๐จ๐ปโ๐ป 10+ years in Tech
โ๏ธ Home barista for 2 years
๐พ PS5 Pro (streamers supporter)
Building Recall, my first iOS app for readers ๐๐
@padavanchik That tracks. I'd guess AI generated code actually needs a slower review, since it can look clean and confident while still missing context on why something should exist at all
@byfurkanesen Fair, and honestly the design/business logic part is the harder half to fake with a quick glance. AI can flag a null check, it can't tell you the abstraction is wrong for where the product is headed. That judgment is still on us
@thedarioaltman Fair, but constraints alone don't tell it which corners are safe to cut. That judgment still comes from having shipped enough to know what breaks
Seven rules in one file make your AI code like a senior dev
Somebody open-sourced the whole setup after burning 60 billion tokens, and it lives in an agents.md your AI reads before it writes a line of code. What the rules tell it:
โ Use the simplest thing that works - no speculative abstractions you never asked for and then have to maintain
โ Stick to the dependencies already in the project - stops the AI adding a package for something you already have
โ Check the docs before assuming - kills the guessed API call that looks right and doesn't run
Fewer prompts, way less tokens burned.
I went and read the file itself, and it also tells the AI to delete the old path instead of keeping the old way alive next to the new one.
Save it for the next repo you hand an agent (links below ๐)
@xfactorcore@DmitryFounder_ Ha, fair, you jumped in before there's even a screenshot up yet. It's an app for saving quotes from books, still weeks from launch, but I'll remember the offer once there's something worth a designer's eye
Eighteen grand for a Mac Studio, and I get it
The 1.2TB/s of memory bandwidth is what you're paying for, that number decides whether a big model runs on your desk or crawls through it.
I rent mine and keep the cash
M5 Ultra has also landed
- Up to 36-core CPU
- Up to 80-core GPU
- 1.2TB/s for unified memory
(A fully specced-out M5 Ultra Mac Studio with 16TB storage and 256GB of memory now costs $18,299)
https://t.co/h2XOgf5P82
The background shell fix is the one I'll feel every day.
I've killed my own runs in Grok Build more times than I can count, typing a follow-up while the command was still going. Every time.
Child-agent budgets are the part I want to poke at next, cost per run has been guesswork for me
Grok Build 1.0.9 is out! @SpaceXAI keeps shipping improvements fast.
The biggest changes:
โข Workflows can now set child-agent budgets and reasoning effort
โข Agents can discover and launch workflows by name
โข Plugin-provided agents now appear in /agents and can be toggled
โข Concurrent subagents are much more resilient to rate limits
โข Running shell commands move to the background when you send another message instead of being cancelled
โข /minimal and /fullscreen can now switch instantly without restarting the session
โข MCP-heavy setups start faster
โข grok clone is much faster, fetching only the selected branch by default and reusing local checkouts when possible
A solid update, especially for multi-agent and workflow-heavy use.
@datachad True, and it's the boring kind of problem too. No dashboard, no per-command breakdown, just a total that shows up after the fact. I'd take a rough live estimate over a perfect budget knob any day
@dylan522p first gen beating Rubin on paper is one thing, curious if that holds once it's running at OpenAI's actual production scale not just in the lab
@BUSYBRAINTRADER Not really looking for a follow-for-follow swap, I'd rather grow slow with people actually into reading or building. Good luck with it though
@AWar1586398 Fair, it's a known problem. I just haven't seen anyone from SpaceX actually publish the mass budget for the radiators on this specific system, and that's the number that tells you if it pencils out
Datacenters in orbit before we fix zoning laws, sure
Nobody in the replies gets to the cooling. Vacuum has nothing to dump heat into, so every watt leaves by radiator, and radiators are mass you paid to launch. Month six is where I'd want the numbers.
I'll believe this one when someone posts a thermal log
SpaceX, in partnership with Nvidia, has designed a space-optimized Vera Rubin NVL72 system for launch to orbit in Q4 next year, with significant scale in 2028
@HemantS42019742 True, and I'd say that's exactly the case where it bites you, tight spec plus a weak model still drifts on execution even when the intent was never in question
The better-engineer-needs-a-dumber-model line has it backwards. Knowing exactly what you want is the hardest input to execute, and a weaker model turns a precise spec into three rounds of correction while a smart one lands it on the first pass. Opus 4.8 over Fable, even when you could have written the code yourself