Coding without Code

Coding without Code

Open AI’s Codex ensures, at the least, that the volume of both code and coders in the world will increase. Just that, it won’t be code anymore.

Coding without ‘code’ may sound rather oxymoronic, but it’s really not.

In fact, it has origins dating back to as far as the 1980s and ‘90s, when they were known as fourth-generation programming languages (4GL), early rapid development (RAD) tools or computer-assisted software engineering (CASE) tools. Fast forward to today, and Forrester research notes that the speed of development of low-code/no-code platforms has increased by almost 10 times over traditional development methods – and only getting faster.

According to research from Forbes, a major cause for this recent burst in low/no-code platforms may be attributed to organisations looking towards “quickly build(ing) online experiences to replace physical experiences amid a scarcity of experienced developers and shrinking IT budgets.” This race for technological innovation is seen as a rather attractive proposition, especially in removing the barrier between ideas and solutions and democratising application development.

The release of Open AI’s Codex last week, in this regard, may just turn out to be the most major step yet, perhaps even marking the onset of a paradigm shift in the way that computer software is written and integrated with future hardware architectures. However, for the craze towards no-code software to make sense today, a good idea may be to observe how it has evolved over time.

‘No code is Code’

The first computers in the world were programmed through punch cards and switches – until, of course, the keyboard was invented. Since then, programming had been the art of typing out complex numbers and commands on a low-level machine language, until American computer scientist pioneer Grace Hopper invented what we know today as the first modern-day compiler and the programming language called COBOL.

The invention of COBOL ushered in decades of development in programming languages and eventually, the world saw the birth of languages such as Fortran, Pascal, C (and C#), Java and Python, with the newest of these allowing programmers to ‘code’ in a language that has become increasingly ‘human’, i.e. high-level languages.

Parallel to the growth of these increasingly ‘human’ languages, the world saw the development of Microsoft Excel – a ground-breaking development in ‘no code’ platforms., empowering people to program computers on a visual interface from literally anywhere.

In perhaps a fitting metonymy to coding, tech news conglomerate TechCrunch even notes:

“Anytime you write a formula in a spreadsheet, or when you drag a block of code on or Scratch, you’re programming, or “coding,” a computer. “No code” is code. Every decade, a breakthrough innovation makes it easier to write code so that the old way of coding is replaced by the new.”

 Coding in English

The release of Open AI’s Codex – an entirely novel way to code in natural language, is a landmark event for the future of no-code, period.

TechCrunch writes: “A computer programmer can now use English to describe what they want their software to do, and OpenAI’s generative Al model will automatically generate the corresponding computer code, in your choice of programming language. This is what we’ve always wanted — for computers to understand what we want them to do, and then do it, without having to go through a complex intermediary like a programming language.”

To observe the growth of this Codex against the backdrop of programming evolution offers, over all things, perspective. It is by no means an end, however. It is the beginning. With AI-generated code now becoming a thing, one can easily imagine a major evolution in every programming tool and class – an almost-Cambrian evolution of software.

One must keep in mind, however, that this by no means that the role of the coder is dead. In fact, quite the opposite. The programmer is still the central node controlling all the moving parts, just that their work just got slightly easier. What this essentially means is more time and wiggle room for innovation and impact than ever before.

Demand for software today is greater than ever – a trend that is only going to grow in the coming years. AI will play a much more central role in generating code in the future, thereby not only multiplying productivity and impact of computer scientists, but also democratising code and making it more accessible than ever.

Open AI’s Codex thus ensures, at the least, that the volume of both code and coders in the world will increase. Just that it won’t be code anymore.

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