Python is foundational, yet AI and cloud skills are imperative
Python still dominates software development, and its position isn’t changing anytime soon. It’s the basis of artificial intelligence (AI) and data science, which are now driving most industries forward. Companies rely on Python for machine learning models, automation, and advanced data processing. If you’re working in software, knowing Python is a basic requirement. But here’s the reality, being good at Python alone won’t keep you relevant.
AI and cloud computing are reshaping the way software is built and deployed. Businesses expect developers to do more than write clean code—they need to integrate AI and leverage cloud-based infrastructures to scale applications efficiently. Python is a powerful tool, but its full potential is realized when combined with AI systems and cloud platforms. Developers who understand how to train AI models, automate workflows, or deploy scalable applications in the cloud will have a clear advantage.
For executives, this means investing in teams that understand the full technology stack, not just the basics. Competitive advantage is created by developers who write code and build intelligent, efficient, and scalable systems. Companies should prioritize AI and cloud fluency within their engineering teams to ensure they stay ahead in a fast-moving industry.
Developers who adapt in this direction will maintain high value in the market. Pluralsight’s 2025 Tech Forecast reinforces this, with Python ranking as the second-most searched topic in 2024, right after AI. The connection is clear—Python’s relevance is tied to its role in AI, and developers who master both remain in demand.
Effective utilization of AI coding assistants requires rigorous oversight
AI coding assistants like GitHub Copilot are no longer optional. They are becoming a standard part of software development, accelerating workflows and improving efficiency. Developers who know how to use these tools effectively will be more productive, but there’s a major challenge, AI-generated code isn’t always reliable. Left unchecked, it can introduce security flaws, inefficient logic, and unnecessary technical debt.
Businesses that rely too heavily on AI-generated code without oversight risk building unstable or insecure applications. AI is powerful, but it lacks judgment. It can generate functional code, but whether that code is efficient, secure, and maintainable is another matter. Developers need to review AI outputs carefully, refining them for quality and ensuring security standards are met. The ability to critique and optimize AI-generated code is now a critical skill.
For executives, this means AI adoption must be strategic. AI coding assistants can reduce development time, but poor implementation can create long-term technical and security liabilities. Training developers in effective AI-assisted coding practices and enforcing strong code review standards will ensure AI remains an asset, not a risk.
Laurentiu Raducu, founder of bitheap.tech, warns that AI-assisted development can create a false sense of productivity. Teams may appear to be delivering more output, but without rigorous oversight, AI-generated code can compromise critical infrastructure. Companies that invest in structured AI governance and quality control will maximize efficiency while maintaining system integrity.
Entry-level developer roles are dwindling
Entry-level software jobs are becoming harder to find. AI automation is taking over routine coding tasks, and companies are shifting their hiring strategies toward experienced developers who can deliver results with minimal oversight. Businesses are no longer looking for beginners, they want professionals who can take ownership of projects from day one.
For aspiring developers, this means expectations have changed. Companies are no longer interested in candidates who can only write simple functions or follow tutorials. They need people who can build complete applications, solve real-world problems, and work effectively with AI coding assistants. Those who want to break into the industry must develop at a more advanced level, contributing to open-source projects, mastering AI-assisted coding, and building strong personal portfolios.
For executives and hiring managers, this shift requires reconsidering how talent is cultivated. While experienced developers are in demand, the long-term sustainability of the workforce depends on training new talent effectively. Companies that invest in apprenticeships and structured learning programs will have a better pipeline of skilled professionals, rather than relying solely on external hires.
Pluralsight’s 2025 Tech Forecast highlights that AI is already replacing some junior developer tasks. Maaike van Putten, a best-selling JavaScript author, has pointed out that while demand for senior developers remains high, opportunities for beginners are shrinking. Companies that recognize this trend and adapt their hiring and training strategies accordingly will maintain a stronger, more capable engineering workforce.
Developers must assume responsibility for cloud and API security
Security is no longer someone else’s responsibility. Developers are directly involved in building and maintaining cloud-based systems, APIs, and software platforms, which means they must also take responsibility for securing them. API vulnerabilities and cloud misconfigurations remain among the top security risks, and businesses can no longer afford to treat security as an afterthought.
Companies that fail to integrate security into development workflows expose their systems to major risks, including data breaches, service disruptions, and financial losses. Cyber threats are evolving, and most organizations lack the security talent to address them effectively. Developers who understand secure coding, implement zero trust architectures, and work with cloud-native security tools will provide immediate value by reducing exposure to attacks.
For executives, this shift requires emphasizing security as a core development priority. Organizations that invest in cloud security training for their engineers, enforce security best practices, and integrate security reviews into software development will avoid costly breaches and compliance failures. Strong security practices are a competitive advantage.
Pluralsight’s 2025 Tech Forecast reinforces this urgency, identifying API vulnerabilities and cloud security weaknesses as major attack surfaces. Companies that ensure their developers have strong security expertise will be in a far better position to protect their infrastructure, data, and customers.
Proactive compliance with accessibility standards is unavoidable
Accessibility is no longer optional. Starting June 28, 2025, the European Accessibility Act (EAA) will enforce strict accessibility requirements for digital products and services. Companies that fail to comply could face fines of up to €1,000,000. This isn’t limited to businesses based in the EU, it applies to any company serving EU customers.
Many businesses still overlook accessibility, seeing it as a secondary concern. That approach is no longer sustainable. Accessibility is now a regulatory requirement, and integrating it into software development from the start is the most effective way to stay compliant. Developers must understand and apply Web Content Accessibility Guidelines (WCAG), ensuring their applications are usable for all customers, including those with disabilities.
For executives, this is both a legal and strategic issue. Companies that develop accessible products avoid regulatory fines and expand their user base, improve customer experience, and strengthen brand reputation. Investing in accessibility now reduces the risk of last-minute compliance challenges and ensures long-term usability for all customers.
The EAA is a clear signal that accessibility will continue to be a mandatory part of software development. Companies that prioritize it today will be ahead of the curve, while those that ignore it will face financial and operational setbacks.
Key takeaways for leaders
- Python alone is not enough: Python remains a core programming language, but its value is maximized when combined with AI and cloud expertise. Leaders should encourage training programs that integrate these skills to ensure developers remain competitive.
- AI coding assistants require oversight: AI tools like GitHub Copilot speed up development but can compromise security and code quality. Organizations must implement strict review processes and train developers to refine AI-generated outputs.
- Entry-level developer roles are disappearing: AI is automating junior tasks, making mid-level skills essential for hiring. Companies should invest in structured learning programs and apprenticeships to maintain a steady pipeline of skilled developers.
- Developers must own security: API vulnerabilities and cloud misconfigurations are growing risks, and developers must build security into their workflows. Business leaders should prioritize security training and enforce secure coding practices across teams.
- Accessibility compliance is now mandatory: The European Accessibility Act enforces strict digital accessibility standards, with significant financial penalties for non-compliance. Organizations must integrate accessibility into product design early to avoid legal risks and improve user experience.
