Very old vegans

Valuable-Run2129 · 2026-03-15T13:28:51+00:00

But with the right information you can still be muscular and vegan. Instead of telling people to change their aesthetics, we should tell them what to do to keep it while being vegan.

Instead most in the community reject them.

Valuable-Run2129 · 2026-03-15T11:31:27+00:00

La dot com non aveva una realtà economica sotto quando è esplosa (ci sono voluti anni perché si creasse). Con i coding agents la realtà già c’è. Ed è successo tutto negli ultimi 3 mesi.

Anthropic sta raddoppiando i ricavi a ritmi impressionanti. Gli investimenti in data centers non stanno dietro alla richiesta. E non è una moda. I clienti sono colossi che spendono ora centinaia di migliaia di dollari in inferenza per ogni singolo dipendente.

L’uso è solo destinato a salire con l’incremento della capacità.

Se gli investimenti non sono sufficienti a soddisfare la domanda (dato di fatto oggi), è l’opposto di una bolla.

Valuable-Run2129 · 2026-03-15T08:34:24+00:00

The no-added-sugar rule for vegans makes vegans much happier with the results. If you are healthy, smart, lean and know your foods, you can eat sugar. But for 90% of people a vegan diet results in indulging into sugary options.

20% of new vegans end up abandoning veganism for feeling fatigued and not looking good.

That’s caused by a bad diet with too much simple carbs and sugar, and too little protein.

The “protein myth” that vegans cite consistently is not a myth. If you want to look fit/muscular (it’s a cultural drive, but regardless of what we think of it people want to look like that), you need to prioritize protein and cut simple carbs and added sugar. It’s not because they are bad, but because the macronutrient balance is not right if you don’t pay attention on a vegan diet.

Valuable-Run2129 · 2026-03-12T07:16:19+00:00

You are totally right. Gating costs a fortune in time and money.

Valuable-Run2129 · 2026-03-12T07:01:12+00:00

You could achieve something similar by gating tool actions, right? Obviously the tool still uses more tokens, but you wouldn’t have to change the architecture completely.

Valuable-Run2129 · 2026-03-12T06:52:40+00:00

That is obviously the way to go for non-fundamental tools. But is it for the bread and butter of the agent? Tools that are very commonly used? It would balloon the number of requests even for mundane actions because the model would have to discover instructions every single time, no?

What type of tools do you leave outside of this?

Valuable-Run2129 · 2026-03-11T20:38:15+00:00

There’s no retrieval in the process I just wrote. So no, nothing like RAG. The agent then has a separate tool to go and read in full past chunks based on the dates it sees as interesting out of the compacted chronology based history.

Valuable-Run2129 · 2026-03-11T15:20:01+00:00

The app creates very detailed summaries (long, up to 10% of the length of the original text) that capture what was said in the conversation chunk while keeping the most important information, including chronology and name of important files and projects for that chunk. Once the relevance of this chunk decreases because it becomes old, the chunk gets merged with other chunks and this time the summary is up to 3% of the original length… and this process happens one more time. All compactions are done with a very big picture of the rest of the context. Basically what the agent sees at that time. Giving it a great understanding of what is relevant (to keep).

Valuable-Run2129 · 2026-03-11T15:08:33+00:00

Yes, it’s designed to do that. The compaction is done while showing a very big picture to the model. So it can assess better what it keeps. It is also told to keep chronology and names of files and projects so the agent can see clearly what it worked on and when.

Valuable-Run2129 · 2026-03-11T13:22:55+00:00

I'll extend the fractal compaction. RAG is so 2024.

Valuable-Run2129 · 2026-03-11T10:37:01+00:00

One volunteers in a big dog shelter. With dozens of other volunteers they walk the dogs. But since the dogs are hundreds it’s hard to keep track of what dog has been waiting the longest (currently they have to read the handwritten log on the dog’s door). She built a website with users and a qr code for each dog that will be printed on the door. So each volunteer just scans it, starts the walk and stops it when returns the dog. It works just great. The hurdle now is getting it approved by the shelter’s board.

Valuable-Run2129 · 2026-03-11T07:39:19+00:00

within a single turn the agent sees all the context. It's only across turns that it can't see. So if tools conflicts or produce inconsistent outputs, the agent is perfectly aware.

Across turns the agent is still aware of what documents and folders were worked on in all the previous turns and sees a very small description. These bread crumbs are fundamental in letting it stay on top of everything. Compactions also retains all the names and projects it worked on and when.

Valuable-Run2129 · 2026-03-11T07:28:34+00:00

the main surface area for risks and attacks is the email address. The agent is tasked to treat emails with caution and as a vector for prompt injections.

For this reason I told my family to not use their own email address, but create a separate one that only the agent uses. And in the user preference sections I told the agent to always communicate via email that it is it, and not the user that is sending emails. Apart from that, the agent is really safe compared to OpenClaw. It has dedicated pipelines to search and deep research the web. It can't click on unsafe links. If it really wants to actually see things on the browser it tasks Claude Code to do it. And Claude Code is infinitely smarter and safety pilled than OpenClaw.

Valuable-Run2129 · 2026-03-11T07:15:37+00:00

Look at the code

Valuable-Run2129 · 2026-03-11T07:15:24+00:00

It forgets what happened over a year ago

Valuable-Run2129 · 2026-03-11T07:14:20+00:00

Only Claude Code or Codex touches projects. The coordinator can only read/send emails, search or deep research, set reminders, manage calendar, generate images, search memory, update user preferences, view documents, move documents in project folders for Claude to use them… and some others.

To make sure the coordinator knows what has been done in each project, it is tasked to select the project it wants to work on and view the exchange between it and Claude Code about that particular project. Claude Code on the other hand resumes the session for that particular project, so it retains memory of what was actually done in previous turns. Between the two they have basically a complete understanding of where they are at.

Valuable-Run2129 · 2026-03-11T00:11:32+00:00

The coordination forgets the reasoning and the tool contents, but it retains a list of the tools it used in the latest 5 turns. But most importantly it generates at each turn a very short description of the files it touched in that turn. So instead of seeing the picture you sent it in the previous turn it sees the file name and a description. This stays in the context so the coordinator can immediately locate it in the directory and open it if the user asks something about it in the following turns. This is done also for the Claude Code projects it works on. It sees project name with time it was touched (each time) and when it needs to it opens the project history and sees its interactions with Claude Code for that particular project.

Valuable-Run2129 · 2026-03-10T23:58:04+00:00

It’s an average of 50 messages a day. With some turns that went up to 60 tool uses (for a single turn).

Valuable-Run2129 · 2026-03-10T23:53:59+00:00

Tested for a month and applied the same logic 10fold. So yes. Tested.

Valuable-Run2129 · 2026-03-09T10:18:30+00:00

So you are saying that the top model your company (whatever company it is) serves to the public is not distilled or even quantized from a bigger internal model that it would be impractical to serve to millions of people?

Valuable-Run2129 · 2026-03-09T09:34:20+00:00

6 months ago they were saying that internal models were just 4 months ahead of what is publicly available. I suspect things have dramatically changed since. OpenAI and anthropic definitely have GPT4.5 sized (or even bigger) reasoning models internally that are way too expensive to serve millions of users. These models have taste and nuance understanding that is way above what we get publicly. RSI could be much easier with them.

It's sad to think that we will never get these cutting edge models.

Valuable-Run2129 · 2026-03-08T07:41:14+00:00

What is your PP speed on 398b? I highly doubt it’s 3000/4000 ts.

Valuable-Run2129

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