The Evolution of the Developer Role in the Age of AI and Hybrid Cloud

Written by: Briana Frank , Vice President of Product & Design for IBM Cloud

While some see AI as a threat to jobs, at IBM, we view AI as an enabler for the workforce – increasing productivity and driving innovation across all industries. The expansion of AI technologies has had a tremendous impact on the role of software developers. They are leveraging AI technologies to offload and automate some of their operational tasks, which is giving them more time to pursue innovation and entrepreneurial projects. As developers navigate this next phase, it is crucial that they reshape their outlook on AI and the technologies that support it.

While some see AI as a threat to jobs, at IBM, we view AI as an enabler for the workforce – increasing productivity and driving innovation across all industries.

Unlocking Greater Generative AI Outcomes with Serverless and RAG technology

The rise of generative AI has brought on an influx of data that developers are tasked with managing, which can be daunting when they must manage the underlying infrastructure as well. We’re seeing developer teams spend too much time worrying about their surrounding infrastructure when deploying AI applications on Kubernetes, taking valuable time away from where their focus should be -- driving business outcomes and innovation through these AI applications.

Serverless technology continues to be a strong solution to ensure that developers can run containers in the cloud without worrying about ownership or management of their environments. Think about this like riding your exercise bike in the morning – you want to be able to get through your workout without worrying about the gears and connectivity of the bike. IBM Cloud Code Engine, for example, offers developers a simple interface allowing them to run applications or large-scale batch jobs without having to manage the infrastructure underneath. For the high parallel processing that is often used with AI, our serverless infrastructure autoscales our clients’ applications and jobs and then is automatically decommissioned when no longer needed.

Another great example of serverless computing in action is Retrieval Augmented Generation (RAG). RAG has emerged as a promising solution to ground large language models (LLMs) on the most accurate, up-to-date information, allowing them to produce increasingly accurate results. IBM unveiled its new AI and data platform, IBM watsonx ?, which offers RAG capabilities,?back in May 2023. Overall, leveraging serverless computing will be pivotal for developers in the year ahead as they strive to produce greater business outcomes.

Navigating Data Management & Evolving Regulations?

We’re also seeing regulators around the globe pay closer attention to the data that AI generates. We expect regulatory scrutiny on data privacy and management to continue to increase as international laws evolve and security risks become more sophisticated, especially for developers working in highly regulated industries like healthcare, telecommunications, the public sector, and financial services.?

Enterprises can prepare for upcoming regulations by adopting solutions with the right technology and controls in place so that ensuring compliance doesn't slow down their development velocity. Solutions where data retention is unalterable at the storage layer to safeguard it from any tampering or manipulation can be key to unlocking the balance between innovation and staying on top of these regulations. With IBM Cloud Object Storage and the IBM Security and Compliance Center for example, we’re giving our clients the tools they need to address these requirements head on. The IBM Security and Compliance Center has an "always on" approach to security and compliance with integrated controls for secure data and workload deployment so developers can ensure all their security and compliance goals are being met. IBM Cloud Object Storage similarly offers immutable data retention, data durability, and security to store large volumes of data, further enabling enterprises to demonstrate their compliance.

The Future of AI is an Open Approach

It’s becoming increasingly clear that to navigate the future of AI, software development, and regulations, collaboration is key. At IBM, we believe the future of AI will be rooted in open collaboration. Open-source projects like InstructLab are putting LLM development into the hands of the open-source developer community, allowing them to collectively contribute new skills and knowledge to any LLM.?

We recently announced the availability of 红帽 AI InstructLab for IBM Cloud. We found many clients wanted the benefits of training a large language model with their own knowledge and skills, but they wanted to keep that data private. Red Hat AI InstructLab for IBM Cloud allows clients to train their own model and run it anywhere without worrying about the model being used for other purposes or shared with external parties. In other words, the client maintains sole access control to the model.

At IBM TechXchange, I demonstrated how easy it is to train your own model with Red Hat AI InstructLab using the platform to help shave several minutes off my half marathon time. To execute this, I trained my model on my private running data collected using my smart watch - including sensitive health data such heart rate, V02 Max and personal running location data. I also trained the model on a host of other informative stats such as cadence, stride length, ground contact time, vertical oscillation, and the features of the running sneakers I commonly wear. Through this personal experience, I was able to see how a client could garner valuable insights with InstructLab such as improving fitness performance, while keeping sensitive data private.

Overall, with an open approach to AI innovation, we can empower developers with the information and tools they need to harness AI and cloud technology in ways that prioritize trust, transparency, security, and compliance.

Learn more about our serverless offering: https://www.ibm.com/products/code-engine