Source URL: https://www.tomtunguz.com/english-as-input/
Source: Tomasz Tunguz
Title: How AI Redefines User Experience
Feedly Summary: What if every software spoke English? We asked this question about two years ago but now they do – with AI we can retrofit existing apps to speak English.
I don’t want to have to figure out any particular menu to find a setting or understand how a product manager or designer intended me to use the product.
I just want to talk to my computer and tell it what to do.
So I’ve started to invent tools that help me do this. Here are some movies of them & admittedly they are quite simple.
Sometimes I just want to send a quick email with my voice. I wrote a Python script where I can dictate an email. The computer will figure out what I mean, who I intended to send it to, and if it needs clarification, raise its hand and ask me to disambiguate the recipient.
Here’s an example of me asking for help from PitchBook customer support to reset my password :
AI email drafter. – Watch Video
Sometimes I’m on the go and I need to dictate a task. Rather than navigating the UI of my to-do app (who has time for 5 clicks?), I created an Android app within about an hour that uses the on-device machine learning model from Google Gemini Nano to summarize and transcribe the task & then send it to my task manager.
It’s not perfect. You can see it doesn’t capture the due date quickly, accurately, but something to focus on improving next weekend.
Over the weekend, I was migrating to a new computer and rather than install all the software I need manually, I used AI coding agents, Claude Code and Cursor, telling them which libraries and repositories I needed, which software I wanted, what environment I preferred. I let them start and 20 minutes later, my computer was 80% ready.
This is the beginning of an era where we are no longer instructing computers, we are delegating tasks to them to figure out, iterate, decide, raise questions when input is needed but otherwise continue.
It’s fundamentally changing both the way we interact with computers and also how designers and product managers will need to design.
If it’s trivial for hundreds of millions of people to develop their own UIs for the core tasks within an app, it highlights a couple of things. The first is very difficult for a PM and a designer to understand all the user segments and use cases.
And the second is the way functionality is exposed will likely need to evolve to make these kinds of custom UIs simpler.
AI Summary and Description: Yes
Summary: The text discusses the innovative applications of AI in enhancing user interaction with software through natural language processing. This emerging trend emphasizes a transition from traditional software interfaces toward more intuitive, voice-driven user interfaces that simplify tasks and increase accessibility.
Detailed Description: The provided content explores the rapid evolution in how users can interact with software systems, particularly emphasizing the integration of AI technologies for natural language processing. Some key points include:
– **Voice Interaction**: Users are increasingly desiring voice-enabled functionalities that allow them to communicate tasks directly, eliminating the need for navigating complex user interfaces.
– **AI-Driven Tools**: The author describes creating tools that utilize AI for tasks such as dictating emails and managing to-do lists, illustrating the practical application of these technologies in everyday scenarios.
– **On-Device Machine Learning**: The mention of Google Gemini Nano highlights the significance of on-device processing capabilities for quick task summarization and transcription.
– **Autonomous Task Management**: The author exemplifies how AI coding agents can autonomously set up new environments by understanding user preferences and requirements.
– **Changing Design Paradigms**: The text suggests a paradigm shift in design and product management, where understanding diverse user segments may become more challenging as users create customized interfaces for functionality.
In summary, the narrative presents a forward-looking perspective on the integration of AI in user interfaces, offering insights into how these innovations are not only transforming user experiences but also necessitating a reevaluation of product design strategies in a landscape where user interactions become increasingly sophisticated and individualized.
– This shift could lead to enhanced user satisfaction and productivity but also poses challenges in terms of designing software that accommodates these diverse customizations.
– It highlights the importance of machine learning and AI technologies in meeting user demands and streamlining workflows.
Overall, the implications for AI and software security professionals could involve ensuring that these emerging tools maintain high standards of data privacy and security while remaining user-friendly.