TheSmartApe🔥

Most AI tools help you talk to AI. Very few help you deploy AI.
Tried many AI tools this week and enjoyed using @CreaoAI.
It's a kind of execution system, you can prompt but also build infra directly with it.
At the center is the Super Agent and every conversation can turn into a permanent Agent App.
With ChatGPT or Claude:
You ask → you get output → session ends → context gone.
With CREAO:
You ask → it builds an Agent App → it runs forever.
The agent app is executable and persistent. You can keep it always on if you want. Means you don't have to re-explain or copy paste prompt each time. I th

how to make $2K/month selling an AI agent you can build this weekend.
97% of consumers read online reviews before choosing a local business, but 87% of businesses never respond to negative reviews.
a one-star improvement on Google = 5-9% revenue increase. for a restaurant doing $500K/year, that's $25-45K in lost revenue.
this is a big gap. and you can fill it with a simple AI agent.
the agent flow would be:
1/ monitors Google Business Profile for new reviews (polling every 15 min)
2/ for positive reviews (4-5 stars): generates a personalized thank-you reply and posts it automatically
3/ for

Your AI agent can now trade on solana. here's how.
@dflow just dropped two things that change everything:
> a universal MCP server: gives your agent direct access to solana trading infra
> a Claude Code skill (with Phantom): agents can build full-stack solana apps from a single prompt
How to use it:
> install the DFlow MCP server → add it to your claude config or OpenClaw MCP config
> set up Phantom Connect → browser wallet, embedded wallet, or mobile deep links
> point your agent at a task → "build me a SOL/USDC swap interface"
> deploy → production-ready code
It's interesting because they're

Anthropic open-sourced the skills that power Claude's document features. 16 skills.
Most are examples. But 4 of them, PDF, DOCX, PPTX, XLSX, are the actual production code running behind Claude's "create a document" feature.
The 3 worth installing right now:
→ MCP Builder. Step-by-step guide for building Model Context Protocol servers. API research, tool naming, auth patterns, error handling.
→ Webapp Testing. Playwright-based toolkit with a decision tree. Server lifecycle manager. Screenshots, logs, the works.
→ Skill Creator. A skill for building skills. Draft, test, benchmark, optimize tri

We recently saw a $1.78M exploit caused by a vulnerability written by Claude Opus 4.6.
cbETH was priced at $1 instead of $2,000.
Not long after @OpenAI launched EVMbench. To put it simply, it’s a benchmark that evaluates AI agents' ability to interact with smart contracts.
It has 3 main evaluation modes:
> Detect: analyzes the agent’s ability to detect vulnerabilities
> Patch: analyzes the agent’s ability to fix those vulnerabilities
> Exploit: analyzes the agent’s ability to exploit those vulnerabilities
Their analysis showed that recent models (Opus 4.6, GPT-5.3-Codex, etc.) are very good at

I built a theoretical probability model to estimate the UP and DOWN price for BTC 15-minute markets on @Polymarket.
The model computes probabilities using only the target price, the current BTC price, and the time remaining before the round ends.
I didn’t expect this theoretical model to be that close to real market probabilities. The gap between market prices and the model’s probabilities is only 1–5%, which means the model tracks reality extremely well.
In this market, probabilities are directly set by traders.
This clearly shows how bot-dominated it is, driven by logical rules and algorithm

burning money to build.

Me lowkey waiting for the US to wake up so $CLAWNCH can finally send it.