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Kontentsu kurieta
@Kontentsukpi
Content Creator & Researcher
Joined August 2026
32 Following
69 Followers
34 Posts
YOUR AI PROMPTS ARE STUCK IN 2022.
the models got 10x better.
your prompts got longer.
that’s the problem.
Claude Fable-5 doesn’t need a wall of examples, endless rules, and “think step by step” pasted onto every task.
delete:
→ long examples
→ step-by-step reasoning unless it’s maths
→ biased endings like “right?”
→ rule lists longer than 3
keep:
→ one crystal-clear goal
→ only the context it cannot know
→ 3 hard constraints max
→ an open-ended question
→ permission to ask before answering
the prompt I use now:
[GOAL]
the test the finished answer must pass
[CONTEXT]
only the facts the model would otherwise invent
[CONSTRAINTS]
3 hard limits. no more.
if anything is missing or unclear, ask before answering.
on Claude: add “use AskUserQuestion.”
and don’t trust sources blindly.
the model can find links that agree with an answer it already wrote.
prompt engineering didn’t die.
it got simpler because the models got smarter.
save this before your next prompt ↓
https://t.co/jhwjalnw8a
THE ONE-PERSON COMPANY IS ABOUT TO GET PERFECT MEMORY.
OpenAI CEO Sam Altman says that in the next 6 months, we may be close to AI that can:
→ watch your screen
→ record every meeting
→ capture every call
→ hold the full context of your life
the breakthrough isn’t better answers.
it’s never having to explain the work twice.
the founders who build around this first won’t need a bigger team.
they’ll need one operator:
themselves.
one person.
one system.
the operation running automatically.
Check out the video right now and bookmark this post. ↓
He built OpenAI in 7 days. At Stanford, he recreated it in 20 minutes.
Here is how to build your own AI company without investors and a team.
The video breaks down the exact process from scratch.
It also addresses the reality that 90% of professions will disappear. If you want to be among the 10% who survive and earn, this is the roadmap.
@henrikhinai These 12 steps will help you get a handle on AI and vibecoding.
@morpphhhaw You’ve gathered everything necessary in this article thanks.
ONE ENGINEER IS BECOMING AN ENTIRE TEAM.
the Head of Claude Code just revealed how far agent workflows have already gone inside Anthropic:
“85% of our engineers are running dozens or hundreds of agents.”
the method has a name:
graph engineering.
not one prompt.
not one assistant.
dozens - sometimes hundreds - of agents operating as a system.
in 40 minutes, he breaks down:
→ how one engineer now handles team-sized work
→ how deeply this has spread inside Anthropic
→ where graph engineering goes next
this isn’t something to catch up on later.
the shift is already happening.
watch the full conversation.
bookmark this before the gap gets wider ↓
https://t.co/HzRxabGscf
THE ONE-PERSON COMPANY JUST GOT A NIGHT SHIFT.
it’s Grok Bot.
most people see another AI chat.
the bigger play is an agent that keeps work moving 24/7.
set it up and hand it the repeatable loops:
→ find leads
→ write outreach
→ create images
→ reply + follow up
→ log + track
→ count the week
while you focus, it keeps operating.
while you sleep, the work doesn’t stop.
the leverage isn’t one great answer.
it’s a system of agents running the work around your decisions.
the full setup, plugins, use cases, and what makes Grok Bot work so well are in the article.
bookmark this ↓
https://t.co/TC69JABnvQ
@Skaly__Bull 300 agents replace approximately 30,000 people.
@kobaHUB This article is very good.
300 AGENTS CAN FIND EVERY FACT.
AND STILL FAIL THE TASK.
the reason is hidden in one line:
E_max = n(n−1)/2
findings grow one at a time.
relationships grow with every possible pair.
10 sources are manageable.
100 sources create 4,950 potential connections.
and the answer to:
who depends on whom?
what contradicts what?
which claim unlocks the next?
usually isn’t inside a report
it lives between reports.
that’s why fan-out isn’t the product.
merge is.
ask the swarm for nodes and you get 300 clean write-ups.
ask it for edges-dependencies, conflicts, support and sequence-and you get a graph you can reason over.
the instruction that changes the result:
return the relationships, not only the findings.
the full spec, the graph questions you didn’t know to ask, and the one rule worth keeping are in the article.
bookmark it. read below ↓
https://t.co/fYpaaiH1dP
@shmidtqq The hardest part is setting up these 100 agents
YOUR CLAUDE LIMIT DOESN’T DIE ON MESSAGE 30.
it dies rereading messages 1–29.
every time you hit send, Claude processes the conversation again.
that’s why a long chat gets more expensive even when your prompts stay short.
10 ways to stop feeding the loop:
turn PDFs into markdown before upload
one page: 1,500–3,000 tokens.
15-page report: ~38,000.
the same document as markdown: ~2,000.
new topic = new chat
20 messages: ~105,000 tokens.
30 messages: ~232,000.
edit the bad prompt instead of adding a correction.
request a surgical redo:
name the section. keep everything else. no commentary.
keep recurring files in a Project.
upload once. cap it around 6–8 files.
batch related asks into one message.
one reread beats three.
switch off connectors, web search and extended thinking when the job doesn’t need them.
match the model to the task:
Haiku for lookups.
Sonnet for most writing and editing.
Opus for decisions you can’t quickly check yourself.
decide the structure in chat.
generate the file after.
work with the 5-hour session window.
don’t burn the entire block before lunch.
the rule behind all ten:
less context reread.
more useful output per session.
save this before the bar turns red.
https://t.co/fYpaaiH1dP
@ridark_eth Hahaha, is that definitely a robot?
@henrikhinai This model could save humanity.
HE BEST CLAUDE CODE SIDE PROJECT FOR CREATORS DOESN’T CREATE A SINGLE POST.
it listens.
for your audience:
-> watches reddit, twitter, youtube comments wherever your ICP speaks
-> extracts pain points, questions, objections and unmet needs
-> returns fresh problems every week that nobody is addressing yet
for your competition:
-> finds every competitor targeting the same ICP
-> pulls their content and offers across platforms
-> analyzes what is working
-> reverse-engineers the patterns so you stop guessing
then it turns the raw signal into structured context profiles + reusable skills.
when you create content or build an offer, you don’t start from a blank page.
you start from what the market is already telling you.
build the listener before you build another content generator.
https://t.co/HzRxabGscf
AI DIDN’T KILL THE ANIMATION PIPELINE.
IT TURNED IT INTO SOFTWARE.
old workflow:
-> rewrite the scene
-> reopen every file
-> re-export every version
-> hope nothing broke downstream
new workflow:
-> change the intent
-> trace the affected shots
-> rebuild only what changed
-> run continuity checks
-> ship every format from one timeline
the breakthrough isn’t “one prompt makes a movie.”
it’s that creative work can finally iterate like code.
direct the system. don’t babysit the files.
save this workflow.
https://t.co/nOMpBIZbkG
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