Tola Awofolu

Uber burned through its entire 2026 AI tools budget by April. Microsoft faced a similar crisis, pulling Claude Code licenses because the tool worked too well and people used it too much. Even OpenAI's chief executive officer (CEO), Sam Altman, has called token costs "a huge issue" for the company and its customers. "Tokenmaxxing," the tendency to burn through tokens without a clear link to business outcomes, has gone from an internal joke to a boardroom problem.

In our previous post, we walked through the agent mesh for software modernization architecture we built on Red Hat AI for modernizing legacy systems at the scale that mission environments actually require. The post covered the harness pattern, the workflows the harness orchestrates, and the KPI framework for measuring success. It also explained why we run coding agents on Devstral and non-coding agents on Ministral, inside a platform that operates in disconnected environments.

Legacy software doesn't retire itself. It sits in production, accumulating technical debt, resisting change, and quietly becoming a risk—not because of what it does, but because of what it can no longer support. That's the challenge facing leading systems integrators (SIs) working in support of government and industry.