AI is here, and so is the end of traditional tech roles.

The design zeitgeist is becoming increasingly concerned with the question, "Will AI take my job, and if so, when and how?"

I can sense this because, in the last few months, I have had multiple chats with design people in manager and IC roles about this topic.

Most conversations always end with the doom-charged assertion that designers must adopt AI workflows to stay relevant. If they don't, external forces will overtake and redefine the field for them.

The prevailing feeling is that the average tech organization might not move fast enough to reskill existing individual contributors around AI-centric workflows and that the average tech worker will remain apathetic to AI innovation as long as there’s no pressure from their employers to shift.

However, it is now clear that despite the hype and vaporware around the AI revolution, there’s indeed a high-value opportunity behind this technology. As it continues to mature, it will force a reconfiguration of technology knowledge work.

Software developers, designers, product managers, and other traditional R&D technology workers are particularly vulnerable to this reconfiguration.

A good example of the force brewing is an emerging class of AI-augmented full-stack builders who don't care about traditional tech role etiquette or decorum and couldn't care less about the identity struggles of contemporary tech workers.

These people are seizing the opportunity and taking advantage of the multiplier effect of AI-enabled solutions to create products, build audiences, and solve real problems.

This new kind of tech builder is not concerned about developing specific hard skills because they understand that there’s a viable path to leapfrog a skill gap with good AI orchestration skills.

This makes sense when you reflect on the pre-AI mechanics of building software.

Traditionally, software creation has involved the circulation and integration of diverse outputs from people of different disciplines into a tangible outcome: a product or a feature.

However, AI has proven that software can be created without this fragmentation if a single individual has enough context and an environment to productively integrate AI outputs.

As long as you have a holistic understanding of the desired end state, you can offload the tactical creation of any software solution by simply orchestrating AI outputs.

This means that a single individual can single-handedly bring a software idea to fruition as long as they clearly understand what they want.

This is no fantasy. As said before, thousands of people are presently building software and producing creative material simply by being effective AI operators.

This trend will likely continue as we enter 2025 and will start emerging as the new standard for software development for new and upcoming startups.

New companies are well-aligned with the incentives of hiring AI operators (people who are good at bringing AI outputs together into tangible products) because they don't have to deal with the cultural challenges of encroaching on the status quo and sunsetting classic tech roles.

Older companies will have to figure out a way not to be outcompeted on productivity output, so they will likely continue with their efficiency mandates as they push new expectations on existing roles and allow organic attrition to extinguish the old status quo. This will be a slow and painful process.

It’s important to understand that this will affect all classes of tech workers. Professional skill boundaries are likely to dilute, and professional identity questions such as “Should designers learn to code?” or “Should developers learn to design?” will stop mattering.

This is now an even playing field that will reward those who can develop multiple areas of knowledge and leverage AI to execute in those areas with depth.

For those who have traditionally operated as developers, the current challenge is how fast they can grow the intangible skills that allow them to create friendly and tasteful user experiences.

For those who have traditionally operated as designers, the current challenge is how fast they can grow the hard skills needed to orchestrate the AI into producing stable software.

Both groups will enter into a race that will collapse into a new emerging class of technology workers, blurring the boundaries between traditional roles.

This will happen over many years and will be no different from previous milder transformations, where it seemed like nothing had changed, but it then became clear that the underlying reality was indeed different.

It is debatable whether this will play out exactly as laid out here. However, the visible trajectory is clear: Change is inevitable. The best course of action is to not resist but embrace and evolve.