The broader market often lacks the economic incentive to create robust, niche accessibility software. AI empowers individuals to build highly customized solutions for their specific needs, democratizing the creation of assistive technology.
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.
AI coding assistants reduce development time from days to just minutes or hours. This makes building custom tools to save a few minutes daily a highly valuable investment, as the payback period for the time spent building is now incredibly short.
Continuously trying to correct a confused AI in a long conversation is often futile, as a 'poisoned' context can lead it astray. The most effective approach is to abandon the conversation, start a new one, and incorporate your learnings into a better initial prompt.
Creating integrations for native desktop applications can be difficult. A powerful workaround is to use the web-based version of the app, like Slack in Chrome. This allows you to build custom Chrome extensions that can read content, trigger actions, and automate workflows.
Instead of typing long prompts directly into the terminal, use the Ctrl+G shortcut in Claude Code. This opens the prompt in a full text editor, which is more screen-reader friendly and easier for anyone to navigate, review, and refine complex instructions.
Instead of learning new technologies for each personal project, focus on a single framework like Chrome extensions. Create an AI "skill" or template for that framework. This compounds learning and allows you to build new custom tools much faster by focusing on the use case, not the underlying tech.
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.
While AI models don't produce accessible code by default, they can do so effectively when instructed. Because web accessibility standards like ARIA are extensively documented, models can follow specific prompts to generate code for components that are screen-reader friendly.