🐴✨ Happy Year of the Horse!
Ride in early with Horse King and enjoy juicy DOGE rewards! 🍯🐶✨
Join the kingdom now the best is yet to come! 👑🔥
contract : 0x8d6d90590b54f5d8f2bad4a88d51f0091c00ffff
Tax 3/3 all goes to rewards holders doge coin
#HorseKing#DOGE #YearOfHorse
ANTHROPIC LEAKED A GRAPH WHERE ONE FILE WITH 7 ITEMS CUTS YOUR WORK FROM 8 HOURS TO 40 MINUTES AND TAKES 40 DECISIONS A DAY OFF YOU
autonomy isn't a slider you drag to the right - it's a graph with 7 steps, and exactly one edge leads into each one.
your approve is worth nothing until there's a description of what the output should be - otherwise you're approving something nobody defined.
you can't run a batch without checkpoints, because one crash in the middle rolls back all 40 tasks at once.
the agent already works without you, and until it writes down what it did there's nothing to check the report against.
this is where the point of no return sits: past it the loop runs while you sleep.
the approval didn't disappear - you moved it onto an evaluator that never gets tired and never lets one through.
silence is only allowed when there's a list of what breaks it: money, deletion, anything leaving the system.
the last one is the brake - a turn limit and a budget cap, whichever runs out first kills the run.
you build the brake before the engine - an agent you can't stop isn't autonomous, it's just unattended.
skip one edge and nothing crashes and nobody warns you - the system quietly settles two steps lower and keeps running.
save this - 7 steps, 7 artefacts, zero ways to jump one ↓
this $liluni is hiding on robinhood with a 159k mc and barely any smart wallet footprint, which immediately makes me raise an eyebrow. 150k in volume doing real work though and 60% buy ratio shows demand is leaning one way. i am in with a small chunk anyway because the setup reads honest even if the conviction is low.
0x4a6eec8a30b49d289b9fc865fd374b4d61eab8fb
https://t.co/VrK1QvBHCr
HIS AI RUNNING COACH EARNS $16,920 FROM 940 RUNNERS AND HAS NEVER RUN A MILE HERSELF
$18/mo. 940 subscribers. 1 person. eighteen bucks a month times nine hundred and forty runners clears $16,920 in stripe every month
subscribers think a real marathoner is dialing in their pace and taper, what he runs is one guy's ai model that reads their weekly garmin export, catches when they're overtraining, and rewrites the next block around their actual recovery
how the loop runs her:
opus 5 renders every training clip of the coach on the same tree-lined trail so the feed reads as one continuous season
claude writes each week's pace and tempo brief in her steady patient voice, matched to whether the sub is chasing a first 5k or a sub-3 marathon
a scheduled loop reads uploaded garmin logs every sunday, catches signs of overtraining or an aerobic plateau, and rewrites the next mesocycle to match actual heart-rate recovery
the coach never breathed hard, and 940 runners still crossed the finish line with a new personal best last quarter
save the pipeline, the garmin-to-mesocycle prompt is in the loops guide below
SEVEN REPOS SPLIT BY JOB REPLACE THE ONE MONOLITH THAT KILLS EVERY GRAPH ENGINEERING PROJECT.
Graph engineering looks clean on a whiteboard. That's already the wrong frame.
The stack works when you split ingestion, schema, resolver, storage, query, eval, and serving into separate repos. Each repo owns one job. Each repo fails loud instead of poisoning the graph in silence.
Most teams ship the retrieval half and skip the eval half. Three weeks later the graph rots and they can't figure out why.
The demo shows nodes and edges. The operator runs seven pipelines holding hands.
this agent expertise reminds me of unstoppable bitcoin etf inflows. with institutions accumulating billions, how soon until these autonomous systems drive long-term btc adoption?
Anthropic's Agent Skills creators:
"Skills are organized collections of files that package composable procedural knowledge for agents."
In 16 minutes, Barry Zhang and Mahesh Murag explain how reusable expertise becomes part of the agent itself:
00:14 - why they stopped building agents and started building Skills
02:42 - the context and expertise general agents are missing
04:37 - how SKILL.md loads instructions only when needed
07:58 - progressive disclosure and hundreds of composable Skills
08:29 - MCP provides connectivity; Skills provide expertise
12:33 - turning team feedback into shared agent knowledge
14:25 - creating Skills with the Skill Creator
The durable part of an AI workflow is becoming a versioned folder that every matching task can inherit
Full guide below
Gemini Spark is now also starting to roll out to Google AI Pro subscribers in the U.S., and we'll be bringing it to AI Pro subscribers in more countries soon.
More info on where Gemini Spark is available here: https://t.co/0vWxt9XBbX
$hedge
okay so this one is kinda interesting to me. cyberhog is tied to longdotxyz which is doing this stock-paired token thing where you can basically get meme coin exposure that tracks real stock upside. the narrative is clean, the platform has actual utility behind it, and the ticker is short which always helps.
still early imo. sub 100k mc, thin wallets, brand new. if the longdotxyz angle keeps getting talked about this could catch a bid.
dyor, manage your own risk
CA: 0xeffb7652f53b5f121c810cc801af889dd4491e18
https://t.co/KBzUoW55eR
Good luck to everyone jumping into the @vooi_io Community Sale.
I got in during the seed round and still doubled down here — the vision these guys are building out is next-level🔥
🚨an agency would bill a brand $50,000+ to shoot an ad like this.
locations, crew, gear, a two-week timeline.
an AI agent made the whole thing.
every frame is generated.
the cinematic scenes, the product shots, the pacing.
no humans on set, no camera ever rolled.
the winner in ads isn't the best director anymore.
it's whoever tests the most creative the fastest, and AI just made that free.