To maximize efficiency, trigger AI-powered micro-apps with keyboard shortcuts. This eliminates multiple clicks and context switching, making the interaction feel seamless and fast. Latency is a critical factor in the usability of AI products.
The new paradigm for building powerful tools is to design them for AI models. Instead of complex GUIs, developers should create simple, well-documented command-line interfaces (CLIs). Agents can easily understand and chain these CLIs together, exponentially increasing their capabilities far more effectively than trying to navigate a human-centric UI.
Instead of relying on one-off prompts, professionals can now rapidly build a collection of interconnected internal AI applications. This "personal software stack" can manage everything from investments and content creation to data analysis, creating a bespoke productivity system.
While chatbots are an effective entry point, they are limiting for complex creative tasks. The next wave of AI products will feature specialized user interfaces that combine fine-grained, gesture-based controls for professionals with hands-off automation for simpler tasks.
For recurring AI tasks, such as loading project-specific diagrams or switching models in Claude Code, create short shell aliases (e.g., 'cdi' for 'Claude diagram load'). This avoids retyping long commands and allows you to quickly switch contexts or modes.
The best agentic UX isn't a generic chat overlay. Instead, identify where users struggle with complex inputs like formulas or code. Replace these friction points with a native, natural language interface that directly integrates the AI into the core product workflow, making it feel seamless and powerful.
Open-ended prompts overwhelm new users who don't know what's possible. A better approach is to productize AI into specific features. Use familiar UI like sliders and dropdowns to gather user intent, which then constructs a complex prompt behind the scenes, making powerful AI accessible without requiring prompt engineering skills.
The most effective application of AI isn't a visible chatbot feature. It's an invisible layer that intelligently removes friction from existing user workflows. Instead of creating new work for users (like prompt engineering), AI should simplify experiences, like automatically surfacing a 'pay bill' link without the user ever consciously 'using AI.'
Instead of jumping between apps, top PMs use a central tool like Claude Desktop or Cursor as a 'home base.' They connect it to other services (Jira, GitHub, Sanity) via MCPs, allowing them to perform tasks and retrieve information without breaking their flow state.
When prototyping new AI-powered ideas, build them as command-line interface (CLI) tools instead of web apps. The constrained UI of the terminal forces you to focus on the core workflow and logic, preventing distraction from visual design and enabling faster shipping of a functional version.
While AI-native browsers are versatile, they can be slow. For frequent, specific tasks, building a focused micro-app provides a faster, more efficient user experience. A specialized 'drill' is better than a general-purpose 'Swiss Army knife' for high-frequency workflows.