Lars Gentsch

From Monolith Tinkering to Modern Software Development

AI can write code in seconds, but can you trust it? Learn why developers are adopting a zero-trust approach to AI models.

From Monolith Tinkering to Modern Software Development
#1about 7 minutes

Why AI will change developer jobs, not replace them

AI is poised to automate repetitive coding tasks, shifting the developer's role towards complex problem-solving, architecture, and critical thinking.

#2about 2 minutes

Understanding AI's impact on productivity and market value

Using AI tools like Copilot can significantly increase development speed, which redefines the market value of software projects and requires adaptation.

#3about 9 minutes

Navigating the new landscape of AI and cybersecurity

AI introduces new security challenges, including protecting AI models themselves and guarding against vulnerabilities in AI-generated code and data poisoning.

#4about 7 minutes

Addressing legal challenges and building trust in AI systems

The use of AI raises complex legal questions around code licensing and intellectual property, while regulations like the EU AI Act aim to build trust through transparency.

#5about 7 minutes

Managing the rapid pace of AI development and its impact

The high cost of training large language models concentrates power, but a shift towards smaller, specialized models may offer a more sustainable and controllable path forward.

#6about 5 minutes

The importance of critical thinking in an AI-driven world

As AI becomes more integrated into daily life and education, it is crucial to develop critical thinking skills to evaluate AI outputs and avoid blindly trusting its suggestions.

#7about 3 minutes

Final perspectives on the future of AI in software

AI presents both significant opportunities and challenges, transforming the world from software-defined to AI-defined and placing developers at the forefront of shaping this future.

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