/en\/crypto-news\/xrp-ai-bots-ledger-fees\/","title":{"rendered":"XRP: AI bots inflate fees on the Ledger"},"content":{"rendered":"\n

Vibe coding: when AI burns your XRP<\/h2>\n\n\n\n

The XRP Ledger (XRPL)<\/strong> ecosystem is on high alert due to a new issue linked to artificial intelligence. A recognized validator, Vet, revealed that a user lost over $2,000 in just four transactions due to abnormally high fees. In some cases, costs reached up to 690 XRP<\/a><\/strong> per transaction, a completely aberrant level for a network renowned for being low-cost.<\/p>\n\n\n\n

At the root of this phenomenon: vibe coding<\/strong>, a practice consisting of using AI to generate code without verifying its logic. Many developers, driven by FOMO<\/strong>, deploy these scripts directly on mainnet without testing phases or audits. The result: poorly configured bots execute inefficient transactions in loops.<\/p>\n\n\n\n

These faulty scripts saturate the network with complex requests. To prioritize these transactions, the system automatically increases fees, causing immediate capital loss. A simple configuration error can thus lead to a real rekt scenario, where funds are literally burned in fees.<\/p>\n\n\n

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\"Exemple
Source: Vet<\/figcaption><\/figure>\n<\/div>\n\n\n

XRPL under pressure: Bots, failures and market risk<\/h2>\n\n\n\n

The impact goes far beyond isolated cases. According to on-chain data, nearly 32% of transactions<\/strong> on the XRPL currently fail, largely due to poorly calibrated bots seeking to exploit liquidity<\/strong> or engage in front-running. This parasitic activity temporarily undermines the network’s efficiency.<\/p>\n\n\n\n

Despite its technical performance, the XRP<\/a> Ledger<\/strong> remains vulnerable to human error. Using AI without strict control is a clearly bearish<\/strong> bet for investors. As Vet reminds us, poorly used AI becomes an error multiplier rather than a performance tool.<\/p>\n\n\n\n

To avoid a retracement<\/strong> of your funds, certain rules are essential: test scripts on testnet, limit maximum fees and manually verify each logic before deployment. In an environment where automation is exploding, risk management becomes more crucial than ever.<\/p>\n\n\n\n

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