This is the presentation I gave in NYC at World IA Day 2016. It's about Conversational Architecture (using the metaphor of human conversation to describe contextual applications) and CAVE Language, the visual design language for Conversational Architecture.

1. CONVERSATIONAL
ARCHITECTURE
A WAY OF DESCRIBING CONTEXTUAL APPLICATIONS

2. WHO’S LOREN?
TECH GUY
FOUNDER AT AXILENT
MAKER OF ACE: THE
ADAPTIVE CONTEXT ENGINE
FORMER DIRECTOR OF
TECH AT HUGE AND AI

3. CONTEXT
IT’S WHAT’S FOR BREAKFAST, LUNCH AND DINNER.
Mobile Sensors
Location
Data
Social
Media
Context

4. NO LANGUAGE
HARD TO DISCUSS
PROBLEM SPACE
DECISIONS STUCK IN
DISCIPLINARY ROLES
HOLDS BACK PROGRESS

5. WE NEED A
METAPHOR
AN ABSTRACTION TO KICK
START THE CONVERSATION

6. Natural Language Conversation
Multi-directional
Multi-modal
Multi-channel

7. CONVERSATIONAL
ARCHITECTURE

8. CONVERSATIONAL
ARCHITECTURE
VISUAL
EXPRESSION

9. CAVE Language
CONVERSATIONAL ARCHITECTURE VISUAL EXPRESSION
Whiteboard / Napkin /
Presentation -friendly
Methodology Neutral
Scales Up / Down
Useful Across Disciplines
Data
Context
Modal
Response

10. Tablet User Article
Reading Habits
Location Data
User Periodically
Abandons Articles
Conditional
Reader
Reading at this
location from 8pm
to 11pm
Reader is
at Home
String of contiguous
locations from 7am to 8am
Reader is on
commuter train
Conditional
Reader
Reader is
at Home
!
Full Versions
of Articles
Conditional
Reader
Reader is on
commuter train
!
Abridged Versions
of Articles

11. DATA
WHAT DOES THE APPLICATION KNOW?
Device SensorData Data
Source
User
Input
Facebook “Likes”

12. CONTEXT
WHAT INFERENCES CAN THE APPLICATION MAKE?
✓ . .
Persona Affinity Goal Environment Sentiment
“PAGES” Analysis
User Reads
Articles
User Predominantly
Reads Business and
Magazine Sections
Category
Loyalist

13. MODAL RESPONSE
HOW WILL THE APPLICATION RESPOND, BASED ON ITS INFERRED KNOWLEDGE?
Rule Functionality Style Content Content
Policy
!
Sensitive to
Cold
Below 72
degrees
Raise to
72 degrees
Control implies
“warming”

14. EXAMPLE: PICK UP MILK
SINCE YOU’RE NEAR THE STORE, WHY NOT PICK UP MILK? YOU’RE ALMOST OUT.
Smart Phone Location Data
Smart Fridge
Fridge Inventory
Milk down to
10%, or is expired
You need milk
Within 300 ft of grocery
store, and you need milk
Alert: “You’re near the
store, and you need
milk. Pick up some now.”

15. EXAMPLE: FLASH SALE FOR JUST YOU
YOU’RE A BARGAIN HUNTER, YOU LIKE THESE SHOES, HERE’S 10% OFF JUST FOR YOU.
User sorts list
of products
Products sorted
by price: lowest
to highest
Persona:
Value Shopper
Store Inventory
System
Overstocked
Products
User views
product detail
page
Repeated viewings
of same product
User affinity
for product
A value shopper has
affinity for an
overstocked product
Flash Sale
on Product
Announce
flash sale
Exciting!

16. EXAMPLE: GET TO THE POINT
SOMETIMES YOU JUST WANT THE GIST, SOMETIMES YOU WANT THE FULL VERSION
Tablet User Article
Reading Habits
Location Data
User Periodically
Abandons Articles
Conditional
Reader
Reading at this
location from 8pm
to 11pm
Reader is
at Home
String of contiguous
locations from 7am to 8am
Reader is on
commuter train
Conditional
Reader
Reader is
at Home
!
Full Versions
of Articles
Conditional
Reader
Reader is on
commuter train
!
Abridged Versions
of Articles

17. CAVE-LANGUAGE.AXILENT.COM
@LORENDAVIE
LOREN@AXILENT.COM