Coding and AI: Programmer Evolution.

Non technical people may not realize that every bit of software they use, each ‘app’, has it’s own life cycle. It’s called the software development life cycle, and we call it that because the focus is not on the software but on the business model that supports it.

There are some that argue that Agile programming has made the software development life cycle antiquated or even obsolete, but I believe that they have that wrong because Agile Programming is just a different approach to the software development life cycle.

Software is developed based on need, or expected need. It is planned based on requirements given by someone – generally the person who is funding the project – and developed and eventually maintained. Most software developers spend their time maintaining existing projects rather than creating that ‘killer app’ that just about every developer wishes to do.

Eventually, the software becomes obsolete for some reason, and generally speaking it means it’s making less money than it costs to support it. Free Software and Open Source software defy obsolescence because it’s generally about interest.

Artificial intelligence isn’t going to end life cycles, or programming. In fact, it’s just changing the face of programming because when you write a prompt, you’re really… programming. Programming has evolved from the lower level languages where we flipped ones and zeroes to increasingly higher level languages so that more people could program. Software development has constantly evolved and artificial intelligence is not that different.

What is kind of interesting is potentially being able to throw away some of these high level programming languages and replace them with lower level programming languages (that tend to be more efficient for a computing device to run) and just have a large language model write the code.

Regardless, people who write code will need to evolve. When I started out decades ago, a single person could write a game or application, then the needs became more complex and software development became increasingly social and multidisciplinary – and even specialized. Coders simply have to adapt again to writing better prompts – which also means better communication skills with those who want the code in the first place, as flawed as their requirements generally are.

Even as people write about the artificial intelligence life cycles, the core concepts aren’t different. In fact, for someone who has experience with software processes (not just one life cycle), it looks pretty much the same.

Identifying The End of the SDLC (2015)

Killer QueenDeath is not the opposite of life, but a part of it.Haruki Murakami

Software projects die. Call it retirement, ‘end’, whatever you wish – they die. In a perfect world, this is planned for – expected – understood. In the real world, many software projects were never established formally and have to be brought, kicking and screaming, to the table for hard decisions to be made.

Some software projects continue living out of some perverse masochistic need to keep them living – but they’re dead but for the efforts of those keeping them alive. Sometimes it’s necessary to admit that the software is beyond repair if only for a business to stop losing money and by that time a company is already deep in the quagmire in the project.

This, of course, is written mainly for businesses with software projects. Some are defined as software projects and some are not – I’ve encountered quite a few software projects over the decades that started off with the question, “Wouldn’t it be nice, if?”, and evolved based on that – a spiral model of requirements that doesn’t necessarily translate into a spiral model of development. While I have worked on successful projects and the world celebrates such successes, it’s the failures that create best practices and other rules of things-not-to-do.

A best practice should be planning for the end of the software life cycle throughout the life of a project – including planning the project. That’s part of any solid software development plan – a living document of a project. that exists in one form of another, be it in one person’s head or many people’s head. The latter creates the conflicts in a project that putting the document in written form so necessary. If this development plan doesn’t exist, identifying the end of the software project – it’s death – is almost impossible.

There are a lot of my fellow professionals out there who know about the software development life cycle to varying degrees of intimacy. In theory, we all want to begin things properly but we never discuss the end too much – and, oddly, the end is typically what employs the most software developers outside of relatively few software companies – the fact that when the software project was started no one planned for planning for it’s death. “Just one more change”, someone will say in consternation, “and we’ll move on to the next evolution because…. <insert your phrase of choice here>“.

It’s rarely blatant to management, and depending on what motivates the software developers, they may be immune to the pungent smell of necrosis if only for fear of not finding employment in a job market that is less than friendly.

For any technology to be sustainable, the economy surrounding it must be sustainable. Identifying the end of a software project requires attention to new technology adaptation both inside and outside of the user demographic as well as an actual interest in what the user demographic wants (will pay for) and needs (what it cannot do without).

The key to knowing when a project is dead is assessing whether the project will make more money than is being spent on it. I’ve worked on projects decades old that were still quite profitable and I’ve worked on projects a year old that were money pits – and a business that keeps throwing money into the money pit is unlikely to remain in business longer than their capital permits.

So how can you tell whether a software project is necrotic? There are a lot of very subjective things that have to be considered, such as the business direction and vision of the future as glimpsed by management – and they color the items listed below as well. In the end, it’s up to management.

There are also very, very simple things that will tell you whether it’s time to break out the candles for the project and will help assess whether any software project is in it’s death throes – or toxicly necrotic for the business.

  • Spending More On The Project Than It Brings In: While this is true of most startup software, the subjective aspects of vision and business direction overshadow it – and sometimes they continue to do so longer than they should. A software project should have a budget. Your company can fight over what is considered an expense and what is considered revenue (it’s not always cut and dry), but if you’re paying software developers more than the project is bringing in, someone should begin asking questions. Startups might be considered exempt but they shouldn’t be – at every iteration, this has to be looked at and with startups even more so than mature projects. Why? A misstep could be the end of it all.
  • Underlying Technologies Are No Longer Competitive/Supported: If you’re required to run a project under DOS or CPM, it may be time to pull the plug. If there’s a niche market, that’s nice. Just make sure that the niche market is paying your overhead and profit. Another example might be a lot of code that is not compliant with the latest and greatest strides in the language. I’ve seen PHP 4 code stuck on LAMP servers that belong in museums – running live on the Internet, where script kiddies are more than happy to show the willing that it’s time to move on with their probing.
  • The User Demographic Says So: Users are a peculiar group of people who don’t necessarily write long and detailed emails about what you’re doing wrong for them – in a world full of software options, it’s hubris to think that your company is so special that your users should invest themselves in your product. Social media makes getting feedback easier but tweets like, “your product sucks” just don’t give the granularity necessary to steer the project.

There are no silver bullets in here. Everything has to be considered within the context of the business and the key problem is that there’s a level of introspection required that wouldn’t have allowed the software project to get where it is now. It can be an uphill battle with those who make decisions since they may have seen how much they invested in the technology in the past as some form of wedding ring.

Image at top courtesy Louise Docker, who made the image available under this Creative Commons License.