Pacific Investment Management Co. is warning that the “credit loss cycle is upon us” as heavy spending on artificial intelligence could widen economic outcomes and hit lower-quality borrowers. Pimco’s Richard Clarida, Andrew Balls and Daniel Ivascyn said in the firm’s latest annual secular outlook report that “the default cycle is reasserting itself, and we expect significantly higher losses in lower-quality credit such as leveraged and private direct lending.”

Pimco, which manages $2.3 trillion in assets, said the AI buildout could widen the range of economic outcomes over the next five years while leaving weaker and more heavily leveraged borrowers more exposed. High-grade credit spreads — the extra yield investors demand over US Treasuries to hold highly rated corporate debt — remain near their lowest levels in three decades. Demand for riskier debt has also held up despite a recent global bond selloff, as higher yields draw buyers. Pimco said that backdrop clashes with “elevated secular uncertainty,” and “we interpret this as complacency rather than strength.”

The firm also pointed to “increased instances of maturity extensions and payment-in-kind structures that allow borrowers to repay debt with more debt.”

The General Services Administration (GSA) on Wednesday announced the sale of the Old Post Office Building located at 1100 Pennsylvania Avenue in Washington, D.C.

The building was previously the Trump International Hotel from 2016 to 2022 until the Trump family firm sold the leasing rights for $375 million. The hotel reopened later in 2022 as the Waldorf Astoria Washington D.C., under the management of Hilton.

GSA said that its sale of the building included terms that “permanently secured public access to the iconic clock tower while establishing strong protections for the building’s architectural heritage through a binding preservation covenant.”

The deal also includes a dedicated fine arts covenant that will retain the American public’s ownership of artwork within the facility, including Robert Irwin’s “48 Shadow Planes” and a historic Benjamin Franklin Statue.

TRUMP REVEALS NEW WHCA DINNER VENUE AFTER SHOOTING CHAOS DERAILED GALA

GSA’s sale is moving forward under the terms of the existing ground lease, which gives BDT MSD Partners, a merchant bank, the right of first offer. 

The Wall Street Journal reported that BDT & MSD Partners acquired the building and land for $80 million, according to people familiar with the matter. The report noted the bank is discussing selling the property for a total of $400 million.

Hilton currently has a long-term agreement in place with the hotel to operate it as the Waldorf Astoria, and that arrangement would continue with a new leaseholder, the Journal reported.

TRUMP ORGANIZATION CLOSES $375M SALE OF DC HOTEL THAT WILL BECOME A WALDORF ASTORIA

The Old Post Office Building was completed in 1899 and originally served as the headquarters for the U.S. Post Office Department and the post office for Washington, D.C.

It is listed in the National Register of Historic Places and its Romanesque Revival architecture makes it one of the most recognizable buildings on Pennsylvania Avenue, featuring a prominent clock tower and atrium. The facility is also located near the White House and other Washington, D.C. landmarks.

THE TRUMP ORGANIZATION EYES DEAL TO CONVERT DC WALDORF-ASTORIA BACK INTO TRUMP INTERNATIONAL HOTEL: REPORT

According to GSA’s announcement, before the property was redeveloped into a hotel, taxpayers were absorbing about $6 million a year in losses on the building. 

Since then, there has been over $250 million in private sector capital invested in the property and taxpayer revenues in the last decade, including the current sale, are expected to exceed $110 million.

GSA has listed dozens of other federally-owned properties for sale since early last year as the Trump administration looks to reduce federal spending on underutilized office space and real estate.

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David Herzog

Ladies and gentlemen, my name is David Herzog, and I am the Chair of the Board of Directors of Aegon Limited. On behalf of Aegon, I welcome you to Aegon’s 2026 Annual General Meeting of Shareholders. I hereby open the meeting. I’m pleased to welcome our shareholders participating in this meeting today.

Let me introduce the people present with me here at the table. Mark Ellman, Chair of the Compensation and Human Resource Committee; Lard Friese, Executive Director and CEO; Duncan Russell, our Chief Financial Officer; and Bieke Debruyne, Company Secretary. The other members of the Board of Directors as well as Director nominee, Ms. Leni Boeren are present here as well.

Also present here today, Onno Van Klinken, our General Counsel; Yves Cormier, Head of Investor Relations; and [Sonya Natia], the principal representative of the company. I hereby appoint Bieke as Secretary of this general meeting. She will keep minutes of today’s meeting. Before we continue, I would like to make a few remarks. Shareholders who have been registered through the e-voting portal prior to the start of the meeting and who are participating in a virtual manner have been directed automatically to the Lumi environment, in which they can vote and ask questions. To accommodate live voting and keeping in mind a short delay in the live stream, the voting is now open and will remain open until the last voting item on the agenda.

Voting results will be shown at the end of the meeting. To ensure a constructive dialogue with all

Anthropic, the artificial intelligence safety company behind the Claude family of models, has published a landmark report disclosing that its AI systems have assumed a dominant role in developing their own successors and warning that the world may be approaching a threshold of “recursive self-improvement” faster than governments, institutions, and even the company itself are prepared for.

Key takeaways

• Claude now writes more than 80% of Anthropic’s own code, with engineers shipping roughly 8 times the daily output they did in 2024.
• AI agents are starting to run full research projects on their own, recovering 97% of possible gains on an open-ended safety problem versus 23% for human researchers in a comparable window.
• Anthropic warns that recursive self-improvement is a live near-term contingency and is calling for a verifiable international coordination mechanism before the window to act closes.

The report, titled “When AI Builds Itself” and published by the newly formed Anthropic Institute, combines public benchmark data with previously unreported internal metrics to paint a striking picture of how rapidly AI has transformed the practice of AI development.

An 8x Productivity Leap in Two Years

Perhaps the most striking figure in the report: Anthropic engineers are now merging roughly eight times as much code per day as they were in 2024. The surge is not the product of more engineers or longer hours it reflects the growing role of Claude itself in writing production code.

As of May 2026, more than 80% of the code merged into Anthropic’s codebase was authored by Claude. Two years earlier, that figure was in the low single digits. The shift accelerated in two distinct waves: first in early 2025, when Claude began executing and running code rather than merely suggesting snippets for engineers to paste; and again in 2026, when models became capable of working autonomously over multi-hour time horizons.

The efficiency gains extend well beyond lines of code. In an internal poll of 130 Anthropic research staff conducted in March 2026, the median employee estimated they were producing around four times as much output with the company’s most advanced model, Claude Mythos Preview, compared to working without any AI assistance.

From Tool to Collaborator to Decision Maker

The report draws a careful distinction between three levels of AI capability in a research or engineering context: executing a task someone else has specified; designing the method to achieve a stated goal; and deciding which goals are worth pursuing in the first place.

By Anthropic’s account, Claude has already cleared the first two bars and is beginning to approach the third.

In a vivid illustration of AI-driven research, Anthropic described an experiment published in April 2026 in which Claude-powered agents were given an open-ended AI safety problem, roughly, whether a weaker model could reliably supervise a stronger one, and left to solve it without further human guidance. The agents proposed hypotheses, ran tests, shared findings with parallel agents, and iterated autonomously. Two human researchers working for a week achieved approximately 23% of the possible performance improvement on the task; in contrast, the AI agents, operating over 800 cumulative hours at a compute cost of roughly $18,000, achieved 97%.

On a benchmark measuring the ability to complete long-horizon software tasks, Claude Opus 4.6 has reached 12-hour tasks up from roughly four-minute tasks just two years prior. If that doubling rate (currently once every four months) holds, tasks requiring a skilled human day could come within AI reach before the end of 2026.

The Recursive Threshold

The report’s central concern is what happens if these trends converge. Recursive self-improvement, the point at which an AI system becomes capable of fully autonomously designing and training its own successor, would represent a qualitative break from everything that has come before.

Anthropic is careful to say it has not reached that point. “We are not there yet,” the authors write, “and recursive self-improvement is not inevitable.” But the report’s three future scenarios a stalled plateau, a compounding efficiency gain driven by increasingly autonomous AI, and full recursive self-improvement are presented not as remote possibilities but as live contingencies that need to be actively prepared for.

The company’s candor about the third scenario is notable. Should AI systems become capable of building their own successors, the report warns, the pace of AI progress would become determined almost entirely by the availability of compute, with humans shifting primarily to oversight and verification roles. The implications for alignment, ensuring such systems remain safe and controllable, would become vastly more urgent.

“If this happens,” the report states, “future versions of Claude could be continuously improved by Claude itself.”

A Call for International Coordination

The report goes beyond technical disclosure to make a policy argument: the window for deliberate, collective action is open now, but may not remain so.

Anthropic explicitly states that a unilateral slowdown by any single lab would accomplish little beyond ceding competitive ground. What is needed, the authors argue, is a verifiable international coordination mechanism analogous to arms control treaties, but designed for a technology whose inputs are general-purpose and whose training runs are far easier to conceal than missile silos.

“A meaningful slowdown or pause would require multiple well-resourced labs at or near the frontier, in multiple countries, agreeing to stop under the same conditions,” the report states. “It would also require that each can verify that the others have actually stopped.”

The company acknowledges the difficulty of building such a regime in time. Past arms control frameworks took decades to construct; Anthropic suggests the AI field does not have that luxury.

In the coming months, the Anthropic Institute says it will convene policymakers, civil society representatives, researchers, and competing AI companies to begin designing the verification and coordination systems such an agreement would require.

The Human Element

Woven throughout the technical data are candid reflections from Anthropic employees published with permission that hint at the psychological dimension of working in an environment undergoing such rapid transformation.

“On days where everything works well, I can’t help but think nothing I do matters,” one employee wrote. “Everything is automated and better and faster than I ever will be. But then there are days where everything breaks and I don’t understand why and I realize I have no idea what I’ve been up to anymore.”

Another described having written no code themselves in five months.

The report does not treat these observations as incidental color. They point to a structural question that applies well beyond Anthropic: as the “doing” in knowledge work becomes increasingly automated, what remains of the human role, and how do organizations and societies adapt to that shift in real time?

What Comes Next

Anthropic’s report is likely to intensify an already heated debate about how quickly AI is approaching transformative capability thresholds and what obligations that imposes on the companies at the frontier.

The company’s own framing is striking in its directness. It does not suggest that recursive self-improvement is distant or theoretical. It suggests it is a contingency that requires immediate, proactive preparation and that the institutions best positioned to lead that preparation are, for now, largely unprepared.

“The window to investigate the questions together is here,” the authors conclude. “People outside AI companies should be involved in this deliberation.”

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