World Congress 2026 Europe Jul 10, 2026 Session details

Giving AI eyes: How to build a dashboard you can't see

Josh Hobson

Stop your LLM from generating broken, overlapping user interfaces. Learn how to build a client-side feedback loop that gives AI the spatial awareness to self-correct layout mistakes.

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#1 about 6 min

Understanding the challenge of dashboards generated by blind AI

Developers tolerate faulty code generation but end users abandon applications when AI visual output algorithmically fails.

#2 about 6 min

Improving spatial awareness and structural layout for generated widgets

Providing metrics like gridline attachment and center of mass helps AI automatically fix overlapping layout structures.

#3 about 4 min

Verifying analytical reality and preventing empty dashboard data states

Exposing domain context and active filter boundaries prevents language models from generating charts with missing data.

#4 about 7 min

Enforcing visual integrity and readable information density limits

Converting data points into client-side pixel density metrics prevents unreadable charts with excessively clustered data segments.

#5 about 2 min

Reducing expensive language model iteration cycles for end users

Creating client-side visual linting rules enables reliable one-shot dashboard generation without repetitive manual prompting execution loops.

#6 about 3 min

Integrating embedded dashboards and future browser based agent protocols

Embedded UI layout libraries avoid server-side dependencies while evolving alongside emerging intelligent web standards like WebMCP.

#7 about 3 min

Addressing audience questions on feedback mechanisms and browser integration

Fine-grained quality scores guide AI UI adjustments while a dedicated browser harness processes generation tasks locally.

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Transitioning from AI co-pilots to AI-native products

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Evaluating AI automated captions and dynamic interface generation

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