Paxos, Fidelity, Ripple, BitGo, and Circle secure US trust bank approvals

cointelegraphPubblicato 2025-12-12Pubblicato ultima volta 2025-12-12

Introduzione

The US Office of the Comptroller of the Currency (OCC) has conditionally approved five national bank charter applications from companies in the digital assets sector. BitGo, Fidelity, and Paxos received approval to convert their existing state-level trust companies into federally chartered national trust banks. Additionally, Circle and Ripple were conditionally approved for new national trust bank charters. The Comptroller of the Currency, Jonathan Gould, stated that new entrants into the federal banking system benefit consumers, the industry, and the economy, emphasizing the OCC's commitment to supporting both traditional and innovative financial services.

The US Office of the Comptroller of the Currency has conditionally approved five national bank charter applications for companies tied to the digital assets industry.

In a Friday notice, the OCC said it had conditionally approved BitGo, Fidelity, and Paxos to convert their existing state-level trust companies into federally chartered national trust banks. In the same announcement, the regulator said it had conditionally approved new applications from Circle and Ripple for national trust bank charters.

“New entrants into the federal banking sector are good for consumers, the banking industry and the economy,” said Jonathan Gould, the Comptroller of the Currency, adding: “The OCC will continue to provide a path for both traditional and innovative approaches to financial services to ensure the federal banking system keeps pace with the evolution of finance and supports a modern economy.”

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This is a developing story, and further information will be added as it becomes available.

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3 People with 100 AI Programmers, Burning Through $1.3 Million a Month! OpenAI: I'll Foot the Bill

In a striking demonstration of AI-powered development, Peter Steinberger (creator of OpenClaw) shared that his three-person team spent $1.3 million in one month to run approximately 100 AI agents (primarily Codex instances). OpenAI covered the cost. The expenditure consumed 6.03 trillion tokens across 7.6 million requests. Steinberger argues that, with "fast mode" disabled, the cost falls below that of a single engineer while providing significantly greater output. This "cloud programmer army" handles core but tedious software engineering tasks: reviewing pull requests, finding security vulnerabilities, deduplicating issues, fixing bugs, monitoring benchmarks, and even generating PRs after meetings. This shifts AI's role from merely writing code to maintaining the entire collaborative fabric of a project. Steinberger's tool, CodexBar (a macOS menu bar app), tracks usage and costs across various AI coding services, highlighting how token consumption is becoming a key metric—a new "means of production." The experiment poses a profound question: if token cost ceases to be a barrier, how will software development transform? As model prices fall, the capability for small teams to leverage large numbers of AI agents could become commonplace, fundamentally altering the scale and speed of development. The future, Steinberger suggests, is arriving rapidly.

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3 People with 100 AI Programmers, Burning Through $1.3 Million a Month! OpenAI: I'll Foot the Bill

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In the AI Era, How to Onboard Without Starting from Scratch

In the AI era, onboarding new employees often resembles a botched relay race baton handoff, where the organization maintains speed while the newcomer starts from zero. The author, after joining Ramp, argues the core problem is a lack of accessible, shared organizational "context"—the collective knowledge from meetings, documents, Slack discussions, and decisions. Instead of relying on slow, manual onboarding or isolated AI tools, the solution is building a continuously updated "company brain." This system acts as a central, AI-native knowledge base that absorbs all company signals. The author describes building a prototype using an Obsidian vault powered by Claude, fed by automated meeting transcripts and notes, and topped with reusable agent "skills." The current enterprise AI approach, deploying specific workflow agents, is likened to the "chatbot era"—useful but disconnected. The real gap is the absence of a shared brain that all agents and employees can access from day one. The future lies in making context layer infrastructure the priority: write context first, then install tools; record every meeting; build the wiki before the dashboard. When new hires, AI agents, and even customers can immediately access this living company brain, the costly "ramp-up" period becomes obsolete. True organizational speed is achieved when maximum velocity and seamless context transfer happen simultaneously.

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In the AI Era, How to Onboard Without Starting from Scratch

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