All of AI, minus the hype. Just what actually works.
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Joined September 2022
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pick a f*cking side. $PROPHET just shipped something clever - and it’s free to play.
the mechanic: your community makes ONE call. a single yes/no question with a real source - ape (yes) or fade (no). you vote, the majority becomes the pick.
every voter gets a tokenized prediction: an NFT of that call. got it wrong? burn it in the graveyard and it unlocks a free spin on Prophet’s wheel. hit or miss, everyone still gets the spin.
no wallet, no cost - sign in with X and you’re in, they make the wallet for you.
built on Robinhood Chain. not financial advice, nothing here is a promised return - it’s a community call game, and it’s genuinely fun to play.
so: ape or fade?
vote: graveyard.prophetthedog.xyz/…
Papertrade has been proposed to be a $60M rug scheme
Its TVL experiences a loss of 70%, sliding down from $100M to $36M since launch date
Never was bullish on it, moreover after points system update (early users' efforts will be washed)
Here's how to profit from the TVL fall:
I made a prediction that Papertrade's TVL will not be above $35M on Tuesday on Prophet [graveyard.prophetthedog.xyz/…]
In return I get a tokenized prediction, an NFT that shows my picked side
> If my prediction wins - I get an airdrop in $PROPHET
> If not - I can burn my NFT and spin a wheel and still get some portion of tokens
That's basically rekt to riches mechanic
this is f*cking wild. four models, one radial engine, four different brains.
Claude Opus 5.5 · GPT-6 Astra · Gemini 4 Argon · Grok 4.7
same words, four completely different machines. look at the cylinder count, the symmetry, how much each one packed in before calling it done. one over-engineers, one keeps it lean, one barely commits. it stopped being about accuracy - it’s how each model decides what “enough” is.
I’m not calling a winner. that’s on you.
which engine would you actually trust to turn over - Opus, Astra, Gemini or Grok? drop your pick and tell me why.
Kinder retweeted
this is f*cking gold.
Every time you explain your projects to Claude from scratch, you’re doing work your files could be doing for you.
Here’s a second-brain setup you can actually copy:
1. Create a folder called second-brain and open Claude Code inside it.
2. Add three folders:
• notes/ - facts, research, ideas
• people/ - contacts and meeting notes
• projects/ - one file per active project
3. Add three files:
• MEMORY.md - essential context about you
• decisions.md - decisions and the reasoning behind them
• LEARNINGS.md - mistakes, lessons, things to repeat
4. Create CLAUDE.md in the root folder. Describe where everything lives, then add these rules:
Read the relevant files before answering. Cite the file you used. If information is missing, say so. Keep one topic per file. Update existing notes instead of creating duplicates.
5. Start with ONE real project. Add its goal, current status, last decision, blocker, and next action.
6. Test it:
Where did I leave this project, why did I choose this approach, and what should I do next?
Check the answer against your files.
7. Before ending a work session, ask:
Save today’s decisions, update the project status, and record the next action.
That last step keeps the system useful tomorrow.
The video shows how these pieces connect. Save this checklist, then open the quoted guide for the full setup.
this is f*cking gold.
Every time you explain your projects to Claude from scratch, you’re doing work your files could be doing for you.
Here’s a second-brain setup you can actually copy:
1. Create a folder called second-brain and open Claude Code inside it.
2. Add three folders:
• notes/ - facts, research, ideas
• people/ - contacts and meeting notes
• projects/ - one file per active project
3. Add three files:
• MEMORY.md - essential context about you
• decisions.md - decisions and the reasoning behind them
• LEARNINGS.md - mistakes, lessons, things to repeat
4. Create CLAUDE.md in the root folder. Describe where everything lives, then add these rules:
Read the relevant files before answering. Cite the file you used. If information is missing, say so. Keep one topic per file. Update existing notes instead of creating duplicates.
5. Start with ONE real project. Add its goal, current status, last decision, blocker, and next action.
6. Test it:
Where did I leave this project, why did I choose this approach, and what should I do next?
Check the answer against your files.
7. Before ending a work session, ask:
Save today’s decisions, update the project status, and record the next action.
That last step keeps the system useful tomorrow.
The video shows how these pieces connect. Save this checklist, then open the quoted guide for the full setup.
this is f*cking surreal. same prompt, two models - and an entire galaxy ended up inside a falling raindrop.
GPT-6.1 Sol vs Opus 5.5. no edits, no cherry-picking. top is Sol, bottom is Opus.
three scenes, one prompt each - and the two read the same idea completely differently. neither is wrong, which is what makes it a hard call.
I’m not picking a side. that part’s on you.
which row goes in the trailer - Sol’s or Opus’s? drop your pick below, and tell me why.
next matchup drops here in a few days.
Kinder retweeted
this is f*cking gold. I turned Claude into 99 one-tap commands that actually make life easier.
no more retyping the same prompt every time - you just drop the command + your input:
/HOOK → five scroll-stopping hooks
/ELI10 → explain anything like you’re 10
/DECLINE → a polite no in one line
/SUM3 → any wall of text in 3 bullets
/STEELMAN → the strongest case for any view
...and 94 more - email, writing, planning, meetings, brainstorming, decisions, all of it.
save this one. you’ll reach for it every week.
full list in the replies
this is f*cking gold. I turned Claude into 99 one-tap commands that actually make life easier.
no more retyping the same prompt every time - you just drop the command + your input:
/HOOK → five scroll-stopping hooks
/ELI10 → explain anything like you’re 10
/DECLINE → a polite no in one line
/SUM3 → any wall of text in 3 bullets
/STEELMAN → the strongest case for any view
...and 94 more - email, writing, planning, meetings, brainstorming, decisions, all of it.
save this one. you’ll reach for it every week.
full list in the replies
this is f*cking unreal. same prompt, two models - a white tiger prowling across a palace floor.
Gemini 4 Argon vs Opus 5.5. no edits, no cherry-picking. top is Gemini, bottom is Opus.
same words, two completely different predators. one locks eyes with you and stalks straight into frame - cold, controlled, already hunting. the other throws its head back mid-roar in a shaft of light, all fury and motion. one chose menace. one chose drama. neither is wrong, and that’s exactly what makes it a hard call.
I’m not picking a side on this one. that part’s on you.
which tiger goes in the trailer - Gemini’s or Opus’s? drop your pick below, and tell me why.
I run one of these every week.
It is becoming f*cking dangerous.
A 24-year-old dev from China just wired 300 parallel Claude Code agents straight into a live weather simulation and built a global predictive swarm on one screen.
He opens the dashboard:
• 300 specialized agents running in parallel across global nodes
• 1.29 million data points processed in real time
• model error driven down to 1.71°C through automated ensemble checks
• a full 5-hour cyclone forecast rendered in seconds
the trick is the pipeline: simulation agents run the physics while verification agents audit every step against raw satellite data - and nothing moves forward until the error hits baseline.
a meteorology lab with a supercomputer used to burn weeks on this. he got full-globe dynamics in seconds, on a laptop.
and here’s the part that matters: it’s all one split - the expensive model does the work, a cheaper one checks if it’s actually true. that’s not a weather trick, it’s how every serious agent stack is about to run.
which model does what, and what each one really costs - I broke the whole thing down in the piece I’m quoting.
this is f*cking unreal. same prompt, two models - and a rhino came up out of a persian rug.
Gemini 4 Argon vs Opus 5.5. no edits, no cherry-picking. top is Gemini, bottom is Opus.
same words, two completely different beasts. one rose wrapped in glowing armor - ornate, radiant, built like a myth. the other came up as a real rhino with a single horn burning like a blade. one went for spectacle. one went for restraint. neither is wrong, and that’s exactly what makes it a hard call.
I’m not picking a side on this one. that part’s on you.
which rhino goes in the trailer - Gemini’s or Opus’s? drop your pick below, and tell me why.
I run one of these every week
this is getting f*cking dangerous.
a 20-year-old student from China just built a living, interactive ocean in the browser - clickable sea life, real currents, the whole reef breathing - and ran the whole thing on AI for under $10.
he dropped the exact same prompt into two frontier models to see which one would actually build it:
ChatGPT-6 Astra → $27.84
Claude Opus 5.5 → $9.06
same world, same prompt - and the cheaper model came back richer. more fish, denser reef, better light, done in one pass.
a design studio would quote you thousands and three weeks for an interactive scene like this. he built it in an afternoon, picked the $9 model, and kept the change.
the agencies still charging $5k for “custom web experiences” should be sweating - this is the month that work quietly got automated.
save this one. it won’t stay quiet for long.
this is a f*cking goldmine. same prompt, two models, one molten elephant and they went in completely different directions.
Gemini 4 Argon vs Opus 5.5. no edits, no cherry-picking. top is Gemini, bottom is Opus.
I’m not calling a winner on this one. watch both - the fire, the detail, the way each one read the same idea.
you make the call. which elephant goes in the trailer, Gemini’s or Opus’s?
drop your pick below.
I run one of these every week.
Kinder retweeted
this is f*cking gold. ChatGPT isn’t a chatbot anymore - it’s turning into a full operating system for work.
everyone still opens it to ask a question. the real shift is everything wired around the models: reasoning, deep research, Codex, ChatGPT Work running long tasks, memory, projects, scheduled jobs, connected tools, custom GPTs.
OpenAI quietly turned a text box into a production stack - a model picks the task, agents run it, memory keeps it, automations repeat it.
and that flips the skill. knowing which model to prompt isn’t the edge anymore. knowing how reasoning, memory, agents and automation fit together is what separates people asking ChatGPT things from people building on it.
I mapped who actually wins at what across the whole thing in the piece I’m quoting.
save this if you want to see where this is actually heading.
this is f*cking gold. ChatGPT isn’t a chatbot anymore - it’s turning into a full operating system for work.
everyone still opens it to ask a question. the real shift is everything wired around the models: reasoning, deep research, Codex, ChatGPT Work running long tasks, memory, projects, scheduled jobs, connected tools, custom GPTs.
OpenAI quietly turned a text box into a production stack - a model picks the task, agents run it, memory keeps it, automations repeat it.
and that flips the skill. knowing which model to prompt isn’t the edge anymore. knowing how reasoning, memory, agents and automation fit together is what separates people asking ChatGPT things from people building on it.
I mapped who actually wins at what across the whole thing in the piece I’m quoting.
save this if you want to see where this is actually heading.
this is f*cking wild. 4 AIs, one prompt - build a radial engine - and not one built the same machine.
Claude Opus 5.5 · GPT-6 Astra · Gemini 4 Argon · Grok 4.7
same words, four completely different instincts. Astra over-built it - every cylinder, every bolt, a full holographic blueprint. Opus went tight and clean, exactly enough and nothing extra. Gemini leaned industrial, all fins and mass. Grok kept it simple - maybe too simple.
this is the part benchmarks never catch. build it isn’t one skill. one model shows off, one model edits itself, one model shrugs. the gap isn’t accuracy anymore - it’s taste and restraint.
so which one would you actually trust to turn over and run? Opus, Astra, Gemini or Grok?
I run one of these every week, and the differences only get sharper.
This is f*cking gold. Claude isn’t just an AI model anymore - it’s becoming an entire operating system.
everyone’s still arguing Opus vs Sonnet. the real shift is everything being built around the models.
reasoning models, the Agent SDK, managed agents, MCP, memory, workspace tools like Code and Cowork - all the way to production. Anthropic quietly turned a chatbot into a full stack.
and that changes what you actually need to know. prompts aren’t the skill anymore. knowing how the models, memory, MCP and deployment fit together is what separates people playing with AI from people shipping it.
the future doesn’t belong to whoever can name the “best model.” it belongs to whoever understands how the whole thing works together.
that’s exactly what the article I’m quoting nails from the build side: stop running one Opus on everything - wire a team instead.
save this if you’re trying to figure out where AI engineering is heading in 2026
It is becoming f*cking dangerous. GPT-6 Astra vs Opus 5.5, same prompt, every clip.
A shark out of a persian rug. A warship swallowed by a wave. One row is AI, and so is the other. Six months ago you caught the fake in a second: the hands, the physics, the melt. Now I’m staring at my own renders trying to remember which ones I made.
The deepfake problem everyone called years away is now one sentence typed into a laptop. So forget who won, the real question is what happens when no clip can be trusted again. And we’re already there.
I run one of these every week. staying ahead of it is starting to feel less optional than it used to.
holy sh*t. Claude Opus 5.5 vs GPT-6 Astra - a frontier model just got mated in 22 moves.
a full chess game. no engine, no internet, just two models thinking move by move. fresh sessions, high effort, no bot, no script, no lookup. Opus on white, Astra on black, one board between them.
Opus castled queenside and looked completely fine. then Astra went quiet and started prying open the b-file - slowly, one move at a time, straight at Opus’s king.
by move 20 you could feel it. Opus’s king had no air left. every black piece was pointing at the same corner.
move 22. Opus plays Nc2 - the one move that stops guarding b2. Astra pounces: Qxb2#. mate.
and here’s the brutal part. Opus knew. its own post-game note: “I was worried about ...Ba3 and missed it.” it felt the attack coming, braced for the wrong threat, and walked into the real one.
final: 0-1. a frontier model, checkmated in 22 - by nothing but the other model’s head.
so what is this: Astra’s just the sharper tactician, or Opus choked under its own overthinking?
follow - I run a new model showdown every week. chess was only round one.
this is f*cking insane:
Opus 5.5 · Gemini 4 Argon · GPT-6 Astra · Kimi K3
one prompt - build a top-down traffic sim. four models, four price tags right on screen.
$1.36 for Astra. $0.06 for Kimi K3. twenty-two times apart.
and this time you can see where the money went. Astra’s is the cleanest - real lanes, real flow. Kimi’s $0.06 run looks exactly like a $0.06 run.
that’s the part the just use the cheap model crowd skips. sometimes the gap is real. $0.06 is no deal if you can’t ship what it hands you.
the move isn’t always cheapest. it’s the one that clears the bar without overpaying - and Gemini at $0.41 is quietly making that case.
so which one actually clears it for you?
I ran the full breakdown - who wins at what in 2026, and what each one really costs. it’s the piece I’m quoting.
new matchup like this every week. hit follow so the next one finds you.