MEGA Optimus
The optimization engine for agent pipelines.
Point MEGA Optimus at a project folder. It drafts the spec, builds the eval harness, and runs the evaluation-driven loop end-to-end — until validated gains stop coming.
The problem
Agent pipelines plateau on vibes.
Three habits keep teams stuck at the same baseline. MEGA Optimus is built to break each of them.
Brittle baselines
You can't tune what you can't measure.
Most agent pipelines ship without a reproducible score. Every change feels like an improvement; nobody knows if it generalises beyond the example that motivated it.
Hand-tuned, single-shot
Manual prompt tweaks plateau fast.
A senior engineer can lift baseline by ~10–15% with careful prompt work. After that the returns stop and the pipeline goes stale until the next model upgrade.
No validation discipline
Gains on the seed set rarely survive contact with the wild.
Without a held-out validation step you don't know if you're overfitting to the cases you happened to look at. The loop has to enforce generalisation, not just improvement.
How MEGA Optimus works
Measure. Refine. Validate.
Every change has to earn its score. The loop never closes an epoch unless gains hold up on held-out data.
Baseline measurement
Sample a stable seed set from your data and score the current pipeline. This number is the target every future iteration has to beat — no eyeballing, no anecdotes.
Evaluation-driven refinement
MEGA Optimus proposes prompt, tool, and orchestration changes, measures each one against the seed set, and only keeps the variants that move the score. Compounding wins, no regressions.
Validation gate
Before closing an epoch the run scores on a held-out validation set. Gains have to generalise — if they don't, the epoch rolls back rather than shipping a brittle local optimum.
What you get
A score you can defend.
Every run lands with a reproducible number, a full audit trail of which variant moved which slice, and a held-out validation result.
Validated lift
+18–34%
Typical task-completion improvement vs the hand-tuned baseline, measured on the held-out validation set after the loop converges.
Wall-clock per epoch
12–40 min
Hardware-dependent. Most teams see meaningful score movement in a single overnight run on the seed set, not weeks of human tuning.
Reproducibility
Deterministic
Same seed, same data, same configuration → same score. Every iteration is logged with its diff, score delta, and validation result.
Drives every major model out of the box
Stop tuning by hand. Start running the loop.
Open the demo and watch MEGA Optimus drive a real project from baseline to validated lift — no setup, no signup.