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The New Era of Programming with AI

Programming with AI has completely changed the way we think about software development. What once felt like a purely technical and often tedious process has now become not only faster but surprisingly enjoyable. Working with AI tools in coding feels like collaborating with an incredibly capable partner one that accelerates learning, boosts productivity, and reshapes the creative flow of building software.

The typical workflow looks something like this:

  1. Generate Code – Use AI to draft initial code structures and functions.

  2. Read & Understand – Carefully study the generated output to ensure comprehension and accuracy.

  3. Manual Refinement – Make small but meaningful adjustments, often with the assistance of intelligent autocomplete features.

  4. Test & Debug – Validate the functionality, identify bugs, and refine the implementation.

  5. Prompt for Larger Changes – When major shifts are needed, craft new prompts to restructure or extend the codebase.

  6. Repeat the Cycle – Return to step one and continue iterating. 

Some developers may skip the second and third steps, diving straight into “vibe coding” trusting the AI without deeper review. But in reality, human expertise remains essential, especially in steps 2, 3, and 4. Understanding, debugging, and refining code requires judgment, context, and creativity that AI has yet to fully replicate.

That said, the benefits are undeniable. Personally, I’m learning concepts at a faster pace, producing high-quality code more efficiently, and most importantly finding far more enjoyment in the process. Programming feels less like a grind and more like a dynamic collaboration.

Are we close to Artificial General Intelligence (AGI) or Artificial Superintelligence (ASI)? Probably not. But in the realm of software engineering, the transformation is already here. AI is reshaping workflows, breaking down barriers to entry, and making powerful tools accessible to more people than ever before. This shift comes with serious implications:

  • Challenges – Job displacement, security risks, and ethical concerns.

  • Opportunities – Greater productivity, democratized access to programming, and a surge of innovation.

To experience this transformation firsthand, on a daily basis, is surreal. We’re not just witnessing the future of coding we’re actively living it.

(And yes, in case you’re wondering, this reflection was written by a human in one take—no spellcheck, no AI assistance. 100% organic writing, for real 🤣)

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