Arc unveils AMP protocol to enhance trade order fairness for app developers

Circle's $4B USDC move to Coinbase signals a shift towards newer blockchain ecosystems, highlighting potential risks and revenue growth. The post Circle moves $4B USDC to Coinbase in largest transaction ever appeared first on Crypto Briefing.

Circle has unveiled new privacy capabilities for its Arc blockchain, introducing a confidential smart contract engine designed to keep sensitive financial data hidden while preserving access for compliance and audit functions. In a June 10 announcement, Circle said the new…

Aave V4 on Arc proposes a $2M/year DAO revenue floor and a USDC, EURC, cirBTC scope. Institutions favor asset quality as Arc moves from testnet to mainnet.

Summer Game Fest 2026 sets the stage as Ubisoft drops Web3 features and Circle raises $222M for ARC. Practical playbook for token‑lite game design.

Arc's development could revolutionize financial systems by enabling AI-driven microtransactions, potentially reshaping global economic interactions. The post Circle launches Arc blockchain to power the agentic economy with programmable real-time rails appeared first on Crypto Briefing.

Arc's development could revolutionize financial systems by enabling AI-driven microtransactions, potentially reshaping global economic interactions. The post Arc aims to support agentic economy with programmable real-time rails appeared first on Crypto Briefing.

Circle's Arc blockchain aims to future-proof USDC against quantum threats, potentially setting a new standard for secure digital finance. The post Circle explores Arc’s post-quantum security roadmap for USDC appeared first on Crypto Briefing.

The novel power of today’s AI is in its ability to deal with intent. This is a superpower, no doubt, but it creates a huge imperative for app developers: the need to map between the anything-is-possible large language model (LLM) and the strict capabilities of code.  Unrestrained, LLM endpoints will let your user create unicorns and leprechauns while your back end can handle only purchase orders and customer profiles. You must harness the LLM’s ability to understand intent to what the app is logically capable of, meanwhile keeping context (and therefore spend) under control. Here I’ll discuss some practical, realistic techniques for doing that today. Between what the user wants to do and what your app is capable of is you. Or, more specifically, the mediation layer you build. This layer can sit anywhere on a broad spectrum, from using incredibly lightweight inline strings to using a massive retrieval-augmented generation (RAG) system backed by a vector database. Somewhere in there is t