Will GPT Replace Programmers? Strategies to Thrive in the AI Era

Since the emergence of GPT, headlines have repeatedly claimed that AI will end programming and replace programmers, with figures like Harvard computer‑science professor and Google engineering director Matt Welsh predicting the end of coding within three years. While some articles provide deep discussion, many are merely hype without concrete guidance.

Drawing on a decade of hands‑on coding and nearly twenty years of R&D management, I offer a practical discussion of this topic and propose strategies for programmers.

01 Impact of GPT on Programmers' Work

GPT’s programming ability is impressive: it enables non‑programmers to quickly build applications such as data crawlers, mini‑games, browser extensions, and even a 20,000‑line CRM system. It also allows developers specialized in one stack to jump into another domain—e.g., a backend engineer can create an Android calculator app, or someone with no Unity experience can produce a game similar to "Sheep Game" within a week. Previously, such a switch required weeks of learning; with GPT, the transition can happen almost immediately.

However, programming is only a small part of a developer’s job. Most of the time is spent understanding requirements, communicating, defining interfaces, designing data structures, planning schedules, testing, and debugging. Collaboration and analysis dominate the work.

Both extremes—believing AI will instantly replace programmers because anyone can code, and claiming GPT has no impact because coding is a minor task—are inaccurate.

02 GPT Will Not Cause the Extinction of Programmers

Historical examples show technology can eliminate certain jobs (e.g., typists). Yet, programming remains a composite profession. Even if GPT boosts coding efficiency by 5‑10×, human communication, collaboration, and analysis are not significantly automated. Overall, GPT may double a programmer’s productivity but will not make one programmer replace ten.

Software demand continues to grow as industries digitize. Many existing applications are outdated or of poor quality, especially in government and enterprise internal tools, requiring redevelopment. Consequently, the need for programmers is unlikely to decline and may even increase.

03 Individual Programmers Are Not Secure

Programmers have high labor costs, and companies constantly seek cost reductions. Since last year, even top firms in China and the US have conducted large‑scale layoffs, and smaller companies struggle to afford software projects.

GPT offers new ways to cut costs: it enables a single developer to handle full‑stack work, and it allows hiring less‑experienced, lower‑cost personnel who can be quickly trained to code with GPT assistance.

China produces about ten million graduates annually, many of whom view programming as a high‑salary, respectable career. With GPT, they can self‑learn quickly, and low‑code platforms already allow non‑technical staff to develop applications within a month.

Low‑code developers, often non‑computer‑science graduates, can deliver comparable solutions at lower salaries, prompting companies to replace senior developers with such talent where feasible.

04 Transition to Full‑Stack or Low‑Code Is Fundamental

Traditionally, developers start in a specific technology stack and progress to senior roles, rarely switching domains due to high learning costs and the need for division of labor in large projects.

In the past, a single programmer could handle UI, data processing, and logic (C/S architecture) or even full‑stack web development. Future trends will depend on demand and learning costs.

Current demand is strong in internet, finance, and large enterprises, but growth is limited there. Most new demand comes from traditional industries undergoing digital transformation, which often require simpler applications—ideal for full‑stack or low‑code developers.

GPT reduces the time needed to switch stacks to near zero, making full‑stack capability highly valuable. Low‑code platforms inherently provide full‑stack functionality, turning low‑code developers into de‑facto full‑stack engineers.

Thus, many application development roles will likely shift toward full‑stack models, and programmers should proactively acquire cross‑stack skills.

05 Full‑Stack Is Not the End Point

Even if a team of ten specialists becomes eight full‑stack engineers, the reduction is modest and does not guarantee job security. Early adopters of full‑stack may enjoy a temporary advantage, but long‑term the landscape will evolve further.

Advances in GPT and low‑code will dramatically lower entry barriers, with platforms like Microsoft PowerApps already integrating AI. Low‑code and GPT together will create a new class of development tools that differ significantly from traditional IDEs.

A simple calculation illustrates AI’s impact: assume a senior programmer spends 40 % of time coding (10× efficiency over a junior) and 60 % on other tasks (2× efficiency). Overall efficiency is 5.2×. With AI, coding drops to 20 % and other tasks rise to 80 %; if coding efficiency falls to 3×, overall advantage shrinks to 2.2×. This reduces the salary premium of senior developers.

Consequently, programmers’ high salaries are driven more by supply‑demand dynamics and technical barriers than by intrinsic value creation, both of which are changing rapidly.

06 Evolving into a Composite Talent Is the Way Forward

Programmers should first become full‑stack (including low‑code) to broaden opportunities and deepen business understanding. Beyond that, they should develop skills in management, architecture, business analysis, product design, marketing, and domain‑specific technology products.

Management and architecture paths are limited (≈10‑15 % and ≤10 % respectively). The most promising route is becoming a business‑oriented developer who can analyze requirements, design products, and code—estimated to offer 30‑40 % of opportunities.

Technical product areas such as cloud computing, big data, and middleware will continue to demand top‑tier programmers.

07 Summary

In summary, GPT is unlikely to eliminate programmers but will profoundly reshape their roles. Developers should evolve into full‑stack (including low‑code) engineers, then expand into business, marketing, management, architecture, or specialized technology product domains. Those who remain confined to pure coding will likely become junior‑level, lower‑paid professionals, while many will acquire software development capabilities without relying on it as a sole livelihood.

Source: Cold Technology Hot Thinking