Hashable is a tool to keep track of new people you meet in the real-world and see who your friends are meeting. Typing in the Twitter handle of a newly-aquainted contact in the iPhone or Android app will generate a #justmet tweet mentioning both parties. Connecting in this fashion is more useful than simply exchanging business cards; both parties are exposed to inherent social pressure (the tweet is public) and have an incentive to continue the relationship.

During the presentation, attendees were exposed to a candid history of Hashable and how the team developed the app over the past year. There were a number of actionable takeaways that other startups can utilize in the development of their products:

Iterate on early product concepts with small test batches

Before Hashable had a definitive product roadmap, the team would release simple prototypes to small groups of 20 people. Each release was given to a unique set of testers and engagement on the prototype was scrutinized in excruciating detail.

With an extremely constrained sample size, the team could quickly determine if they were onto something based on the active usage of just a few people. The team experimented for a few months before landing upon the #justmet concept.

“Nerdy” input methods are confusing for many users

In the early versions of Hashable, users could only make connections through specific #hashtag tweet syntax on Twitter. While it was a neat trick for power Twitter users, the command-line input method was complex and intimidating for many people. Hashable remedied this issue by providing web and (more recently) iPhone and Android apps for connection inputs.

Don’t always assume that the cool or unique way to interface with your app will work for everyone… simplify the process for non-early adopters.

Target key influencers in a calculated and strategic fashion

The Hashable team, like many other startups, created a list of the top influencers in the startup community: VCs, angel investors, popular startup co-founders, etc. Hashable went further, segmenting individuals into categories and adding lesser-known influentials to their lists. They generated a list that included more than the typical “elite” of Silicon Valley.

With an extensive list in hand, Hashable hustled to get the top-tier influencers signed up for the app. They were not as concerned with the level of activity of these users; Hashable wanted the “big names” in place for when they invited everybody else.

Getting “name-worthly” people in your system, even if they are light users of the app, can immensely help with the credibility of your startup and your brand.

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Hashable is looking to rock #SXSW this year; feel free to #justmet the Keepstream team if you meet us in person. Check out tweets from the Austin #HashyHour in the Keepstream collection below.

Digg 1.0
It’s a barebones site with the core functionality and nothing more. Reminds me of Hacker News in some ways.

Digg v 1.0 - click to expand

Digg 2.0
Now we start to see some familiar elements. Good ‘ol Helvetica. Yellow digg count boxes. Timestamps.

Digg v 2.0 - click to expand

Digg 2.1
The blue top bar appears. Digg pretends the Digg Spy is new even though it’s been around for over a year haha.

Digg v 2.1 - click to expand

Digg 3.0
Digg places categories at the top. They also put focus on two key features: the ability to filter by time (24 hours, 7 days, 30 days, etc.) and the ability to quickly bury a story.

Digg v 3.0 - click to expand

Digg 3.1
Digg adds the media types to the top nav (news, video, images, podcasts). The site has so much traffic and quantity of stories now, so they add Upcoming to show stories that aren’t the most popular but are quickly trending upward.

Digg v 3.1 - click to expand

Digg 3.2
I’m guessing Digg realized more clicks get driven through categories, so they make that the bigger, more prominent nav element. And search gets labelled as new even though it’s been around forever. Maybe they update the results page or the algorithm.

Digg v 3.2 - click to expand

Digg 4.0
Digg hits the big four zero and like the rest of us, has a mid-life crisis. I do enjoy the cleaner look though.

Digg v 4.0 - click to expand

And so that’s the story of Digg as told by their user interface. I think what I find so interesting is that Digg was iterated over the course of 6 years. Digg had to deal with a lot of scaling and behind-the-scenes work, but I feel like many startups these days build similar feature sets much more rapidly. Maybe I’m just delusional. Or maybe today’s improved programming tools and APIs are making a huge difference.

What do are your thoughts on Digg’s evolution?