AI Moves Fast, But You Can't Stand Still

You have a problem to solve and a solution that would fix it… but in 6 months there will be a newer, faster, off-the-shelf approach, so what do you do? AI is evolving at a phenomenal pace, and adopting new tools and frameworks can often feel like chasing a moving target, but if you're always waiting for stability, you'll never move ahead.

Drawing on first-hand experiences we'll dive into the reality of working with cutting-edge tech, the dismay of building a solution only to find it quickly rendered "last-generation", and most importantly, why that's a healthy, beneficial thing!

We'll discuss the value of these encounters, the benefits of pioneering your own solutions, securing early stakeholder buy-in, and contributing back to the community. We'll touch on avoiding overcommitment, embracing refactoring, and the importance of documenting lessons learned. When it comes to AI, move fast, adapt faster.

This is a crucial yet rarely discussed topic, where obsolescence is seen as an opportunity for continuous learning and improvement. So whether you're an early adopter or a sceptical stakeholder, join me to explore why sometimes being ahead of the curve means embracing the inevitability of obsolescence - and finding success through suffering!

Shifting mindset to view obsolescence as a driver for learning and innovation, rather than a money pit. Bolder ambitions to try out new technology and techniques. Strategies to adopt new technology confidently while avoiding overcommitment and ensuring adaptability.