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Exploring page 3 of our thoughts, tutorials, and insights about web development and technology.
Case study: extending Vector from chat-only to email replies, broadcasts, and delivery tracking in a single Thread-Based Engineering session. Real code, real architecture.
![Thread-Based Agentic Experience Engineering [TBE + AXD]](/_next/image?url=%2Fax-design-playbook-tbe-meets-axd.webp&w=1920&q=95)
The unified framework connecting Thread-Based Engineering to Agentic Experience Design. How thread autonomy levels map to trust patterns and supervision models.
How we use Radar, Vector, and Hive to monitor AI visibility across SEO, GEO, and LLM channels. Real GSC data and the 3-layer monitoring framework.
Radar by Pixelmojo runs 12 AI visibility tools in parallel, generates cross-tool insights, and produces AI-ready implementation prompts you paste into Claude, ChatGPT, or Cursor to fix every issue.
Task completion alone is a vanity metric for AI agents. The five-pillar AX metrics framework that separates agents users tolerate from agents users trust.
Too much anthropomorphism kills trust by 47%. A practical framework for AI agent personality, tone calibration, and voice design that builds trust.
![Conversation Flow Architecture [4 Design Layers]](/_next/image?url=%2Fax-design-playbook-conversation-flow.webp&w=1920&q=95)
LLMs lose 39% accuracy after 5 turns. Learn 4 conversation flow layers: state machines, context persistence, handoff topologies, and state recovery for production agents.
Only 6% of companies fully trust AI agents for core processes. This guide covers the six trust patterns, progressive autonomy, and recovery cycles that make agentic experiences trustworthy.
AX (Agentic Experience) Design is the discipline of designing interfaces where AI agents and humans share control. This guide covers the framework, patterns, and maturity model.
Showing posts 19-27 of 73 total posts