"Last 30 Days" shows that accessing high-value, real-time data from platforms like X and Reddit isn't trivial. Users must assemble a personal "stack" of API keys (OpenAI for its Reddit deal, an X API key) to power the tool, highlighting the fragmented nature of data access for AI.

People struggle with AI prompts because the model lacks background on their goals and progress. The solution is 'Context Engineering': creating an environment where the AI continuously accumulates user-specific information, materials, and intent, reducing the need for constant prompt tweaking.

Combine specialized AI tools in sequence. Use one tool (like "Last 30 Days") to research a trending market signal, then feed that context into another (like "Compound Engineering") to generate a business plan and technical architecture, drastically accelerating the ideation-to-development pipeline.

For AI Search Optimization (AEO), content freshness is critical. Research shows that content updated within the last three months is three times more likely to be cited by LLMs like ChatGPT compared to content left untouched for six months or more, revealing a steep drop-off curve.

When querying ChatGPT for trends or tactics, failing to specify a time period (e.g., 'in the last 60 days') will result in outdated information. The model defaults to data that is, on average, at least a year old, especially for fast-moving fields like marketing.

The challenge in using AI effectively is often prompt engineering, not model capability. A potential solution is a social platform where users can follow experts, discover their prompts, and be 'catalyzed' by others' creativity. This democratizes access to AI's full potential beyond one's own ingenuity.

To signal recency to Large Language Models (LLMs), marketers must include specific time periods (e.g., year, quarter, month, or 'Updated [Date]') directly in content titles. This simple change makes content over 50% more likely to appear in AI-generated results on platforms like ChatGPT, which are rapidly replacing traditional search.

When an AI tool automatically gathers rich, timely context from external sources, user prompts can be remarkably short and simple. The tool handles the heavy lifting of providing background information, allowing the user to make direct, concise requests without extensive prompt engineering.

Simply using one-sentence AI queries is insufficient. The marketers who will excel are those who master 'prompt engineering'—the ability to provide AI tools with detailed context, examples, and specific instructions to generate high-quality, nuanced output.