When evaluating startups there are few key matrices
- financial stability - most notably runway. Taking funding and # of employees can give you a rough sense of things
- key people churn
- business traction graph - depending on the market you are in you can get some sense through similarweb and the likes
We took it to the next level at Yodas and provide detailed analysis. We help individuals make better, more informed career decisions.
In Yodas.com we've helped hundreds of developers to discover & connect with opportunities. Even though it's not PM roles we gained enough experience that I think would be helpful here.
I'm happy to jump on a call to learn more and give you honest feedback that would hopefully be helpful.
Hey Nir, late reply but: based on the names and (self?) descriptions of the startups I found it a bit of a downer to think of these being the hot new pre-unicorn wondercompanies. And the Crunchbase list, while a bit annoying with its upgrade hard-sell, has a lot more information that would be useful in figuring out what a company's about, where its money comes from, and how useful it might be for a serious hacker to ask them about jobs.
As to the Hyper-Yoda idea itself: I'm sure your selection is quite useful to some people -- junior developers? programmers having trouble finding jobs? the recently laid-off?
My only criticism of your site per se is that you use a lot of hand-wavy buzzwords while not showing a lot of useful data.
I'm happy to introduce you all to Yodas Hyper - a list of silicon valley startups that are about to grow fast.
Working with hundreds of fellow developers we discovered a common trend: There are many talented individuals with deep desire to make a significant impact but struggle with how to put their desires into action. A common theme is the openness to take a small risk for an exciting mission and take a meaningful role in the creation of something new.
Hyper is a list that get updated on a weekly basis with companies that match the following criteria:
- Raised Series A funding
- 25 employees or less
- Based in San Francisco Bay Area
I don't like the San Francisco-only bend. Your title is "Smart Career Bot for Developers," it doesn't mention anything about how location-specific it is (same with the name of this HN thread). Not everyone can relocate and there are plenty of hyper-growth startups worth promotion that are not in SV (Boston, New York, Austin, LA come to mind).
(1) "Solid Academic Background" is defined... how, precisely?
(2) And the predictive power of "solid academic background" with respect to "about to grow fast" is based on... what, precisely? (Other than something vague like: "everyone knows that solid academic credentials correlates with success").
1. Solid academic background is done by analyzing the team track record and experience together with the open source activity
2. We do not pretend to predict success.. Any company that appears on the list comply to three simple roles: raised large series A, below 25 employees and in SF bay area.
The tags are there as an additional analysis that each user can decide how to interpret.
Any way to look at other areas? The Bay Area is a decent place to find startups, but it's not a strong quality indicator. Or maybe it is! I'd still like to see the data on it, and I'd still like to see you consider anywhere else on earth in addition to the Bay Area regardless of the data.
Maybe a business query service would be a better fit, on further thought.
The relatively easy part is to find who recently raised money and we do it mostly through monitoring the press and limiting what we present only to companies that fit the criteria.
Behind the scenes we do much more complex stuff in order to evaluate the companies and a hint for that can be seen in the badges below the company description.
In essence, we built search engine that profiles companies in depth by looking at the companies website, github activity any anywhere we could find information about the founders, investors, team, product and even the code itself.
This is being developed mostly for our discovery engine - Yodas (www.yodas.com) and we benefit from it for Hyper.
Do you have a way to backtest the algorithm? Would be interesting to be able to verify accuracy without needing to wait 1-2 years (or whatever the time period meant by "about to go into hyper growth").
The reason I ask is I tend to be pretty cautious about these types of predictors of "business success" given that VCs nor research teams ("Good to Great" by Jim Collins) don't exactly have a strong track record.
An interesting test would be to make it time bound and run it on something like Clinkle circa late 2013.
