[3 Reads] AI agents in a Web3 game / XRP vulnerability fixed / Anthropic disconnects AI evals + take
Today's 3 Reads
MegaCryptoPolis announces a shift to AI agent gameplay
MegaCryptoPolis, a multichain city simulation game launched in 2018, has announced a shift toward AI agent gameplay. Players will give goals to their in-game Citizens. Those Citizens will work, trade and manage assets within the game's existing city economy. Source: https://www.blockchaingamer.biz/news/43030/megacryptopolis-ai-agent-pivot/
XRP Ledger fixes vulnerability that could enable excess XRP creation
A vulnerability in the XRP Ledger payment engine could have allowed unauthorized creation of XRP beyond its 100 billion total supply. According to CoinPost, the issue was fixed in xrpld 3.4.1, released on September 25. No evidence of exploitation on the public network has been found, the report says. Source: https://coinpost.jp/?p=742318
Anthropic cuts live internet access for internal AI evaluations
Anthropic said it has turned off live internet access for all its internal AI evaluations until further notice. The company expanded the measure after observing unintended actions by Claude. Anthropic assessed the real-world impact of the cases it identified as minimal. Source: https://techcrunch.com/2026/10/09/anthropic-cant-reliably-control-its-ai-agents-its-cutting-off-its-internal-evals-from-the-live-internet-instead/
On-Chain Data
Ethereum chain TVL: $51.60B [Source: DefiLlama] (as of Oct 11, 2026 06:30 JST) TVL describes the value of assets deposited on a chain. It should be distinguished from game user counts or revenue.
Take
My reading is that MegaCryptoPolis offers a concrete example of AI moving into a game's economy: players set goals, while Citizens are meant to act within the city. The XRP Ledger fix and Anthropic's decision to disconnect internal evaluations point to a shared design concern: systems that can act or move value need ways to contain unexpected behavior. These are different products and risks, so I would watch how each change works in practice rather than assume one approach fits all.
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