At Altitude NYC, noted writer and programmer Paul Ford of Postlight some of the reasons behind two decades of "weird media/tech battles," and some of the challenges faced by modern publishers.

1. Why we fight
PAUL FORD
Or; Two decades of weird media/tech battles

2. PageFastly Living through the history glut with style 2

3. Paternal aphorisms

4. PageFastly Weird media battles!
Frank Ford’s wisdom
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• “A program is like a poem.”
• “A man should have a vocation
and an avocation.”*
• “Laughing ends up in crying.”
* (Actually Andrew Peabody at Harvard in the early 1800s)

5. “Baked” vs. “Fried”

6. PageFastly Weird media battles!
Baked
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July 2000, from Ian Kellan, then of Salon.com:
“Baking”
This is the publish time commitment of data to a
file (or a more efficient cache, if you have one).
Editorial narrative, headlines, datelines and other
pieces of editorial/business data that doesn't
change can and should be pre-calculated in
advance.

7. PageFastly Weird media battles!
Baked or fried?
7
"Frying”
This is the request time processing of data for
the final presentation. Stylesheet assignment,
session start/finish accounting, ad placements
and other things that actually may change on a
per request basis are handled by the HTTP
delivery engine.

8. Why is everyone fighting?

9. Blogging vs. Journalism

13. Content vs. Community

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15. Free vs. Paywall

17. Publishers vs. Ad Networks

18. © LUMA Partners LLC 2017
Performance
Video / Rich Media
Targeted Networks / AMPs
Horizontal
Vertical / Custom
Mobile
ExchangesDSPs
Publisher
Tools
Data Suppliers
Ad Servers
DMPs and Data
Aggregators
Measurement
and Analytics
Creative
Optimization
Agency
Trading Desks
Ad Networks
Media Planning
and Attribution
Verification /
Privacy
Ad Servers
Retargeting
Media Mgmt Systems and Operations
Sharing Data /
Social Tools
SSPs
DISPLAY LUMAscape
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Tag Mgmt
Agencies
Denotes acquired company Denotes shuttered company

19. Performance
Targeted Networks / AMPs
Vertical / Custom
Publisher
Tools
Ad Servers
DMPs and Data
Aggregators
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Wordpress
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Drupal
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Joomla
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23. Blockbuster vs. Long Tail

24. $

25. News vs. Archives

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400 years!
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~1605: Relation aller Fürnemmen
und gedenckwürdigen Historien
(Account of all distinguished and
commemorable news)
~2005: Online archives become
feasible. New Yorker, Harper’s,
Playboy, Times Machine.

27. PageFastly Weird media battles!
News always caches
DEFINITION
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28. PageFastly Weird media battles!
Archive fun facts!
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A woman named Marion Stokes
recorded 140,000 VHS tapes of local
and national news from 1977 to her
death in 2012.

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Archive fun facts!
29
Mozart has 796,628 followers on
Spotify (and Spotify has 50 million
paying users).

30. PageFastly Weird media battles!
Archive fun facts!
30
DP.LA (the digital public library of
America) has 15,499,687 items from
all over.

31. PageFastly Weird media battles!
Archive fun facts!
31
Archive.org has 11,529,270 books,
3.2 million videos, roughly the same
amount of audio. Also: 284 billion
web pages.

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In total…
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Billions of scanned pages, millions of
hours of recorded media.

33. PageFastly Weird media battles!
Who has monetized the past?
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Ancestry—because humans want to know about
our own families and how we came to be
Spotify—because people like to listen to music
from different time periods, and music is relatively
timelines.
Kindle—because books were already nice
discrete units and hold up pretty well over time.
Bloomberg—even though past performance
doesn’t predict future results

34. …Everything vs. Social

36. Documents vs. Apps
Editorial vs. Experience

37. vs.

38. vs.

39. vs.

40. New York vs. San Francisco

41. The big question:
how does your writing influence your coding?
How does your coding influence your writing?

42. Creative interpretation
vs.
Creative automation

43. Workflow
vs.
Databases

44. News vs. Fake News

45. Machine learning
DSPs
Really long schedules
Big data
Surprising discoveries
Everything very expensiveVenture Capital
Recurring schedules
Unicorns
Everything
a feed
Liquidity events
Incremental audience growth
Consumer marketing
Great distribution
Too many interns
Going not-for-profit?
An audience is an audience!
High-value viewers
Long hours!
Never stop working
Editors
CEOs
Breaking news
Getting fired
Cashing out
Consumer analytics platform
Long-form vertical
Rich 30-year-olds
Home page editors

46. Descent into punditry

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Machine learning blah blah blah blah
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There should be some bullets here about the future
Maybe a picture of someone in a VR helmet
Or something about augmented reality
Bring back all the stuff about archives from before
and explain how there is some opportunity here to
get ahead of the curve and start thinking about the
kind of data-informed experiences that people are
going to want as augmented reality finds its way into
more things and become more profitable.
blah blah blah blah blah blah word
vectors tensor flow self-driving cars
blah blah blah blah media experiences
blah blah blah blah data mining
augmented reality archives blah blah
blah blah archives as big data creating
new experiences blah blah blah blah
automatically-generated media
experiences blah blah blah blah virtual
reality blah blah blah blah blah blah
blah blah blah blah word vectors tensor
flow self-driving cars blah blah blah
blah media experiences blah blah blah
blah data mining archives blah blah
blah blah archives as big data creating

48. Vocation vs. Avocation

49. PageFastly Weird media battles!
Stop fighting
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There will always be these tensions.
We’ll be okay as long as no one
wins.

50. Thank you
Paul Ford
paul.ford@postlight.com