Clicky vs Mediator.ai

Clicky is a Mac application that surfaces an AI assistant inline — directly adjacent to your cursor — without requiring you to switch windows or paste context manually. The app maintains persistent screen awareness, reading what's in front of you and using that context to answer questions, guide tasks, and make suggestions relevant to what you're doing in any application. Unlike clipboard-based AI tools that require explicit copy-paste workflows, Clicky works through ambient screen reading: you invoke it with a hotkey, it understands the current screen context automatically, and responds inline. The approach is closer to GitHub Copilot's ghost-text model than a chat sidebar — the assistant lives where your attention already is. The indie approach prioritizes a single, focused Mac use case rather than trying to be a cross-platform agent platform. Early Product Hunt reception highlighted the overlay UI and the speed of context capture as standout experiences. For knowledge workers who context-switch constantly between reference material, documentation, and writing tools, the cursor-adjacent model reduces the friction of asking a question by eliminating the need to describe what you're looking at.

Mediator.ai applies LLMs and Nash bargaining theory to real-world disputes, generating agreements that both parties would accept — including solutions neither side had imagined independently. The process is private by design: each party separately describes their position, priorities, and constraints. The AI then generates multiple candidate agreements, scores each one against both parties' stated needs, and iteratively refines proposals until reaching an optimal solution. Use cases range from founder equity disputes and contractor payment conflicts to shared housing arrangements and inheritance disagreements. The system's key insight is that human negotiation is systematically bad at identifying the entire solution space — we anchor on positions, not interests. By modeling both parties' utility functions simultaneously, the AI can find Pareto-optimal outcomes that pure adversarial negotiation often misses entirely. With 159 Hacker News points, the response was genuinely enthusiastic — and the concept is hard to dismiss. Nash bargaining as a formalism has decades of academic credibility; what's new is making it accessible via natural language input. The pricing isn't published yet and the team is small, but the application domain (legal, HR, personal disputes) is enormous if they can nail trust and confidentiality.