Table of Contents
If you are using Claude Code out of the box, you are likely playing with one hand tied behind your back. While Anthropic’s models are powerful, they suffer from the same limitation as every other LLM: a knowledge cutoff that leaves them blind to the immediate present.
In the world of AI development, "last week" is ancient history. Frameworks update, new libraries launch, and marketing meta-strategies shift overnight. To bridge this gap, tech veteran Matt Van Horn has developed a tool that acts as a real-time injection of expertise directly into your terminal. It is called Last 30 Days.
This skill for Claude Code allows developers and founders to scrape trending data from X (formerly Twitter), Reddit, and the open web to optimize prompts based on what is working right now. It is not just about writing code; it is about "vibe coding"—capturing the current zeitgeist to build products, designs, and copy that resonate immediately.
Key Takeaways
- Real-Time Context Injection: The "Last 30 Days" tool connects Claude Code to live data from X, Reddit, and the web, bypassing static training data limitations.
- Instant Expertise: Users can generate highly optimized prompts for niche topics—from cold email frameworks to specific UI trends—without prior knowledge.
- The "Vibe Coding" Workflow: By letting the AI research the current "meta" first, you can generate product requirements and code that align with modern standards automatically.
- No Coding Required: Non-technical founders are using this tool by pairing Claude Code with ChatGPT to debug terminal errors, effectively coding through plain English.
The "Last 30 Days" Superpower
The core premise of the tool is simple but transformative. When you ask a standard LLM to "write a cold email" or "build a landing page," it pulls from a vast but dated average of human knowledge. When you use the "Last 30 Days" skill, you are forcing the model to look at what is trending currently before it generates a single character of output.
Matt Van Horn compares this to the famous scene in The Matrix where Neo instantly learns Kung Fu. You do not need to read the last six months of newsletters to know which cold email subject lines are getting high open rates; the tool does that research for you in seconds.
"I feel like everything is moving so quickly in AI. It's nearly impossible to keep up with the conversation on X, on Reddit, on GitHub. I wanted a tool that gives you superpowers to be able to just become an expert on any topic based on what's happening... very, very quickly."
How It Works Under the Hood
To achieve this, the tool aggregates three specific data streams:
- Reddit: Accessed via an OpenAI key (leveraging OpenAI's data partnership with Reddit) to find raw, unfiltered user discussions and feedback.
- X (Twitter): Accessed via an XAI key to tap into the real-time stream of tech updates and thought leadership.
- The Web: General search queries to validate trends and pull documentation.
This combination ensures that when you ask for a solution, you aren't getting a textbook answer from 2021—you are getting the solution that experts are discussing today.
Optimizing Marketing and Design with Live Data
The utility of "Last 30 Days" extends far beyond writing software. It functions as a high-level research analyst for creative and strategic tasks.
Cracking the Cold Email Code
During a live demonstration, Van Horn showed how the tool could write a high-converting cold email with virtually zero context. He inputted a simple prompt about being a "former smart oven entrepreneur" pitching to Greg Isenberg.
Instead of guessing, the tool scanned recent discussions on cold outreach. It identified modern frameworks like the "Three P’s" (Praise, Picture, Push) and "Attention-Interest-Desire-Action" (AIDA), but applied them using current best practices found on X. The result was a highly personalized email that connected hardware manufacturing struggles to AI development—a genuine angle that a standard generic prompt likely would have missed.
Generating "Vibe-Based" Design Prompts
One of the most impressive capabilities of the tool is its ability to translate visual trends into technical prompts for design tools. When asked to research "web page designs getting the most love right now," the tool identified a shift toward "warm, humid" aesthetics, anti-grid compositions, and specific typography choices like Satoshi or General Sans.
It didn't just describe them; it generated a prompt ready for an AI design tool (like Figma AI) to execute. This allows a non-designer to bypass the "blank canvas" paralysis and immediately generate a UI that feels modern and relevant.
Building Enterprise Software from Scratch
For founders, the most potent application of this workflow is moving from a vague idea to a deployed product without writing the code manually. Van Horn demonstrated this by taking a trending open-source AI agent ("ClaudeBot") and asking the tool to research how to turn it into a profitable enterprise SaaS.
The workflow followed a logical progression:
- Trend Analysis: The tool identified that enterprise users want multi-tenant architecture, audit logging, and security compliance—features missing from the open-source version.
- Strategic Planning: It used that research to generate a comprehensive build plan, acting as a Product Manager.
- Execution: Using a tool like "Compound Engineering" alongside Claude Code, it began writing the actual code structure, setting up TypeScript and Node.js environments automatically.
This effectively automates the role of a CTO for early-stage prototyping. You are not just asking the AI to "build a bot"; you are asking it to "research what makes a bot profitable right now and build that."
A Guide for the Non-Technical Founder
Perhaps the most encouraging aspect of "Last 30 Days" is that it was built and is used by someone who openly admits to not having shipped code in years. Van Horn’s strategy for using Claude Code relies on a "two-window" approach that anyone can replicate.
The Two-Window Strategy
If you are intimidated by the command line (terminal), Van Horn suggests keeping two windows open:
- Window 1: Claude Code (Terminal). This is where the work happens. You run your commands and let the agent build the software.
- Window 2: ChatGPT. This is your debugger. When the terminal throws an error or you get stuck, you simply screenshot the terminal, paste it into ChatGPT, and ask, "What do I do?"
"I’m not a software engineer. I have not shipped anything of value since high school... My recommendation for starting out is set up Claude Code. It's magical. And keep a ChatGPT window open to ask questions to."
This loop removes the technical barrier to entry. You don't need to know the syntax for fixing an API key error; you just need to know how to copy-paste the error message. This allows founders to focus on the high-level logic and "vibe" of the product while the AI handles the syntax.
Conclusion
We are entering an era where the barrier to building software is no longer technical skill—it is context. Tools like Claude Code provide the engine, but they need the right fuel to run effectively. By using the "Last 30 Days" skill, you ensure that your engine is running on high-octane, real-time data rather than stale information.
Whether you are researching competitor strategies, looking for the next viral design trend, or building an enterprise SaaS platform, the ability to instantly download the last month of global knowledge into your AI agent is not just a productivity hack. It is, as Van Horn puts it, a legitimate superpower.
