One Agent, an Assembly Line, or Agent + Editor? We Built the Same AI Agent 3 Ways
Does architecture matter more than model choice? We built the same Reddit-posting agent three different ways, ran 8 model mixes through a 14-criteria AI judge panel, and the most expensive configuration lost twice. Here is the full scoreboard.
Everyone argues about which model to use. Almost nobody tests which architecture to use. So we built the same Reddit-posting agent three different ways, ran 8 model mixes across them, and graded every run with a 14-criteria AI judge panel. The most expensive configuration lost. Twice.
The three architectures
Same job in all three: read a set of source pages, write 4 publish-ready Reddit posts with a target subreddit and a real image, and obey each community's rules. What changed is how the work is split:
The setup
Every configuration ran on the same 3 dataset samples (each a set of live source pages), and every post was graded by the same judge panel: Claude Opus 4.8 scoring 14 criteria, 0–1 each, with browsing enabled so it verifies claims against the actual source pages. Criteria include content value, community compliance, human voice, engagement potential, originality, and whether a real image was attached. All of it ran as Evaligo experiments with a cost cap.
All 8 configurations, ranked
| Setup | Judge score | Human voice | $ / post |
|---|---|---|---|
| Assembly line · Opus writes, mini rest ★ best score per dollar |
85.5% | 0.73 | $0.04 |
| Agent + editor · mini writes, Opus edits | 85.4% | 0.77 | $0.23 |
| Assembly line · Sonnet writes, mini rest | 85.2% | 0.67 | $0.04 |
| Agent + editor · Opus writes, mini edits ★ best human voice of any strong setup · what our template ships |
84.6% | 0.88 | $0.10 |
| Assembly line · Opus everywhere priciest of its group — 3rd of 4 |
84.1% | 0.50 | $0.24 |
| Agent + editor · Opus writes, Opus edits priciest of its group — 3rd of 4 |
83.0% | 0.52 | $0.49 |
| Assembly line · mini everywhere | 82.3% | 0.60 | $0.02 |
| Agent + editor · mini writes, mini edits cheapest — and the most human voice of all |
80.9% | 0.90 | $0.01 |
3 samples per configuration, 4 posts per run. “$ / post” is the flow cost only. Judge score = the average of all 14 criteria.
5 things we learned
“Best model everywhere” lost twice.
Opus-on-every-step finished 3rd of 4 in both architectures, at up to 13× the winner's cost.
Expensive setups sound the least human.
All-premium configs scored 0.50–0.52 on the human-voice judge; the cheapest scored 0.90. Over-polish reads as AI.
Routing beats brute force.
The strong model only on the step that moves quality: higher score than all-premium at 84% lower cost, about $0.04 per publish-ready post.
Sometimes the prompt is the bottleneck, not the model.
The assembly line's human-voice score was stuck near 0.40 through several model upgrades. What fixed it was a prompt change: hard 150-word cap, topic in the first sentence. Same models, +45 points on voice.
The cheap floor is surprisingly high.
Mini-everywhere landed at 81–82% for $0.01–0.02 a post: fine for volume drafts, wrong for the posts that represent you.
Bottom line: pick the architecture first, then route models per step. We ship the agent + editor setup with a strong writer and a cheap editor — statistically tied with the top score and the best human voice of any strong config. It's a ready-made template you can run in minutes.
Method notes, honestly
Three samples per configuration is enough to expose the big gaps (single runs wobbled a few points, which is exactly why we averaged), but the 1-point differences at the top of the table are ties, not rankings. The judge is a single model (Opus 4.8) applying written criteria; a different judge would shift absolute numbers, though in our earlier checks the ranking held. Every experiment, judge goal, and cost figure in this post came straight from the Evaligo experiment reports — the same feature you can point at your own flow.
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