AI in the Future

Source: Dev.to

Here are my two cents on the current AI era.

Before reading this, understand that I am not a thought leader, nor have I spent time with founders in Silicon Valley or leaders in major tech companies. Everything below reflects my personal perspective, based on what I have read about AI over the last few months, my experience using AI tools, and my exposure to sci‑fi movies involving artificial intelligence.

My First Encounter with ChatGPT

I was introduced to ChatGPT through dev.to and Instagram when it launched. After seeing a few reels and memes, a quick Google search revealed that GPT was not yet available in India. When a creator later announced its availability, I signed up and started using it.

My initial use case was refactoring legacy code written with class‑based components and an older version of Next.js into functional components using modern practices. Tasks that once took days of code review and documentation lookup were reduced to a few hours. Early GPT models were unreliable and often repetitive, but newer versions are noticeably more capable, more natural in tone, trained on larger datasets, and even suggest follow‑up questions on their own.

What Happens to Developers as GenAI Improves?

Short answer: not much.
Long answer: AI has changed how developers work, not whether developers are needed.

Before GenAI, developers memorized syntax, patterns, and snippets. That repetition built deep familiarity with code. Now, much of that recall is outsourced to prompts.

But writing code has never been the hardest part—understanding code has. Understanding comes from writing, breaking, debugging, tracing variables, inspecting logs, and spending hours figuring out why something fails. AI cannot do this inside your real production environment. It does not see your full system, nor does it feel the consequences of a bad deploy.

AI is fundamentally a response generator. It does nothing without a prompt; it is just another software service.

Web and app development is more than writing code. If coding were all that mattered, anyone with Claude or GPT would already be launching profitable products. That is not happening.

My Definition of AGI

A system with a brain‑like structure, composed of neurons similar to the human brain, capable of thinking independently and acting without constant user input.

Even if companies release something labeled “AGI,” it will likely be a much smarter version of today’s models—trained on more parameters, possibly with vision and real‑time perception—and demonstrated in controlled environments to create the impression of general intelligence, much like polished product demos today.

True AGI resembles Skynet (Terminator), Ultron (Avengers), or the robots in I, Robot: machines with independent consciousness and autonomous decision‑making. We do not yet have hardware capable of mimicking even a fraction of the human brain’s processing capacity. Research into brain‑like computing is ongoing, but we are far from replicating it.

What It Would Take for AGI to Replace Developers

1. Accept vague business requirements.
2. Ask clarifying questions on its own.
3. Design architecture.
4. Write code with extremely high accuracy.
5. Test and iterate autonomously.

Current GenAI cannot do this.

Example: Ask GenAI, “Create a signup feature.” It typically generates a form with name, email, password fields, and a backend endpoint. Yet the user never specified:

• Client‑side vs. server‑side validation
• Mandatory vs. optional fields
• Encryption standards
• Authentication method

A human developer asks these questions, refines requirements, creates an outline, gets approval, implements, tests, reviews, and iterates until defects reach zero. This workflow requires judgment, prioritization, and accountability.

Even if something called AGI appears within a year or two, it will still resemble advanced GenAI, not a human coworker.

Bottom Line

AI will not replace developers anytime soon. Think of GenAI as a powerful machine in a factory: the machine produces output, but workers (humans) inspect results, correct errors, and supply better input. Without workers, the machine does nothing. Claude, GPT, and Gemini cannot write code without prompts.

Current Applications of GenAI

• Customer support chat
• Basic copywriting
• Simple content generation
• Basic‑to‑intermediate graphic design (banners, posters, social media creatives)

Many companies now generate these assets in‑house using image models. Vendors who previously specialized in this work are only contacted when AI output is not good enough or requires heavy refinement. There are likely more affected roles; these examples are not exhaustive.

Advice for Developers

• Learn fundamentals.
• Understand systems.
• Know how things break.
• Know how to fix them.

Job uncertainty existed long before GenAI: projects get canceled, clients cut budgets, markets crash, and companies reduce headcount. Layoffs existed before AI.

The Future

The future is not fewer developers. The future is developers who think better and move faster.