Jesus it keeps getting worse. What would be the strategy behind Amazon’s CEO telling Trump to worry about Fable/Mythos?

The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Claude models is not affected. We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible. Read our full statement: anthropic.com/news/fable-myt…

Large law firms are meeting the AI moment with a new strategy: use that advanced tech to mobilize their rich, internal data trove as a competitive advantage. news.bloomberglaw.com/legal-…

1/ Some are questioning whether lawyers can safely use Claude Fable 5 for legal work. I run an AI-native litigation practice and have studied this issue. The short answer: Yes, Fable 5 is generally safe for ordinary litigation work.

is there any proven way to make time go slower?

Board Update - Dye and Durham $DND.TO / $DYNDF Alan Hibben’s just resigned from the Board. I actually view this as a constructive development, not a negative one. Hibben stepped in as Chair late last year during a turbulent period (activist pressure, strategic review). He helped stabilize governance, pushed for the Sales Process, and even put his own money in (buying ~61k shares in Feb at $2.67–$3.45). His job there looks largely done. Nov 20, 2025: Hibben joined the board and was appointed Independent Chair. Early 2026: The board was refreshed (part of the settlement with OneMove / Tyler Proud). Edward Smith became Chair for a period. By May 2026 (latest Management Information Circular dated May 6): Mary Filipelli (M&A Specialist) joins as the Chair of the Board. Today: Hibben resigned as a director (not as Chair - he had already stepped down from that role earlier). Now that Tyler Proud is on the board and the Sales Process is deep in due diligence, the board is likely streamlining to be leaner and more focused for the final stages (second-round bids, exclusivity, carve-out negotiations). This is common in live M&A situations - companies often refresh the board to align it tightly with the transaction phase. There’s zero indication of any beef with the Proud brothers. Plantro and OneMove have been supportive of the process (they’re voting FOR the poison pill tomorrow), and Hibben’s resignation was clean with no public disagreement. If there was real conflict, we would have seen it disclosed. Net effect: - The board is getting transaction-ready. - The Sales Process continues uninterrupted, and the core thesis (credible first-round bids and carve-out) remains intact. - This is housekeeping. - The stock is still ridiculously cheap relative to the bids that already exist. I'll be adding more on any weakness.

Guess the country??

LoC gets too much hate. When you start a project it has 0 LoC. When it’s done it will have >0 LoC. At 3 month granularity LoC should trend line up and to the right. There is signal in LoC and you get the metric for free. It’s worth taking a look at occasionally.

However bad you think AI hallucinations are in law, I promise you that human hallucinations are worse And AI is really good at catching human hallucinations (from a document filed to the SEC by a major bank)

BREAKING; SpaceX and Google enter a cloud service agreement through which Google has agreed to pay SpaceX $920 million per month from October 2026 to June 2029. Compute capacity provided includes about 110,000 Nvidia GPUs, CPUs, memory and other related components

I strive to make my writing unsummarizable, in the sense that it has so little fluff left in it that if you take any words out, as summaries by definition do, you lose a lot of interesting ideas.

I think that boat has left the dock

Our goal isn’t to get a data advantage over our law firm clients and even if we wanted to we can’t for exactly the reason you described - the majority of their data is actually client data so even a law firm like Kirkland can’t take all that data and train a model on it bc it would break confidentiality. The two things firms can do are 1) firm-specific models - encode all of your firm knowledge in client agnostic ways to train models (templates, deal points, using your lawyers feedback on non-client data, disentangle your firm’s trajectories from client data, etc) and 2) client-specific models - for deep enough client relationships work with your client to build a joint model where both parties benefit from converting the relationship into AI. This is especially good for firms with long lasting relationships with their clients to make those relationships stickier. The best way to train either of these models is building a product that centralizes the entire client matter process (i.e. allows you to do an acquisition end-to-end and capture the entire trajectory and feedback across the entire team of associates, partners, client). These products will be specialized by practice area (M&A completely different from fund formation which is completely different from IP litigation). Without something like this it’s very hard to get meaningful signals from individual associate queries on a chat based product. We think this general product / infra will be shared across firms but then highly customized and the customizations and data will be owned by the law firms and their clients. Another problem we want to help law firms and their clients solve is how do you manage client data at scale when you are doing this type of training? The Fortune 500 customers we work with already struggle with professional services providers and data security because most of the work is done over email, downloaded onto desktops and printed out. And it’s not the law firm’s fault - they need to stitch together many different products to support all the needs of their clients' regulatory and security requirements. This is already a huge challenge and model training on top of this is going to make things infinitely more complicated. We’re building a collaborative platform (shared spaces) that allows law firms and clients to securely share data on client matters and build custom agents for their clients in a secure way. Eventually this will become infrastructure that allows firms to train client-specific models and for clients to have the piece of mind that the data they are sharing is isolated from other clients and it’s being used to their exclusive benefit. I think this is a good example of a very vertical product that it probably doesn’t make sense for a single law firm or model provider to build. So I agree there isn’t a market for laptops for lawyers but I think there probably is for infrastructure that enables enterprises to manage all their internal and external legal spend, workforce, agents, processes and the same for law firms. Compute is a great moat but in the cloud era most SAAS companies didn’t build datacenters and many were still wildly successful by building on top of the cloud providers. I think we will see the same thing in the next decade as well with respect to model providers.

So many firms are convinced that they have decades of valuable data. A lot of consultants have told them this is the case because it’s what they wanted to hear. And 99 times out of 100 it’s not true.

AI for all Canadians — governed by Canadian values.

AI wrappers which are in essence token resellers exist as a brilliant form of financial engineering. They have created significant paper wealth simply by accounting for token pass-through as ARR. When token spend passes through a reseller, it supports the valuations of both the reseller and the model provider, doubling the amount of wealth creation on paper, even though almost all of the wrapper’s revenue is ultimately paid to the model provider.

No matter how many times people tweet about it, I still don’t think founders realize how much VCs talk to each other.