teddit

honest personal take (disclaimer: i'm not an ML expert, i just study and use a lot of social apps):

i think its highly unimaginative and tired to tell new users on a social platform to "reply a lot" in order to get any engagement.

social platforms, for a long time, pinned discovery as a user problem. tiktok changed that. they didn't expect users to earn attention the hard way (hustling to self-promote and get follows).

instead tiktok took on discovery as a platform problem and decoupled distribution from follower count entirely: a content-first, graph-agnostic approach.

on tiktok, a user's responsibility is to make good content and the algo would do the rest based micro interactions and watch behavior. YouTube took a similar approach, but favored creators who mastered their (effort intensive) rules: SEO knowledge, thumbnails, content cadence, etc.

if we're hearing that discovery is a problem, the question should be: whose problem — the user's or the platform's?

take long-form text platform substack: the recommender engine places more of the burden on the platform than the user, and the platform bias is towards quality via a trust graph.

it recommends newsletters based on what you read, introduces editorial curation, and the "recommended by other writers" feature means that small / new writers can get regularly recommended to audiences that a specific writer's taste.

each platform makes a design choice about who should work to be seen. on substack, they believe that good writers should be lifted through network effects and curation.

does this scale easily? no, it scales slowly but is compounding.

so why is this so hard for short-form text-based platforms like twitter, threads, bluesky, or farcaster?

because short-form text is typically low-signal, high-noise. short posts on their own carry very little context or signal. it's easier to produce, but harder to evaluate. as a result, discovery for short-form text platform has relied heavily on follower graphs. 

twitter initially solved this with hashtags (then failed to do it at scale with lists, fleets, and circle). substack partially solved this with its writer graph (trust graph) and categories (topic / semantic clustering).

and i think farcaster's open data, mini apps, and interoperability (zkTLS) can be leveraged for creative solutions here that aren't possible on other platforms. that excites me.

Is this the user’s fault or the platform’s fault?

Excellent question by @ted. Should be asked in many situations, not just this one. Because sometimes it’s user error, sometimes it’s platform error, and sometimes it’s both.

building farcaster | surfing @ venice, ca | eating @ gjusta / gjelina | “lucky me, lucky mud” 🤠

Author of The Network State.
Work with me: jobs.ns.com

Totally agree —
but blaming the user
is seldom a successful
growth strategy.

More useful than asking
who’s at fault
is asking:

what was the default
that shaped the behavior?

Because
the default
is the fault.

And defaults
are design decisions.

Twitter’s default
is short, acerbic takes.

Instagram’s default
is everyday beauty
and images.

Facebook’s default
is the long, winded
status post.

TikTok’s default
is a vibe-driven,
moving, loop-able loop.
(not woo woo vibe 
talkin but mood as 
atunement, i.e., 
stimmung
as medium) 

Farcaster
doesn’t need
a copycat default
with better 
decentralized 
permissionless infra
(open data graph,
mini apps,
ZK credentials)

Farcaster needs
its own default
form and fram
for content. 
A new
paradigmatic frame
and form of content. 

What if that default
The Farcast were 
a front-facing,
thoughtful,
peripatetic
video? 

(Farcaster 
could do this with 
a few simple features
and design choices:
a video reply button
and auto-captioning 
feature—the captions 
could be distinctive 
purple kareoke captions
so when they’re
shared on other plafroms
others will learn to recognize
the captions as the mark of 
farsighted thinking) 

Not selfie sermons
but situated speech.
Not dunks 
but dialogue.
Not content 
but communication.
Not static 
but in motion.

A “Farcast”
could be part forecast,
part broadcast.

A vessel
for thinking aloud.

For meaning
that is embodied,
not outsourced.

A new civic form 
of communication 
suitable for 
denizens of
network states! 

Farcast (noun):
A front-facing container
for  authentic 
human expression 
and communication.

For embodied 
meaning
situated in time 
and place 
through a person’s
voice,
face,
and body.

Non-robotic.
Non-algorithmic.
Not generated
by artificial 
intelligence 
but by human
intelligence.