It has been a busy past year ideating, getting feedback, developing the Trumio platform, and getting ever closer to our initial release. A lot has happened in that timeframe, including the mainstreaming of AI into the public discussion and meaningful debates about the opportunities and challenges it presents. As we get ready to unveil our initial offering and value proposition, this is a mid-journey post (pun intended) on what we have learnt first-hand on the impact of AI. The bottom-line – the world is inexorably changing and new opportunities are emerging at multiple levels on how work gets done and who does it.
Using AI in our platform development
The best analogy for AI-assistance is that it is currently an aid to get you to your destination faster. Let’s say your preferred mode of transport for a planned journey is getting there by car. Existing AI can already help the car accelerate faster and maintain higher speeds (laws permitting), while also navigating around unexpected traffic by suggesting detours. However, for the foreseeable future, the driver at the wheel (the “human in the middle”) is a crucial element of doing this responsibly. Responsibility goes beyond the programmed promise of FSD (Full Self-Driving) – getting to a destination safely and comfortably with optimal efficiency. In software development, there are creative problem solving, quality, process, integration, team collaboration, and user expectations that cannot be captured and resolved through AI prompt engineering and automation. At least not yet.
Real use cases
As various stages of software product development get more efficient with AI assistance, there is no doubt that it will become easier to incorporate AI smarts into business flows. This will become as routine and impactful as Dev Ops tooling has been in the transition to Cloud. Even in the development phase, we are seeing benefits in semantically understanding requirements and automatically assessing the prioritization and impact of defects. All this while maintaining privacy of our own data, with adapted LLM’s analyzing our code and content. As we do this, we are also understanding how AI can better bridge the unstated wishes of product managers to the delivery from our development team and there are some interesting capabilities from this experience that is being built into our platform.
Younger drivers welcome
Any narrative on our journey will be incomplete without a shout out to university student interns who are developing key parts of our platform. They are working hand in hand with a talented set of developers at our technology partner. While they may publish their own internship stories, it is clear that their openness to learning and harnessing AI, becoming smarter with it, and creating pathways for even greater acceleration is ready to unleash an economic miracle. While our current experience is in software product development, we can very well see through our conversations with prospective clients, that this phenomenon will span functions and industries.
What this means for the future of work is that the next generation workforce can not only drive to the destination faster but also at a dramatically lower cost per mile, which is good for the environment and the bottom line. For some, they can now travel further and experience more within their current budget.
What’s not to like in this future?