Tuesday, June 6th, 2023
Embracing the Evolution of Software Engineering in the Age of AI
Artificial Intelligence is evolving at a breakneck pace and here at EXIT83, we’re enjoying the thrill ride and exploring ways to create new opportunities for our business and our clients. It feels like literally every day I’m seeing new tools and use cases for AI emerge in our Twitter feeds. The impact of AI on our lives is already profound—and obviously, there real implications for what’s ahead for folks in our lines of work.
The race to adopt AI is on. Will you be left behind?
AI's ability to automate processes, generate insights, and learn from vast amounts of data has led to a significant decrease in the time and resources required to develop software—accelerating the commoditization of software engineering services. Take this quote from Nvidia’s CEO, Jensen Huang.
The world now realizes that maybe human language is a perfectly good computer programming language, and that we've democratized computer programming for everyone, almost anyone who could explain in human language a particular task to be performed.
We’re predicting an inflection point where everyone will have the same technology at their disposal, setting off a “race to the bottom” for software service delivery. The value of software will plummet, engineering services value will plateau, and then both will follow roughly the same downward trend:
Conceptual chart of predicted changes in value for software engineering and products over time.
While it's impossible to know exactly when this inflection point will occur, I’m expecting we’ll see it sooner than later; maybe in a matter of months rather than years. There’s no time to lose in incorporating AI tools into our work.
Putting AI tools to work at EXIT83
EXIT83 is already using AI to accelerate our engineering in ways that don’t require us to send any client data to AI tools, including:
- Paired programming in ChatGPT
- GitHub Co-Pilot for each dev
- Using LangChain to build a bot for internal repos
- Automated creation of unit tests through GitHub actions
- Basic threat modeling
- Experimentation with agents like AutoGPT to optimize source code
As expected, the time we need for developing and deploying code has decreased: we’re much faster to build proof of concepts and have accelerated the training experience for engineers learning a new programming language.
We’re also pushing the edge and experimenting with dummy data that doesn’t touch any of our client work, for the sole purpose of exploring the possibilities of everything AI might do for our business.
We’re working to build knowledge and skills as fast as we can but taking the practical application a little bit slower. Responsible use of AI tools requires commitment high standards of security and ethics, so we are proceeding with caution and transparency.
Adapting to the New Era of Software Consulting
Because AI tools can make engineering so much faster and easier, it’s going to be increasingly difficult for companies like ours to differentiate themselves and maintain a competitive edge. Our value will rely more on our ability to:
- Focus on solving real-world, strategic business problems for our clients
- Build strong client relationships foundation in trust, transparency, and integrity
- Foster a culture of innovation and creative problem-solving to go beyond the bounds of traditional software development
- Celebrate experimentation and the yearn for new technology.
- Provide an engineering environment where everyone feels empowered to voice their opinion
AI will be a powerful tool but never a replacement for our software engineers. At the end of the day, if we remain true to the needs of our clients, continue to hold ourselves to the highest standards of integrity, data stewardship and ethical business practice, and encourage creativity and innovation, I’m certain we’ll continue to thrive in this brave new world.