Professionals in fast-paced industries often struggle with email overload, particularly from messages filled with vague buzzwords that obscure their actual intent. While spam filters catch obvious scams, they miss subtler forms of low-value communication, leaving users to waste time deciphering or deleting such emails. A tool that identifies and filters these "bullshit" messages could help prioritize meaningful correspondence and improve productivity.

How It Could Work

One approach would involve building an email filtering system that detects overused or hyperbolic language. This could start with basic keyword detection—flagging terms like "game-changing" or "exclusive offer"—while allowing users to customize their own list of trigger words. Over time, the system could incorporate machine learning to improve accuracy by analyzing sender reputation, email frequency, and contextual usage. For example, the word "collaborate" might be fine in a colleague’s message but suspect in a cold pitch.

To refine the tool, users could provide feedback by labeling emails as "bullshit" or legitimate, training the algorithm to adapt to their preferences. Ideally, it would integrate with major email platforms like Gmail or Outlook, either as a plug-in or browser extension.

Potential Benefits and Challenges

The tool could save time for professionals who receive high volumes of buzzword-laden outreach, such as founders, marketers, or consultants. However, false positives might occur if legitimate emails use flagged terms. This could be mitigated by allowing users to whitelist trusted contacts or domains. Additionally, since buzzwords evolve, the system would need regular updates—perhaps through crowdsourced suggestions or automated tracking of emerging jargon.

• MVP path: Start with a shared Gmail filter template or lightweight extension, then scale to AI-driven features.
• Monetization: Offer a freemium model with advanced analytics or team customization for paid tiers.

Standing Out From Existing Tools

Current solutions like SaneBox focus on email prioritization, not language quality, while Boomerang helps with scheduling rather than content filtering. A tool specifically targeting buzzwords could fill a niche by reducing the cognitive load of parsing inflated or vague language.

Testing early assumptions—like user willingness to adopt such a tool or the accuracy of keyword detection—could involve a demo version with optional feedback prompts to gauge interest and refine the approach.