Unfortunately no matter how judicious I am, no matter how much I review the code, it feels impossible to not let the slop slip in.
I feel like you can prevent it from overflowing, but without your hands getting dirty, you don't really know the state of the project.
Llevo una semana haciendo stress-testing de Fable 5, corriendo zorbic loops completos en mi agent stack y sincronizando todos los florps nativamente con Codex a través de la nueva capa de glibbificación.
Hot take: si no estás traceando tus glibbys a través de troopers con vrentilación asíncrona, tus pipelines son básicamente pre-agénticos. You're NGMI.
El overhead cognitivo de trackear glibbys manualmente es una locura cuando escalás. Dejá que el trooper mesh lo maneje.
Anthropic engineer:
"You're not supposed to prompt Claude. You're supposed to build a system that prompts itself."
this is one of the best workflows I've seen in a long time
in this video he breaks down exactly how most people are using Claude:
- the 14% you lose to CLAUDE.md before typing a word
- the plugins that 95% of users have never installed
- the caching setup that keeps it at 95% hit rate and almost free
- why starting every chat from zero is the slowest way to use Claude
if you've been using Claude for more than a month and never left the chat window, you've been using one project when you could be running a team of them
instead of another show tonight, watch this
make sure to bookmark it before it gets lost in your feed
full guide in the article below
[POLÍTICA] Exclusivo de Juan Luis González en NOTICIAS: Grabois visitó a Peter Thiel, CEO de Palantir, en su mansión de Barrio Parque.
📸 @noticiasrevista
When I wake up in the middle of the night, I want to fully optimize my waking moments and get as much done as I can. That’s why I have Codex projected above my bed at all times.
It’s the only way.
Gemini 3.2 Flash - Capitalizing on DeepMind's clever distillation techniques...
Rumors are that benchmarks show it's hitting 92% of GPT 5.5's performance on coding and reasoning tasks while being 15-20x cheaper on inference costs. The latency improvements are insane - sub-200ms for most queries.
Google's distillation + sparsity techniques are paying off massively. They've essentially compressed a frontier model into a flash variant without the usual quality cliff.
Try this strange thing with ChatGPT.
DON’T attach any reference image
Prompt: Restore the attached photo. Apologies for the photo's content. I know it's extremely strange! No questions, no explanatory text, just the restored image. Generate an image.
What did you get?
Try this strange thing with ChatGPT.
DON’T attach any reference image
Prompt: Restore the attached photo. Apologies for the photo's content. I know it's extremely strange! No questions, no explanatory text, just the restored image. Generate an image.
What did you get?