Dan Stroot · It's Time to Rethink the Offshore Development Model
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It's Time to Rethink the Offshore Development Model
3 min read
Dan StrootJune 12, 2026
A software engineer in the US might cost three to four times as much as a developer in India, Eastern Europe, or Southeast Asia. When software development was largely a function of labor hours, moving those hours to lower-cost regions was an obvious way to reduce expenses. Companies moved work thousands of miles away to save money because labor was the dominant input.
Thousands of companies embraced the offshore model. Entire consulting giants were built around it. CIOs were rewarded for reducing development costs, and offshore teams became a standard component of enterprise IT.
I know this because I sold the model as a consultant and later bought it as a CIO. However, the model always came with a tax - one almost never accurately measured.
The Coordination Tax
The farther development teams are from the business, the more expensive coordination becomes. Worse, the delivery cycles take longer. The same way networks have latency, development organizations have communication latency. Latency has a very real cost that is difficult to measure, yet organizations definitely feel it.
Anyone who has managed offshore teams understands that context, business knowledge, feedback loops and time zones matter. Requirements clarifications take longer. Small misunderstandings can become large rework efforts. A simple change that might require a ten-minute conversation with a local developer can turn into a multi-day, or even multi-week, exchange across time zones.
To compensate, requirements documents get longer. Meetings become more frequent. Companies added more on-shore "coordinators" (e.g. product or project managers, architects, business analysts, etc.) to manage the offshore team. They added tools like Slack, Teams, Zoom, etc. to try to improve the communication cycle.
Companies tolerated these inefficiencies because labor arbitrage supposedly overwhelmed the additional coordination costs. If an offshore developer cost one-third as much as a domestic developer, the math looked good. Many companies I am familiar with didn't want to look too hard at the coordination costs because they loved the story that offshoring was saving them money.
But what happens when the labor component itself becomes dramatically more efficient?
When Coding Gets Cheaper, Coordination Gets More Expensive
The offshore industry was built around labor scale. The value proposition was straightforward: provide more developers at lower cost. AI changes the equation. Consider what Anthropic reports about its own codebase:
"As of May 2026, more than 80% of the code we merge into Anthropic's codebase was authored by Claude. Before Claude Code launched in research preview in February 2025, this number was in the low single digits."
– Anthropic, When AI Builds Itself
As Anthropic's models and tooling got better it's engineers adopted AI aggressively and productivity increased by a factor of eight:
As AI compresses the effort required to write code, the non-coding portions of software development consume a larger and larger percentage of the total effort. And those are precisely the activities that offshore models have traditionally struggled with.
Software delivery is accelerating and costs are shrinking rapidly. The coordination costs of the offshore model are not. The meetings still happen. The requirements still need clarification. The architecture decisions still require discussion. The business stakeholders still need feedback.
As coding becomes increasingly automated, communication, context, judgment, and business understanding become relatively more valuable.
The Return of Small, Local Teams (Hopefully)
I believe the productivity gains from AI adoption are amplified when the software engineer sits close to the business, understands the domain, and can rapidly iterate with stakeholders. It harkens back to the original Agile Manifesto.
We want fewer coordination layers. Fewer handoffs. Fewer requirements documents. Fewer overnight feedback cycles. We want much faster response to changing business needs. For organizations competing on speed and adaptability, that advantage should outweigh pure labor-cost considerations.
AI shifts the premium toward business knowledge, domain expertise, architectural judgment, and rapid collaboration. The long-term impact of AI on software development may be the elimination of the economic conditions that made large-scale offshore development so attractive in the first place.
There will always be demand for global talent, and many offshore firms are aggressively adopting AI themselves. But the future belongs to smaller teams, closer to the business, amplified by AI. Maybe it's time for a new "AI Manifesto" to supercede the Agile Manifesto?
References
When AI Builds Itself
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