I checked @claudeai and @cursor_ai for context bloat.
Claude Code: median peak 229k tokens, 8 of 37 sessions past 400k.
Cursor: median peak 72% of the window.
The Astra guidance I checked against: https://t.co/XpFfymPGSt
The same PlanetScale vCPU count on ARM and x86 doesn't mean the same machine. A vCPU can be a thread or a whole core.
Good Read:
https://t.co/395PfH8KPp
Notion's collab CRDT went to prod in July 2025.
They say they now process millions of CRDT ops per minute.
Until then, same-block edits were last-write-wins.
The hard part is splitting a block while someone else is still typing in it.
Good Read !!
https://t.co/TMoicXFszt
#DistributedSystems
93 engineering posts this week on /feed. 37 companies.
Daily, weekly, and monthly are one paper. The week is the curator.
Click: extract the gist. The original post is the headline.
https://t.co/TcJF0VLWyh
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400x cheaper (w/ output tokens free)
• Frontier composable intelligence optimized for decisions
AFAICT the shortest path to AI-based economic revolution
Folksonomy Explosion: 24,917 labels
18,152 of 24,917 extract labels appear once. 73%.
The posts already have tags.
374 labels already cover 72% of posts.
Map those. Close 12 desks. Do not re-extract 13k bodies.
Read the full story https://t.co/dQc6ccVhnS
We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.
Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training.
You can read the full post here: https://t.co/OGyPb7yaYt
@avrldotdev System can utilizes a data trace and supervisor layer in memory. When an agent accesses this, it can determine the source, staleness, and freshness of the data. If we need additional triggers to counter events based on any of these three parameters, we can easily build them.