Illustration of a glasswing butterfly with transparent wings over a dark grid, evoking the Project Glasswing security theme
Industry News May 20, 2026 7 min read

Project Glasswing Is a Cybersecurity Story. A Conversation Designer Reads It Differently.

Project Glasswing is a new Anthropic-led effort, with partners like Amazon, Google, Microsoft, and JPMorganChase, to secure critical software using Claude Mythos Preview, a model that finds software flaws better than almost any human. Most coverage will focus on the hacking. This opinion piece reads it through a conversation designer's eyes: the names, the framing, and what it means for any business whose AI talks to customers.

The Conversation Design Skills Gap: Why AI Teams Are Hiring Linguists
Industry Trends April 22, 2026 10 min read

The Conversation Design Skills Gap: Why AI Teams Are Hiring Linguists

AI teams at enterprise companies are quietly adding linguists, conversation designers, and AI content strategists to their rosters. Engineering teams alone cannot build conversational AI that works. Language expertise is now table stakes for enterprise AI. The skills gap is widening because most computer science programs do not teach pragmatics, discourse design, or conversational repair.

The 5 Conversational Patterns That Make Users Rage-Quit Your Chatbot
Conversational AI April 11, 2026 9 min read

The 5 Conversational Patterns That Make Users Rage-Quit Your Chatbot

Five conversational patterns cause users to rage-quit chatbots: the dead-end response (no path forward), false confidence (sounds sure but wrong), context blindness (forgets what was said two turns ago), hostile politeness (over-formal refusals), and circular escalation (asks for the same info repeatedly). Each pattern shows up in support data and is fixable in conversation design, not in the model.

Conversational AI April 1, 2026 8 min read

Designing for the Moment AI Gets It Wrong: A Conversation Designer's Guide

Every AI chatbot will get something wrong. The real question is what happens next. Three failure types need explicit design: misunderstanding (the AI parsed the input wrong), low confidence (the AI is not sure of the answer), and out-of-scope (the AI cannot help with this kind of request at all). Each failure type has a different recovery pattern. Trust depends on getting these right.

CX Strategy April 1, 2026 7 min read

"But ChatGPT Can Already Do This." How to Make the Case for Conversation Design.

When a leader asks why you need conversation design when ChatGPT can already handle conversations, here is the answer. ChatGPT can hold a conversation. It cannot reliably represent your brand, follow your policies, escalate at the right moment, or handle the customer questions you actually get. Conversation design fills that gap. The 'works' bar and the 'works well' bar are far apart in production.

Tool Reviews March 18, 2026 6 min read

How Gamma Is Changing the Way Consultants Build Deliverables

Gamma is an AI-powered presentation tool that lets consultants generate decks, one-pagers, and reports from a prompt or outline. The tool changes the economics of consulting deliverables: hours of layout and formatting work compress into minutes. Gamma works best for strategy documents, workshop materials, and pitch decks where structure matters more than custom design. It struggles with highly visual or chart-heavy work.

Tool Reviews February 19, 2026 6 min read

How to Choose an AI Customer Support Platform in 2026

Choosing an AI customer support platform in 2026 means evaluating seven criteria, not feature lists: conversation design support, prompt customization depth, integration with your existing stack, analytics and observability, escalation design, multi-language support, and pricing model. The wrong platform will work in the demo and fail in production. The right one matches your use case, not the vendor's pitch.

Industry Trends January 8, 2026 5 min read

Chatbot vs. Conversational AI: What Enterprise Leaders Need to Know

A chatbot is a rule-based system that matches keywords to scripted responses. Conversational AI uses natural language processing, large language models, and machine learning to understand intent, maintain context across multi-turn dialogs, and generate dynamic responses. Most enterprise chatbot projects fail because teams confuse the two and choose the wrong technology for the use case.

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