--- title: "Agentic UI Series - Post 1: Why Chat Interfaces Will Stick Around For A While (and Where They Fall Short)" description: "Chat was how GenAI went mainstream. Here’s what it’s good at, where it breaks, and why it’ll stick around until we invent better interfaces." date: "2025-09-22" tags: ["AI", "Agentic AI", "UX"] status: "Published" --- ## Key takeaways - **Chat sent GenAI mainstream** - a simple text box, the first interface to gpt-3.5, was enough to introduce millions of people to LLMs & GenAI for the first time. - **It’s flexible and forgiving** - open‑ended chat invites creativity and rapid iteration. It’s like the command line for non‑coders. - **But it's also overwhelming** - blank pages and completely open-ended possibilities create **decision paralysis**. Good UX patterns (starter prompts, enhanced inputs) are essential. - **Voice is now real** - low‑latency, interruptible speech makes "chatting" to AI feel close to real conversation, but it comes with text chat’s strengths and limits. - **It’s not the final form of AI interactions** - chat will remain the default for a while (we already live in Slack/Teams), but I don’t believe we’ve found the best UI/UX for working with AI systems yet. --- ## How we got here: next‑token prediction → chat windows Large language models are trained to **predict the next token**. That simple objective turned out to be incredibly powerful: wrap it in a friendly chat UI and you get ChatGPT, the product that brought LLMs to the mainstream consciousness. > The chat box is the new command line for non-developers. **Why it worked:** - **Zero‑setup, zero‑knowledge.** Users could  interact successfully with ChatGPT without learning *how* to use it or having deep technical skills. - **It’s responsive and reactive.** Ask → get an answer → repeat. - **(Almost) Unlimited use cases.** One interface worked for ideation, drafting, coding, planning and anything else people could come up with. ## Where Chat Works Well (and how to build on that) - **Creativity & exploration.** Chat’s open‑endedness helps people *discover* uses. Support it with **prompt suggestions** that show example use cases in the empty state. - **Rapid iteration.** Keep turns quick and answers not overwhelmingly long, acknowledge the model won’t always get things right first time and  propose next steps. - **Personalisation.** Light‑weight **memory** (preferences, glossaries, goals) reduces re‑prompting, improves consistency and builds relationships. - **Low onboarding effort.** Anyone who can type a message can get started - keep it simple. **Design Choices To Improve The Experience** - Give the user **starter prompts** (sample use cases, templates, builds on previous entries). These reduce the **blank‑page problem** and teach people what tools can be used for. - Offer **structured outputs** (tables, checklists, JSON) the user can easily copy into other tools. Nothing happens in one master platform (yet...) and we’re getting to the point where chat-based tools can output full Excel spreadsheets or Powerpoint presentations already. ## Where Chat Falls Down (and how to improve it) - **Decision paralysis.** Completely open prompts can give users paralysis of choice or send them down rabbit holes. Counter with visible **capability menus** (using chips and suggestions) and clear next actions. - **Messy state.** Long replies and threads hide key facts and decisions. Solve this with **named tasks/conversation** summaries, and **memory** that persists across chats. - **Reproducibility.** LLMs are variable by design, but in a wider system consistency is more important. Add **system prompts, retrieval, typed tools, and evaluation** to raise floor consistency. Experiment with parameters like temperature to find the ideal level for each use case. - **Break down tasks** Chat isn’t great at co-ordination. For workflows, pivot to **structured flows/inputs** (forms, planners) and han**d** tasks to an **agent** that expects and returns fixed formats. ## Voice Chat Is Now Good(ish) Low‑latency, interruptible speech changes the feel of chat, makes it more “human” and opens more use cases: - **Pros of voice chat:** hands‑free, faster than typing, more natural turn‑taking, better for brainstorming and “getting stuff down on a page" - **Trade‑offs:** potential for transcription errors and model input being less structured (a spoken “stream of consciousness" rather than an optimised prompt) ## Why Chat Will Stick Around (for now) Chat fits nicely with how we already work. **Teams and Slack** are already our first point of contact with many human colleagues today. This built-in comfort level, plus chat’s flexibility, make it the **default interface** for GenAI apps for the foreseeable future. > The future is agentic, but the entry point is still chat. ## Chat Is Not The Final Form Of AI Interaction, So What’s Next? We’re already seeing interfaces that go beyond the humble text box: - **Agents that act.** Models with **computer control** can literally *use your PC* for you. - **Multi-modal assistants.** Systems with access to camera and audio input that can “see”, explain, and guide users (see the latest [Samsung Galaxy ad](https://www.youtube.com/watch?v=rh7LhYT3jiI)). - **Native "AI-Based" Tools**. "AI Spreadsheets”, “AI Browsers”, “AI Whatever-You-Can-Think-Of" I’ll cover these patterns in more detail in this series of blogs. ## Summary: A Checklist For Building Better AI Chat UX 1. Show **3-5  starter prompts** in the empty state (DON’T just offer “Ask me anything”) 2. Add **use‑case chips** that reveal capabilities without overwhelming users 3. Offer structured **output modes** (bullet points, tables/CSVs, JSON) and easy **Export functionality** 4. Include memories (but make sure they are transparent and editable) 5. Use web/context **retrieval** for facts and prompt to avoid confident hallucinations where possible 6. Add **evaluation & retries** under the hood to raise reliability 7. Let users **name** and **manage** threads 8. Don’t use chat where it’s not the best interface. Eg use structured form inputs for set workflows --- ## Sources & further reading - TechCrunch, [ChatGPT hits 100M weekly active users (Nov 2023)](https://techcrunch.com/2023/11/06/openais-chatgpt-now-has-100-million-weekly-active-users/) - Reuters, [ChatGPT reached 100M MAU in \~2 months (Feb 2023)](https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/) - OpenAI, [Realtime API updates (production voice agents)](https://openai.com/index/introducing-gpt-realtime/) - Nielsen Norman Group, [Prompt suggestions reduce blank‑page anxiety](https://www.nngroup.com/articles/prompt-suggestions/) - Nielsen Norman Group, [Designing use‑case prompt suggestions](https://www.nngroup.com/articles/designing-use-case-prompt-suggestions/)