RSI Benchmark — March 2026
Intelligence That Compounds
Reverse engineering the factors behind content performance — uniquely for each company.
+47%
accuracy gain over
self-improving agents
self-improving agents
1,000+
unique performance indicators
across 100s of companies
across 100s of companies
~12%
learning rate acceleration
per round on average
per round on average
2 wks
to first compound
learning cycle
learning cycle
How our agent learns what works for your company
Every 2 weeks, it runs this cycle on your content performance data
01
Train
On your existing content performance data
02
Hypothesize
Run evidence-backed SEO & GEO campaigns
03
Analyze
What worked, what didn't, and why
04
Learn
What factors & patterns actually matter for you
↻Adds, removes & re-weights ranking factors each round
Compounding vs. Static
Opus 4.6 · same data · 20 weeksL0Single-Pass AgentL1Self-Improving AgentL2Recursive Compounding
Prediction Accuracy Over Time10 rounds · 2 weeks each
Content performance prediction across AI search surfaces. Our agents compound their learning — by R10 (Wk 20), recursive compounding reaches 73%, self-improving hits 46%, single-pass plateaus at 29%.
Different companies. Different blind spots.
Hover the indicators to see how the rubric evolves at each round.
Unified HR, payroll & benefits platform
68% final · baseline 31%
CompoundingBaseline2 ▾Hover for changes
Rubric · R10 (Wk 20)
Hub-spoke topic clusters16%
Internal linking patterns driving topical authority
Content recency16%
Payroll law changes drive ranking boosts within 48hrs
Editorial depth14%
Commercial intent alignment13%new
AI Overviews absorb informational — pivot to buyer queries
Payroll calculator interactivity12%
Interactive tools outperform static guides 2.4×
Technical SEO10%
State payroll compliance pages10%
Pages covering state-specific payroll rules
Backlink authority5%
Core Web Vitals4%
What blind spots is your company missing?
Every company has factors that generic tools can't see.