Revert to Type: The Unexpected Rise of Text-First Interfaces

For decades, the trajectory of technology has been to make interactions more visual, more graphical, and seemingly more intuitive. From GUIs to touchscreens to voice interfaces, we’ve optimized for ease of use. And yet, there’s an unexpected countertrend emerging: text is becoming the interface of choice for some of the most advanced workflows.

At the same time, the cost of working with text—generating it, analyzing it, translating it, summarizing it—is collapsing toward zero. Large language models can now write functional code, generate detailed reports, extract insights, and automate complex tasks in seconds.

Counterintuitively, even as text-based work is increasingly automated, the value of text as an interface is on the rise.

The iPhone and the Cost of High-Fidelity Interfaces

The rise of the iPhone was largely due to a revolutionary user interface—rich, fluid, and intuitive. Early on, it was even skeuomorphic: ornamental design elements derived from real-world counterparts (the Notes app resembling a yellow notepad, or the Calendar app looking like a leather-bound desk calendar). This approach helps build a 'bridge' to new interfaces, making it easy for users to explore, understand, and interact intuitively. It also looks great.

This level of fidelity, however, comes at a high cost. Rich interfaces require significant design effort, engineering resources, and ongoing maintenance. But because the value is also high, great apps with polished, visually rich interfaces have thrived on the iPhone as a platform.

Contrast that with today’s new platforms—LLMs and AI-powered systems. For these, the need for high-fidelity graphical interfaces is dramatically lower, sometimes even superfluous. Their power comes not from glossy visuals but from raw functionality, flexibility, and intelligence. A well-crafted prompt can accomplish more than an elaborate UI, and systems like Claude Code and Amazon Q demonstrate that plain-text interactions can be remarkably effective.

Why Text as an Interface Works So Well

There’s a reason tools like Claude Code, Amazon Q, Warp, and terminal-based development environments are gaining traction: text is a powerful, flexible, and efficient medium for interaction. Consider the following benefits:

• Transparency & Inspectability – Text naturally preserves history. You can scroll back, see every step of reasoning, every command executed, and every output. No need for special debugging tools; the record is just there.
• Composability & Chaining – Unix popularized the idea that small, simple text-based commands can be strung together to perform sophisticated operations. Text-based AI tools are reviving that philosophy, making it easy to pipe the output of one process into another. Indeed, this is how most agents systems work.
• Ease of Iteration – Graphical interfaces often require clicking through layers of menus to make small changes. With text, making modifications is as simple as editing a line and rerunning a command.
• Rapid Development & Deployment – Building features in text interfaces is often faster and less resource-intensive than designing full graphical experiences. This agility is crucial for AI-assisted workflows, where iteration speed is key.
• Universal Compatibility – APIs, scripts, and automation tools all natively understand text. A text-based interface is inherently easier to integrate with other systems than a proprietary graphical one.
• Personalization & Adaptability – Rigid graphical interfaces tend to be polarizing—you either love them or hate them. Text-based interfaces, on the other hand, can dynamically adapt to user preferences. Whether you prefer more or less information, a terse or verbose style, or a structured or freeform layout, text can be customized in ways that fixed UI elements cannot.

Text-First Interfaces: A Time-Tested Approach

While this trend might seem novel, text-based expert systems have long been dominant in domains where speed, accuracy, and flexibility matter most. Consider:

• Vim & Command Line Tools – Developers have long preferred text-based environments for coding because they are fast, scriptable, and infinitely extensible.
• Airport Consoles – Airline employees rely on cryptic but powerful text-based reservation and scheduling systems to manage millions of passengers efficiently.
• Bloomberg Terminals – Financial professionals depend on dense, text-heavy interfaces to access real-time market data, execute trades, and analyze trends.
• Hotel & Banking Systems – Many backend systems in the hospitality and financial industries still prioritize text interfaces due to their speed, reliability, and structured workflows.

All of these examples demonstrate that when performance, transparency, and speed matter, text can provide a superior interface. Now, with AI making text manipulation nearly effortless, we are seeing a renaissance of these principles applied to a broader range of tools and use cases.

A New Design Language is Emerging

We are witnessing the rapid development of a new design paradigm—one that is text-heavy and function-first. Prompts are just the beginning. Expert AI systems like Claude and Q are moving beyond the simple chatbot model into minimalistic, structured text-based interfaces that prioritize clarity and efficiency over personality or aesthetics. Unlike the anthropomorphic approach of early AI, these tools are designed for precision, offering concise responses, deep insights, and structured outputs with minimal fluff.

This shift reflects a move away from designing interfaces for casual consumers toward interfaces built for power users who demand efficiency, transparency, and control. Instead of asking AI to mimic human conversation, these systems are being honed to function more like powerful Unix-style utilities—modular, predictable, and capable of being combined in creative ways.

The Discoverability Tradeoff: Why It Matters Less in Expert Systems

One of the biggest arguments in favor of graphical interfaces is discoverability—icons, menus, and tooltips guide users through what’s possible. With text-based systems, the concern is that users need to know what to type or ask for in order to unlock the system’s potential.

But in enterprise and expert contexts, this matters far less:

• Expectation of Training – Unlike consumer apps, where zero onboarding is the goal, expert systems assume a level of proficiency. Bloomberg terminals, hotel and airline reservation systems work because professionals are trained on them.
• Embedded Knowledge & AI Assistance – AI-infused text interfaces can provide inline suggestions, autocomplete, and adaptive prompts to help users discover functionality naturally over time.
• Efficiency Over Exploration – In expert settings, users often prioritize speed and precision over discovery. A financial analyst doesn’t want to browse; they want a fast path to the exact data they need.

This suggests that while text interfaces may feel "hidden" at first, they actually align well with environments where mastery, not casual exploration, is the priority.

The Economics of Text-First Interfaces: Faster, Cheaper, More Capabilities

One of the most overlooked advantages of text-based interfaces is their economic impact. Lowering the cost of delivering new capabilities doesn’t just make existing workflows more efficient—it fundamentally changes the rate at which innovation happens.

Lowering the Cost of Feature Delivery

• Traditional software development requires designing, testing, and maintaining complex graphical interfaces, which can be a bottleneck for shipping new features.
• Text-based systems, especially AI-driven ones, allow for rapid deployment of new commands, integrations, and workflows with minimal UI overhead.
• This means developers and enterprises can push new capabilities faster and at lower cost, without worrying about UI constraints or redesigns.

The Flywheel Effect of Faster Integration

• Because adding new features is cheaper, more features get built.
• Because more features get built, users demand (and expect) more integrations.
• Because integration is easier in a text-based paradigm, systems become more interconnected and composable.
• The result? An acceleration of innovation cycles, where new functionality is not just possible, but inevitable.

A Shift in Software Economics

• In the GUI era, software differentiation often came from how features were presented and designed.
• In a text-first paradigm, differentiation comes from what features exist and how seamlessly they integrate with other tools.
• The winners will be the platforms that enable rapid, frictionless innovation—where capabilities, not just UI, define competitive advantage.

This economic shift suggests that as text-based expert systems gain traction, we won’t just see more efficient workflows—we’ll see an explosion of new capabilities emerging faster than ever before.

The Future of Text-Based Interaction

We’re at an inflection point where interacting with computers via text isn’t just about writing prompts; it’s about treating text as the interface itself. The traditional terminal is being reimagined with AI-assisted workflows, and we’re seeing the resurgence of command-line-like efficiency in new contexts.

Rather than designing ever-more-complex visual experiences, we might find that the most powerful interfaces are the simplest ones—just words on a screen. And as AI continues to drive the cost of text manipulation toward zero, the strategic advantage will shift toward those who know how to harness text’s unique strengths.

The question isn’t whether text will replace graphical interfaces entirely—it won’t. But in an age where AI can work seamlessly with natural language, we may find that returning to text-based interactions gives us more control, clarity, and speed than we ever expected.

Epilogue & Notes

A few further thoughts.

1. The Future of Text-Based Interfaces: Dynamic UX on Demand

Right now, the shift toward text-based expert systems is driven by efficiency, transparency, and adaptability. But as AI advances, we may see an evolution where traditional UX isn't eliminated, it just becomes dynamically generated when needed. Instead of static apps with predefined user experiences, AI could generate tailored interfaces on demand, optimized for each task, user, or context. AI systems could infer your preferred level of detail, structure, and interactivity, delivering a UI that adapts in real time (I'm pretty certain this is the path Apple and others will take, building on SwiftUI and UIKit).

The paradox here is that while text-based interfaces may replace some traditional UI, AI may make UI more fluid and context-aware than ever before—rendering it precisely when and where it’s actually useful.

2. The Limits of Text-First UX: Where Visual Richness Still Wins

There are, of course, entire fields where text-first interaction simply isn’t enough, or where visual interfaces are not just useful, but necessary. It’s hard to imagine a text-first Photoshop where you type “increase contrast” instead of using sliders and tools. While AI is advancing in creative domains, visual interfaces remain essential for tasks like design, video editing, and animation.

Architecture, engineering, and game development rely on manipulating complex visual objects. AI might assist, but text alone won’t replace these workflows. Still other software isn’t about efficiency but discovery. Think of music production, video editing, or scientific visualization—fields where interaction and iteration are inherently non-linear.

I could also imagine a hybrid world: could we see a text-first Photoshop for expert users, where someone types “remove background, enhance shadows, sharpen edges” instead of manually adjusting layers? Maybe. I'm sure someone will try (and I'll be first in line).

:wq