How does the "AI" interpret this repo:<p><a href="https://github.com/EnterpriseQualityCoding/FizzBuzzEnterpriseEdition" rel="nofollow">https://github.com/EnterpriseQualityCoding/FizzBuzzEnterpris...</a><p>It's near perfect idiomatic java. But does the dev solve any actual problem? More generally, how can you really evaluate a code project by parsing it line by line for syntax and style best practices? I think this algo would select the essays with the best handwriting, not the best ideas.
> <i>Once a candidate links their online portfolios and projects—usually Github repositories—to Gradberry, the platform analyzes whether or not a candidate has written good-quality code.</i><p>Tell me one human being that can read someone else's code and determine whether it's "written good-quality code" and I'll have you a queue of companies that want to use you as a recruiter. AI instructions are created by humans. If a human can't determine the rules for "quality", then how is an AI going to do it?
Not sure about the approach to take a look in public code.<p>Students and graduates may still not developed good coding skills, assuming they have the time and energy to contribute to open source (they probably should as a pure marketing tool, though)
People with experience may not have their code available. Not every company works with open source.<p>It seems to be quite biased to certain kind of developer. I agree is a good kind of developer, but if the objective is to find "the best", it could be a relatively small talent pool.
Their number one tip is "Good profile pictures matter", so welcome back to prejudice land (I'm registering anyways, I'm a white dude, it shouldn't hurt me).<p><a href="https://gradberry.com/getting-started-candidates/" rel="nofollow">https://gradberry.com/getting-started-candidates/</a>
A a Latino programmer, I must say it's never been easier to get a job. From this angle, there's something even beyond a meritocracy.<p>However, if one wants to raise money(some VCs) or get a finance job, most are biased towards a certain stereotype(skills not as blatant) and that's where the real prejudice exists.
This company may be missing an opportunity to market this product to the industry that may benefit the most - agency recruiting (aka headhunters).<p>Most recruiters don't have the ability to evaluate code, so when they are representing candidates to their clients they are relying on a host of other indicators and data in order to try and gauge the coding ability of their candidates.<p>This product is a way for recruiters to vet the code of their candidates, and could then pass along those results ("Gradberry score of n") to their client as a value-add that other recruiters not using the system can't provide. A somewhat similar concept to recruiters years ago who asked candidates to take skills tests from places like Brainbench.<p>For the right price, I imagine recruiters would be interested in this as a differentiator between themselves and other firms. Gradberry would also still benefit from the feedback data if recruiters reported their results.
> According to Reuters, an overwhelming majority of the startups it looked at were founded by people who had held a senior position at a big technology firm, worked at a well-connected smaller one, started a successful company, or attended one of three universities—Stanford, Harvard, and Massachusetts Institute of Technology<p>Did they ever stop to think that maybe people who are talented and interested in starting their own tech startup business might seek out these schools and positions, disproportionately to other options?<p>You can't point at facts like these and claim they are proof for a lack of diversity. It might turn out that, given the chance to evaluate and interview every possible candidate in the world, that the top 1% of talent might be 80% drawn from those backgrounds, irrespective of all other traits.
So I'll only be considered a good programmer if I work on github?
Way to replace one broken method with another equally limited view of candidates.
Coding is only a small part of the equation.<p>Better architecture / data modeling (often) leads to less code.<p>Working out the problem that actually needs to be solved will likely lead to a better architecture.
Is anyone else driven nuts by how hard it is to get at the data behind so many articles?<p>For instance, the bit about how it's important to have attended one of three universities - "Stanford, MIT, or Harvard", made me wonder what kind of disadvantage you are at if you attend a very strong but public CS program (Berkeley, University of Washington, Illinois).<p>The article has a link to the reuter's analysis here:<p><a href="http://www.reuters.com/article/2013/09/12/us-usa-startup-connections-insight-idUSBRE98B15U20130912" rel="nofollow">http://www.reuters.com/article/2013/09/12/us-usa-startup-con...</a><p>Which includes a link to a graph (I'm thinking, ok, great, here's the data!)<p><a href="http://www.reuters.com/subjects/series-a" rel="nofollow">http://www.reuters.com/subjects/series-a</a><p>If you hover over some of the dots on the "unconnected" companies, you can see a few of the other universities attended. So it does appear that yes, attending Berkeley or other top public CS programs does put you at a significant disadvantage where it comes to getting series A funding [1], though this was as far as I could get. Maybe I'm bad at web searching, but I just couldn't find the raw data.<p>You know, as an aside… ycombinator set up an amazing series of talks from founders and CEOs for a truly exceptional class at stanford (<a href="https://news.ycombinator.com/item?id=8325479" rel="nofollow">https://news.ycombinator.com/item?id=8325479</a>). There was a posting about it on HN a while back, and they did make the videos available… but there's nothing like actually being there, possibly with the opportunity to meet a high up in person.<p>There were a few objections, some down-modded (for a variety of reasons), about possible class issues here. I would say this: there's a reasonably good CS program across the bay at a university that enrolls more low income students than the entire ivy league combined. If middle and low income students appear to be having more trouble becoming founders and getting funding (as opposed to becoming high value employees for those who get series A funding), this might also be a great location for another round of this course.<p>[1] this is highly relevant, since students from top public CS programs don't appear to have significantly lower mid-career salaries as <i>workers</i> (in fact, worker bee salaries may be slightly higher out of Berkeley).<p>Also I may have made a correlation causation error. Could be that the university itself has little to do with this.
<i>Silicon Valley really, really wants to be a meritocracy.</i><p>Nope. It really doesn't. It wants to be <i>perceived as</i> a meritocracy. That's a different goal entirely. It's the same privileged, well-connected "MBA culture", but in the 21st century, MBA stands for "Meritocracy By Assertion".<p>VC doesn't want <i>not</i> to be a clubby, relationship-based business, because who-you-know cultures are great at giving the well-connected an extortive power that they wouldn't otherwise have. ("Those who question the meritocracy will be de-meritized.") Sure, there are Silicon Valley <i>engineers</i> who want to live in (and believe in) meritocracy, but they're not the people with the power. You can get an employee position on merit, but if you want to ascend to the founder or investor ranks and get real equity in the Valley... you still have to be a child of the old empire.<p>It was hard to read the rest of this article after this critical miss.