Every engineering team is shipping AI agents. Few can guarantee they'll work reliably next month. Agents are probabilistic, session-dependent, and drift silently. Models update, distributions shift, and the agent your team shipped last quarter isn't the agent running in production today. Most teams find out something is wrong only when users complain.

The root cause is always the same: no systematic way to measure, diagnose, and improve agent performance. Teams fall into one of three patterns: generic dashboards that create false confidence, reactive prompt rewrites that fix one thing and break another, or endless model swaps with no measurement of whether anything actually got better. An eval platforms tell you what's wrong, but someone still has to fix it.

MEGA Code closes that loop. We're an agent optimization infrastructure. We built rigorous, eval-driven infrastructure because optimization demands it. The loop runs automatically: eval, optimize, improve, feed back into the next session. Every success, every failure, every session compounds into a smarter agent. No manual intervention. No thrashing. No whack-a-mole.

If you're building agents and care about what they become, and not just what they do today, we're building the infrastructure for that.

MEGA Code

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MEGA Code

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