The future of software development is here, and it’s driven by artificial intelligence (AI). As we enter the year 2024, developers can look forward to a paradigm shift in their industry. From enhanced security measures to the diminishing role of legacy platforms, the impact of AI on software development is set to be transformative. In this article, we explore the key trends and changes that developers can expect in the coming year.
1. Securing Sensitive Access Points with Secretless Authentication
In 2023, human error played a prominent role in costly security breaches, with the human element being involved in 74% of all breaches[^1^]. To combat this, organizations started embracing biometric hardware and identity verification. However, attackers have shifted their focus from stealing passwords to seeking a range of secrets embedded within an organization’s infrastructure[^1^].
To address this challenge, the widespread adoption of secretless authentication is predicted to be a game-changer in 2024. Secretless authentication involves eliminating the need for secrets such as passwords, browser cookies, private keys, API keys, and session tokens to secure sensitive access points[^1^]. By moving towards fully secretless authentication, organizations can significantly reduce the risk of human error and hamper threat actors’ operations[^1^].
2. Shifting Roles in Development and IT Security
The year 2024 will witness significant changes in how companies approach network security. The traditional IT-centric strategy of dedicated security teams will evolve, with security teams taking on the role of consultants and auditors[^1^]. Engineering teams will be responsible for choosing vendors and implementing security protocols, while cybersecurity teams will focus on policy and ensuring that workflows and systems meet security requirements[^1^].
This shift in roles will empower developers to take a more active role in security decision-making, fostering a culture of security throughout the development process. Developers will have the opportunity to contribute their expertise in choosing secure technologies and implementing best practices, resulting in more robust and resilient software systems[^1^].
3. Augmenting Developer Integrations with AI Tools
Artificial intelligence tools will continue to augment developer integrations, revolutionizing various aspects of software development in 2024. OpenAI has sparked a massive information revolution, leading to innovations in DevOps, data mining, and project management[^1^]. Developers will need to adapt to these advancements and place more emphasis on core web vitals, ensuring optimal user experiences[^1^].
One notable shift is the transition from local workstations to cloud workstations. Developers who embrace this change will stay ahead of the curve, leveraging the scalability and flexibility offered by cloud-based development environments[^1^]. This shift, combined with AI-powered tools, will enable developers to streamline their workflows and enhance productivity.
4. Low-Code Development and Organizational Design
Low-code development will continue to gain popularity in 2024, driven by the AI boom and the need for increased productivity and agility[^1^]. Low-code platforms empower citizen developers to create applications with minimal coding, freeing up professional developers to focus on system design and architecture[^1^].
The rise of low-code development parallels the use cases and adoptions of AI. Both AI and low-code development reduce the burden of writing extensive lines of code, enabling faster development cycles and easier maintenance[^1^]. As organizations look to expand software development to citizen developers, the use of low-code platforms is expected to increase significantly in 2024[^1^].
5. Integrating Legacy Systems with Modern IT Stacks
Legacy systems, while often considered a barrier to innovation and change, will continue to play a role in the modern IT landscape in 2024[^1^]. Organizations in industries such as financial services find it expensive to replace these systems, leading to the integration of legacy systems with current technologies[^1^].
Modern integration platforms enable seamless integration between legacy systems and modern IT stacks, allowing organizations to leverage the functionality of legacy systems while embracing new technologies[^1^]. This integration prolongs the use of legacy systems and supports innovation and change without incurring excessive costs[^1^].
6. AIOps: The Intersection of AI and Network Operations
Artificial intelligence for IT operations (AIOps) will play a critical role in software development in 2024[^1^]. The adoption of AI is growing exponentially, and while complete automation is a distant goal, human talent remains essential in the AI story[^1^].
Networking companies will embed AIOps into their operations to improve network quality, support engineers, and modernize infrastructures[^1^]. The concept of a “Dark NOC” will enter the lexicon, where automation is at the heart of network operations, but human skills and expertise are crucial for its success[^1^].
7. Strengthening Software Supply Chain Security
In 2024, software supply chain attacks will continue to be a significant concern for developers and organizations[^1^]. Attackers have realized the impact of compromising a single software supplier or widely used open-source software library, making it more efficient than targeting individual organizations[^1^].
To combat this, the industry will see a push for secure-by-design practices and software liability products[^1^]. Platform providers will drive systemic changes by making secure platform changes, benefiting many users[^1^]. The topic of software liability will remain debated, with some concerned about stifling innovation while others advocate for holding software suppliers accountable[^1^].
8. Meta’s Purple Llama: Advancing Safety in AI Models
Meta’s Purple Llama project aims to empower developers and promote AI safety in 2024[^1^]. The project offers trust and safety tools and evaluations to guide responsible deployment of generative AI models and experiences[^1^]. The goal is to protect AI systems from unintended behaviors
