When Code Becomes a Commodity Be Ready.
Arslan Mehboob · May 19, 2025 · 5 min read
When Code Becomes a Commodity Be Ready
We are in the future just like a Black Mirror episode where everything is relatable at some level, there are no flying cars and everything is kind of the same but feels different at the same time. By we, I mean the software industry. The episode is live streaming right now.
Code has begun its slow but unstoppable slide from craft to commodity. If that sentence triggers déjà‑vu, good, it happened when we moved from punch cards to compilers, from C to Java, and from on‑prem racks to the cloud. The difference this time is speed.
According to McKinsey’s 2023 Coding Boost study, LLM‑powered assistants already shave 35–45 percent off routine coding tasks and halve documentation time. GitHub needed eight years to reach 100 million users; ChatGPT did it in two months. Buckle up!
Code as a Cheap Commodity
Abstraction has always won. COBOL hid assembly, Java hid malloc, Kubernetes hides the data centre, and large language models are about to hide the code itself. When the cost of one more feature drops to the price of an API call, supply inevitably outstrips demand.
Today I can ask an agent for “an event‑driven order service in the language of my choice, tested, observable, and PCI‑DSS compliant” and receive a pull‑request before my coffee cools. The challenge is no longer whether I can get code, but how to get AI to write the required code and whether I should merge it.
If all this feels unsettling, remember that software value has always migrated upward. We once debugged with paper print‑outs, now we orchestrate fleets of containers we never SSH into. The next hop is orchestrating black‑box code repositories written and refactored by machines.
Enter the Operator‑Architect
The software development role is going to be evolved into an operator model. The operators will be much more involved with the domain knowledge. The good news is that this role will not be eliminated or outsourced to a vibe coding cat.
If you strip away all the implementation complexity, the real world problems essentially revolve around managing tradeoffs. For example domain knowledge lets us understand why a system prefers eventual consistency in order to support horizontal scaling. The complexity will even amplify as we move up the layers of abstraction.
Essentially the code bases will become black boxes. How many boxes you need, the size of each box, how the boxes talk with each other in a secure manner will still be the important decisions to make. Coders will need to become architects. The engineering fundamentals will become more relevant than ever. Instead of using the only sort algorithm you know and apply everywhere, you would be able to apply the best suited algorithm for the right job. The engineers will need to know the right design patterns, architecture gotchas and security needs and let AI handle the heavy lifting.
Workflow: 2026 Edition
In practice, the future workflow will be remarkably conversational. Development begins with a plain‑language user story that doubles as a system prompt. A specialised agent uses that intent to draft code, tests, infrastructure changes, and an architectural‑decision record. A second model performs continuous review, running static analysis, executing unit tests, and attaching risk scores.
Throughout this process, the operator‑architect curates, choosing trade‑offs, aligning with domain constraints, when satisfied, pressing Merge. Once in production, an observability bot monitors service‑level objectives and automatically opens new stories when drift appears.
This isn’t science fiction. Right now you can do this by welding VS Code, GitHub, and Jira together with MCP. Right now you can
- Pull in a JIRA ticket right into your IDE.
- Ask AI to create a plan of required changes based on the acceptance criteria.
- Verify the plan, tweak if required and ask the agent to execute the plan.
- Get the PR reviewed by another AI.
- Test and verify.
- Final review from a team mate.
- Merge and release.
The user experience will feel like mentoring a slightly distracted super genius junior developer.
Preparing for the Pivot
Start by reinvesting in fundamentals. Big‑O, CAP, and SOLID will become the compass when AI obscures the map. Next, go deep into the business: when code is replaceable, contextual judgement becomes priceless.
Treat security as a first‑class prompt, assuming every generated line ships with an exploit until proven otherwise.
Automate the plumbing so you can human‑ise the product; the less time you spend arguing with linters, the more you can spend delighting users.
Lastly, keep an open mind about the innovations that are coming. The next generation of engineers will be able to do things we can only dream of today. They will be able to create and maintain systems that are far more complex than we can imagine. They will be able to do this because they will have the tools and the knowledge to do so.
Adopt or Fossilise
Engineers who cling to the editor as identity may become the mainframe programmers of this era, largely invisible. Those who step up to architecture, curation, and levelling up their domain knowledge will find the career landscape broader, not narrower. Code is getting cheap, whereas good judgement is becoming expensive. Choose your side of the supply‑and‑demand curve.
