It’s the eternal conundrum of a hiring manager – you have to hire for every single position in the company without any first-hand experience. How to do it? If you can have a trusted programmer sit in on the interview, that’s ideal, of course. But what if you’re hiring your first programmer? Or what if you’re hiring a freelancer? Or what if company policy dictates that you’re the only person allowed to do the interviewing? Well, in that case, you need some helpful advice and your innate bullshit detector. We questioned programmers and hiring managers and compiled a list of dos and don’ts. Here are some things to ask when interviewing programmers:

Past Experience

Ask the programmer about the biggest disaster of his career so far, and how he handled it. Did he come in at midnight to fix the code? Was he unaware of the problem until someone brought it up? Did someone else handle it?  According to our programmer sources, “Anyone worth their salt has caused a major meltdown. If they say they haven’t, they’re lying. Or very, very green.” Pushing a code with bugs in it isn’t necessarily bad. Not handling it well is bad.

As usual, your biggest asset is not knowing the field, it is knowing people. Asking about career disasters can be uncomfortable, but if the interviewee is experienced and honest then she won’t have a problem telling you about it, and you will get an idea of how she handles mishaps. Even if you don’t understand what the disaster was or how it was fixed, you should be able to tell how honest she’s being and how she handles being put on the spot.

No industry is as global as software development.  Pervasive networking means that software developers can, and do, work from anywhere. This has led many businesses to hiring development subcontractors in other countries, aiming to find good development talent at lower prices, or with fewer hassles on entry into the US.

While this is an ongoing and dynamic equilibrium, there are compelling reasons for doing software development in the United States, or using a hybrid model where some parts of the task are parceled out to foreign contractors and some are handled locally.

Development Methodologies

The primary reason for developing software overseas is cost reduction. The primary argument against overseas software development is slower development cycles. When software still used the "waterfall" industrial process for project management (where everything is budgeted in terms of time at the beginning of the project), offshoring was quite compelling. As more companies emulate Google and Facebook's process of "release early, update often, and refine from user feedback," an increasing premium has been put on software teams that are small enough to be agile (indeed, the development process is called Agile Development), and centralized enough, in terms of time zones, that collaborators can work together. This has made both Google and Facebook leaders in US-based software development, though they both still maintain teams of developers in other countries tasked with specific projects.

Localization For Americans

The United States is still one of the major markets for software development, and projects aimed at American customers needs to meet cultural norms. This applies to any country, not just the U.S. This puts a premium on software developers who aren't just fluent in English, but native speakers, and who understand American culture. While it's possible (and even likely) to make server-side software, and management utilities that can get by with terse, fractured English, anything that's enterprise-facing or consumer-facing requires more work on polish and presentation than is practical using outsourced developers. There is a reason why the leaders in software User Interface development are all US-based companies, and that's because consumer-focused design is still an overwhelming US advantage.

Ongoing Concerns

The primary concern for American software development is talent production. The US secondary education system produces a much smaller percentage of students with a solid math and engineering background, and while US universities lead the world in their computer science and engineering curricula, slightly under half of all of those graduates are from foreign countries, because American students don't take the course loads needed to succeed in them. Software development companies in the United States are deeply concerned about getting enough engineers and programmers out of the US university system. Some, such as Google, are trying to get programmers hooked on logical problem solving at a young age, with the Summer of Code programs. Others, like Microsoft, offer scholarships for computer science degrees.

Overall, the changes in project management methodologies mean that the US is the current leader in software development, and so long as the primary market for software remains English and American-centric, that's going to remain true. That trend is far from guaranteed, and in the world of software, things can change quickly.

Companies have been collecting and analyzing data forever, pretty much.” So what’s really new here? What’s driving the data-analytics revolution and what does it mean for those that choose to postpone or ignore the pivotal role big-data is currently having on productivity and competition globally?

General Electric chairman and CEO Jeff Immelt explains it best when stating that “industrial companies are now in the information business—whether they like it or not.”  Likewise, digital data is now everywhere, it’s in every industry, in every economy, in every organization and according to the McKinsey Global Institute (MGI), this topic might once have concerned only a few data geeks, but big data is now relevant for leaders across every sector as well as consumers of products and services.

In light of the new data-driven global landscape and rapid technological advances, the question for senior leaders in companies now is how to integrate new capabilities into their operations and strategies—and position themselves globally where analytics can influence entire industries. An interesting discussion with six of theses senior leaders is covered in MGI’s article, “How companies are using big data and analytics,” providing us with a glimpse into a real-time decision making processes.

The Zen of Python, by Tim Peters has been adopted by many as a model summary manual of python's philosophy.  Though these statements should be considered more as guideline and not mandatory rules, developers worldwide find the poem to be on a solid guiding ground.

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!