IS CODING ABOUT TO DIE? - HOW ARE PROGRAMMING JOBS TRANSFORMING

Harness AI to supercharge your workflow: Speed up testing, encourage language learning, and evolve team structures for efficiency.

Dec 16, 2025 7m 4s

Krzysztof Zablocki

Expert Insights

In the film "Is Coding About to Die? - How are Programming Jobs Transforming," Krzysztof Zablocki gives a forward-looking perspective about AI and its impact on the software development landscape. Zablocki’s vision for AI-assisted software development is revolutionary, arguing that we are on the cusp of a significant transformation in programming careers due to the capabilities AI presents.

Zablocki warns that more conventional programming jobs might observe a steep decline, and implicates that entry-level programmers could face potential obsolescence due to AI replacing lower-level tasks. Crucially, he suggests those entering the software development field should focus on applied AI or machine learning, as those areas still present growth opportunities.

Key insights from Krzysztof in this film:

Zablocki warns about the impact of AI tools on the job market, predicting a significant drop in developer headcount. He encourages those entering the industry to focus on applied AI or machine learning.
Small teams and startups can greatly benefit from the use of AI, leveraging its capabilities to expand their productivity and reduce reliance on larger teams or higher staffing budgets.
AI grants those developers and teams utilizing the technology the ability to rapidly test and iterate their work, allowing them to accomplish tasks in a fraction of the time it used to take.
Despite the criticisms and challenges surrounding AI-generated code, Zablocki defends its utility and states that it opens the field to more experimentation and diversity in solutions.
Learning is accelerated with the help of AI. Zablocki believes that AI can be key to discovering missing information and providing a personalized learning experience.

What AI allows us to do is run five different sessions on five different work trees, each with slightly different descriptions of how I wanna build something, and I'm gonna get five different implementations.

Monterail Team Analysis

Here are practical takeaways for software teams as they navigate the new default of AI-assisted development:

Prepare for the influx of AI: Recognize that AI is not just another tool but a new field that is reshaping the nature of programming jobs. Investing in AI and machine learning skills is crucial for future relevance.
Adapt team structures: With AI able to handle lower-level tasks, adopt leaner, more specialized team structures that can fully leverage the capacities of AI.
Accelerate your work processes: Harness AI's ability to create multiple variations of solutions, facilitating rapid testing and iteration of your work. This can significantly cut down your project's timeline.
Leverage AI in the learning process: Utilize the capabilities of AI not just for building, but for learning as well. AI can help identify gaps in knowledge and facilitate faster, more efficient learning.
Evolve your job requirements: As AI tools take over routine tasks, developers are freed to concentrate on advanced tasks such as system design and AI-related technologies.
Utilize AI in building prototypes: With AI, you’re not restricted to build one product at a time. AI lets you prototype different versions of your product, saving time and resources.
Set higher expectations for projects: Given the speed and productivity boost AI grants, it's crucial to reassess what to expect from a project in terms of quality and delivery time.