AI: the silver bullet to stop Technical Debt from sucking you dry
You’ve heard a lot about student debt, but what about technical debt?
--
It’s Friday evening in the Bahamas. You’re relaxing under a striped red umbrella with a succulent glass of wine and your favorite book — it’s a great read and you love the way the ocean breeze moves the pages like leaves on a tree. As the sun descends your eyes follow, your consciousness drifting with the waves, closer to the horizon, closer to a soft, lulling sleep, closer to a perfect evening in a perfect world.
And then your phone rings. It’s your boss. The production system is down. One of the marketing guys brought in a big haul, but your code wasn’t built to hold its ground against this many users. Before you can scream in agony, a small demolition crew brings down your umbrella, a seagull swoops away your wine, your book dissolves into sand, and you’ve got an economy ticket on a United flight back to work — boarding closes at 1AM, don’t be late.
As you sigh and start your trek across the now coarse, itchy sand, you can’t help but wish you spent an extra couple of hours writing the login system a few months ago; a couple hours of choosing the efficient, extensible solution, the solution that would have saved your dream vacation.
You’ve just become the latest victim of Technical Debt.
Technical Debt — The Phantom Menace
What exactly is technical debt? Well to put it simply, every time you choose the quick & easy solution over a scalable, efficient alternative, you accumulate technical debt. More formally, according to Techopedia:
Technical debt is a concept in programming that reflects the extra development work that arises when code that is easy to implement in the short run is used instead of applying the best overall solution.
If it sounds bad, that’s because it is. Technical debt is one of the largest and most impactful issues affecting software development today.
It has become an issue large enough to cripple companies, destroy successful products, and cost billions of dollars each year. A joint report published by Stripe, Evans Data Corp, and CIA Factbook estimates that developers waste 13.5 hours each week just dealing with technical debt — for those of you counting, that’s around a third of their working time.
That adds up along with time lost to debugging, refactoring, and other tasks related to code management, to a sum of around 30 hours of the workweek (75%), with an annual loss surmounting to $85 BILLION DOLLARS.
To put that in perspective, that’s 85 billion donuts worth of loss.
Of course, this is no secret. The majority opinion remains that developers spend too much time dealing with bad code:
This wastes precious hours, and precious money. Unfortunately, technical debt is usually also not included in budgeting.
As a result, several projects are sucked dry by this vampire-like burden:
At Crane, we know the struggle of technical debt all too well. After working on several projects, it became evident to us that a solution to this growing problem was needed. And so, we set out to create a new platform for developing applications, one that eliminates technical debt — one that integrates and implements artificial intelligence.
Why AI?
The issue with technical debt is one that is enormously complex, and it was evident to us that the only solution was to design a new platform for development that would work to eliminate this.
However, there are inherently many challenges faced when trying to eliminate technical debt. You can read more about our discovery process and how we handled these challenges here:
https://medium.com/craneai/behind-crane-fe13c0415544
It became clear to us very quickly that solving these unique challenges required the use of Artificial Intelligence. We’ve managed to embed AI into our application to provide the ideal development experience, handling everything from frontend view generation to backend scaffolding and AI-powered project management.
We strongly believe that artificial intelligence will play a vital role in eliminating technical debt, and the future of software development. The majority of time spent with bad code and running maintenance is attributed to tedious tasks like refactoring, upgrading, and migrations. By analyzing the codebase as well as the project with artificial intelligence, it becomes possible to automate these tasks and alleviate the burden on the developer, saving thousands of hours and billions of dollars.
It’s not surprising that the future of software development involves Artificial Intelligence. In fact, this too is an industry majority opinion:
Investment in cloud technologies, mobile apps, and artificial intelligence is also very much on the rise:
Sitting at the intersection of these three industries, Crane is poised to solve the issue of technical debt and combine leading technologies to develop the first AI-powered development suite.
Conclusion — The Future of SoftwareThe Future of Software
As software development evolves it’s evident that we are heading towards a stronger, more robust and far more efficient future. While the industry grows more issues and challenges will appear, and it’s clear artificial intelligence will rise to solve them.
We’ve got high hopes for the future. A future far more efficient and painless than the present, one guided by AI — and most importantly, one without the burden of technical debt
Hey! I’m Tomer, an entrepreneur, and maker. You might know me from Mevee, Crane, Shots, Slides and now investorintelligence.io among other products I’ve launched! This article is a part of a more extensive series I’m writing mostly based on my experiences and is mainly made of me and my team’s opinions.
I hope this helps you to avoid making the same mistakes I did, and remember to keep shipping!
Please clap 👏 if you found this valuable, and follow me 👈 for more writing like this as I share stories about what software development and entrepreneurship looks like in real life.
