AI Force Software Engineer to Adapt into AI Ecosystem

Software engineer used to work on converting user story into actual working products. It could be inform of web app, mobile app or the backend services. There are various developer during a system implementation project such as backend engineer, frontend engineer, database engineer, infrastructure engineer, tester, solution architect and network engineer. Each of them play important roles to make the user story into an actual working product depending on the area of working.

However, those landscape are completely changed into new direction in the age of AI especially on the staffing plan strategy. With the help of AI as supporting tools, these role are now actually become a vague because everyone can shape shifting into different roles.

a super developer who used to excel on backend and frontend before the age of AI might be able to take all of these role with the help of AI. It resulting in the trend of reducing the headcount of IT departments staff. For example, it might took at least five developers to finish 50 story points, but now with help of AI which specialized in coding like cloude, the number of required developer to complete up same story points is drasticly reduced.

— 1 million dollar question, is it enough just to become super developer to survive the current harsh job market?

Globalization amplify the AI adoption side effects for software engineer

AI can be accessed by anyone regardless their nationality, political interest and race. As long as they have internet connection, those tools can be used. AI is reducing the gap between an actual skilled software engineer and mediocre software engineer.

Given said that, many organization started to aggresively hire developer from low cost country such as south east asia country, india, south america and equip them with the best AI tools for coding while keeping some senior tech lead/solution architect onshore to guide the offshore developer.

— it distrupt the software engineering market especially on high cost country like USA and europe.

For many organization, this sitution is a win. They used to spends tons of money just to create a “simple POS system”. Nowdays, the cost can be reduced by utilizing less headcount to build the system with the support of AI.

How to Survive the Harsh Job Market as Software Engineer?

The only way to survive is to adapt, learn and transform by considering these mindset

1. Instead of limiting ourself as technical person, we should understand the business domain
2. Dont see business domain as a burden, see it as an opportunity
3. With the help of AI, most of business domain can be self taught, evehthough it might no as deep as someone who learn it directly fromt their education background. The gap still there, but its thinning.
4. Blend the business domain knowledge and technical knowledge = strong positional offering for the organization (less prone to be replaced)

​ Deep technical knowledge + Actual System Implementation Experiences + Business Domain Knowledge = Higher chance to keep the employment and survive the harsh job market.

Its harsh truth but it is what it is. Unless we adapt to the new era, most of organization will replace their expensive software engineer with cheaper resources which could be providing more contributions due to the AI.

How to Learn Business Domain Effectivly Using Specialized AI Tools

Functional area role such as business analyst is facing similar challenges with the AI adoption. Everyone know can learn business domain with the help of AI. However, as a technical person, this is an opportunity to equip ourself with business knowledge to increase the impact of our contribution on the organization.

There are various specialized AI tools which used by business analyst shapen the business knowledge during their projects / works.

Note: the AI specialization impression is purely based on the writers opinion and preferences.

Below are the lists.