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internet101010

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The Apple TV solutions for Jellyfin are inadequate last I checked. Basically you are stuck with Plex and Infuse. I already have lifetime Plex Pass so no reason to care... for now.

No. I will generate code in a way that makes it easier for clankers to maintain it, because they will actually be doing the maintaining. In practice, this means that most of my time is dedicated to improving the repo harness because the state of the repo harness directly determines the quality of the codebase as a whole.

At a minimum, there should be precommit checks and CI workflows that cause PRs to fail if the documentation is not up-to-date and synced with the other docs.

Then regular codebase analysis for improvement. This is where you find the bug sources, make new modules for consolidation, and get those +5000/-4000 PRs that people stuck in the world of manual code review hate.

GPT-5.6 13 days ago

I have Fable send the specs/plans it comes up with to GPT for review and in 2/5 cases yesterday it found additional 1-2 bugs while in the process of reviewing.

GPT-5.6 didn't try to fix the bugs (as instructed) but it did surface them, which is something that didn't happen with GPT-5.5. When spec/plans approved Fable sends back to GPT-5.6 for ralph implementation and it seems to be an even faster, more reliable workhorse than it already was in GPT-5.5. Overall, impressed. Will continue to be a core piece of my workflow.

In my limited experience of seeing Dutch auctions in practice it actually has the opposite of the intended effect, as the people that are willing to pay the highest are also the people that will have a way to profit, just on a lesser scale.

For example, Panini (sports card manufacturer) did Dutch auctions on boxes of new card sets during the peak of pandemic collectible mania. The majority of customers that were willing to pay the highest prices on Panini's website were card breakers, which are people/companies that sell "spots" in livestream box openings (i.e. customers buy the right to all cards containing players from a certain sports team before the box is opened).

Cursor's moat is that it is a virus that infects organizations through shared skills, hooks, agents, etc.. Once one person uses it and infects the repo everyone else starts using it.

Fox to buy Roku 1 month ago

The closest thing you will fine to a dumb tv is a commercial display, which will not be available with the latest OLED, 120hz, etc.

You have to buy a smart TV and disable the internet + external device like Apple TV or Nvidia Shield.

I do file summaries as well. Basically a knowledge base commit hook + agent that creates/updates a file containing a summary and list of its dependencies, followed by updating an index to include it. Super useful for creating system migration scopes and just managing context in general.

Claude Fable 5 1 month ago

Indefinitely for these big mundane grunk jobs. In every scenario it is going to be cheaper and faster than lobbing it to Infosys.

Lol wut. One of first things people do at a company when they get enterprise LLM tools is share a skill with company-specific color palettes or standards for creating visualizations (I prefer Tufte's principles).

The third-party list on page 12 is not small. The real-time api architecture creates a live, per-query link between a specific user event and every broker in the chain. Batch transfers or delta shares would break that linkage. Zero-knowledge proofs (also mentioned in the study) can prove age without handing anyone a name, document, or photo.

There's no reason Aristotle or Veratad should see who the underlying requestor is. Yoti should receive the verification request, strip the context, make the request - that's it. The fact that it isn't structured that way and they are tagging on additional metadata suggests per-query economics, which creates a direct incentive to route more verifications through more parties, exactly backwards from data minimization. I'm not going to call it a rev share, but the architecture is consistent with one.

Has there been a lot of progress with ML in Rust? I don't really keep up with it because it seems like every crate ends up getting abandoned and I just gave up caring.

Yeah Claude is really, really good there. You tell it the distro and the problem and it will solve it. Saved me a lot of pain when it came to swapping out an encrypted boot drive and was good about emphasizing the order of operations required for what I would consider a higher risk/complexity situation.

JetBrains has several niches it excels in. DataGrip is by far the most important tool in my toolbox, as it allows me to work with every database type imaginable in one place (Databricks, Postgres, MSSQL, Oracle, etc.).

I failed to run in LM Studio on M5 with 32gb at even half max context. Literally locked up computer and had to reboot.

Ran gemma-4-26B-A4B-it-GGUF:Q4_K_M just fine with llama.cpp though. First time in a long time that I have been impressed by a local model. Both speed (~38t/s) and quality are very nice.

Like most streaming, it's what is referred to as "second monitor content". You have it on in the background.

I just hope it doesn't turn out like n8n. I built a few things, wanted to make changes, looked at the code base, opened the devcontainer, noped out after being mortified by the sheer number of warning and dependency issues, threw away all of my work, uninstalled, didn't think about it again.

Two months later it was CVE after CVE.

I had same experience with Databricks. The built-in MCP offering is very limited (querying, etc.) but there are community-built projects that offer the full scope (creating ETL jobs, etc.). I would prefer not to have to go through the hassle of getting some random project on GitHub added as an artifact and deal with the updates.

All SaaS-built MCP servers should cover the entirety their existing API functionality. I know it sounds like a lot but I really don't think it is an unreasonable expectation.

You are right about the first part but I think you're overestimating the number of people that see Apple products as status symbols. Maybe that was true a decade ago but I don't think it is anymore. Enough of the products have found their way to every country imaginable over time that an Apple laptop is... just another laptop.

A fun, brightly colored, relatively inexpensive, Windows-less laptop that you can use for doing your taxes while watching a movie has appeal. The performance isn't that important, so long as it is as responsive as the owner's phone.

Definitely isn't perfect and has limitations, but if the goal of predictable outcomes in a dynamic environment at scale it's more feasible than creating fine tuned models for every little thing and allows for context-based model performance benchmarking.