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With AI Boosting Productivity, AWS Strategist Advocates More Developers, Not Fewer

• By David Ramel
• 12/10/2025

AWS Enterprise Strategist Mark Schwartz argues that the current wave of AI-assisted development should not lead to automatic developer layoffs.

AI tools are increasing team output, he says, and leaders looking only for cost cuts may be tempted to shrink headcount. Schwartz's core point is that higher productivity changes the value equation for software work, and the smarter business move is often to do more, not less.

He starts with a straightforward definition of productivity: AI increases "the value of each hour of developer time." AI-assisted integrated development environments can automate routine development work, insert code, and flag issues as developers type, while also surfacing information that previously required separate research. Schwartz extends that improvement across the entire delivery lifecycle. AI agents can help generate test cases, refactor code, and manage dependencies, and he says newer patterns of agentic development shift the burden of complex reasoning into models. The result is that "the developer's code is compact; it delegates much of the hard stuff to the LLM." He also points to higher-level tooling that translates specifications into code, which can let product managers, architects, and other contributors participate more directly in building software outcomes.

The main question, Schwartz says, is what companies should do with this extra capacity. His answer leans on a familiar problem: most organizations have far more worthwhile IT work than they can staff or fund. Backlogs are not just major projects queued for later; they include long-lived tickets and bug fixes, modernization efforts, technical debt reduction, agility investments, and risk management work that often never reaches the top of priority lists. Capacity limits force hard go/no-go choices, leaving valuable tasks waiting or abandoned.

AI-driven productivity gains, he argues, raise the return on that entire backlog. Because tasks cost less developer time to complete, their ROI increases. Schwartz calls this the pivot: "the AI-driven productivity increases change the ROI calculation for everything in the backlog." Projects that once fell below governance thresholds may now exceed them, and work already approved in the pipeline can deliver higher returns when AI accelerates delivery. AI also enables new initiatives with strong business cases, meaning the pool of high-ROI work expands rather than contracts.

That leads to his counterintuitive conclusion. If each developer hour is now more leveraged, cutting developers can destroy value by removing the means to capture that higher ROI. Schwartz says "reducing headcount--headcount that has become even more valuable to the company--destroys business value," and he adds that "hiring more developers could make sense, since each incremental developer contributes more to the company's bottom line." He notes that layoffs only cleanly fit a rare scenario where a company already has exactly the IT capacity it needs, which he suggests is unlikely given how often business leaders complain about IT delays.

This argument arrives as Amazon and AWS are investing heavily in AI infrastructure while acknowledging that AI efficiency will reshape some jobs. Amazon CEO Andy Jassy has said, "As we continue to invest in generative AI, we do expect that some roles -- especially in corporate functions -- will evolve or no longer be needed." (See: Are Cloud Giant AI Investments Being Fueled by Workforce Reductions?.) However, Schwartz's Dec. 9 post is focused specifically on software delivery capacity, arguing that AI makes developer labor more valuable and expands the set of projects worth doing, even as Amazon's broader messaging anticipates role reductions in other areas.

Schwartz also argues that productivity gains can support several business priorities that are often constrained by bandwidth. For executives pressing for savings, he notes that much backlog work is intended to reduce costs elsewhere in the organization, and delivering it faster still yields those savings even if they appear in different budget categories. He says newly possible AI initiatives can raise employee productivity across the company, multiplying benefits beyond IT. For leaders who want more innovation, he suggests the added capacity can sustain a portfolio of experiments and proofs of concept, allowing new ideas to be tested quickly and with less risk. And for organizations carrying significant technical risk, extra capacity can be directed toward outdated systems, security gaps, disaster recovery improvements, and technical debt that erodes agility over time.

He closed with this:

The key point is that AI still requires technologists, who will create some of the more complex agents and make all the company's AI agents enterprise-grade, with the appropriate resilience and security. But with AI-driven productivity improvements, each dollar spent on those technologists brings a higher return to the business than before. Spending marginal dollars on IT, rather than reducing IT spend, is the route to higher business value.

That's assuming that the organization doesn't already have enough IT capacity. Does yours?