Same AI, Four Different Jobs: Startup, Mid-Size, Big Tech, IT Services

In March 2025, a quarter of the W25 batch at Y Combinator reportedly had codebases that were about 95% generated by AI, according to managing partner Jared Friedman. At the same time, Stack Overflow's survey found that 28% of developers believed their company's IT or Information Security teams had strict rules prohibiting the use of AI agent tools.

As the source indicates, despite the use of the same models and technology, engineers in different company sizes experience vastly different working lives due to the impact of AI.

In a startup, the engineer's role changes significantly. With 95% of the code generated by AI, the engineer becomes highly technical and capable of building their product from scratch. They now spend most of their time reviewing code and finding bugs, as there is no existing infrastructure to maintain. This shift places a heavy emphasis on speed and ownership, but also exposes the engineer to potential risks such as being the only person aware of the system's inner workings.

In a mid-size company, AI is seen as a tool to increase impact by 2x within a year. Engineers are given more autonomy and are encouraged to self-report their progress, as the organization places less emphasis on formal measurement. This setting offers the engineer a voice in how AI is evaluated, but also carries the risk of losing trust if the company grows too large to maintain that level of personal accountability.

At large enterprises and big tech companies, AI becomes a metric used to measure performance. Engineers face pressure to work faster than sustainable rates and have to deal with the surveillance of their work. Their time is consumed by untracked, invisible tasks, such as reviewing AI output and fixing bugs. According to a 2026 survey, 54% of developers at large enterprises fear that their performance reviews will be based on AI data, while 46% report experiencing unsustainable workloads and privacy concerns.

Finally, in IT services, AI is transforming the way services are priced. With persistent clients demanding 25% to 30% less work delivered faster, IT service companies are tying contracts to outcome measures. The Nifty IT index saw a decrease of 20% in 2026, reflecting the impact of AI on the industry. For engineers in this field, the challenge lies in adapting to the new pricing models and ensuring their skills remain relevant in an increasingly automated environment.