04Capabilities · Grading + Memory

Humans teach the system what wins.

Every asset gets graded against a rubric your team built. Memory carries those judgments forward — so next week's content starts where this week's ended.

Grading + Memory · operator-controlled · auditable
01Inputs · Outputs

What goes in. What comes out.

A clean contract: real signals on the way in, structured artifacts on the way out. Every output traces back to its inputs.

Inputs
  • Rubric definition
    Criteria + weights, owned by your team
  • Sample library
    30+ approved + rejected examples
  • Reviewer grades
    Pass / revise / reject + comments
  • Performance signals
    CTR, reply, conversion per asset
Outputs
  • Grade scorecard
    Per-asset score across rubric criteria
  • Promotion decisions
    Auto-promote when threshold + diversity met
  • Memory diff
    What the system learned this week
  • Brand voice profile
    Live model of approved language
02Sample Artifact

An example, generated live.

This is the kind of structured output the module produces. Every value cites its source, every claim is graded for confidence.

Memory diff · this week
Confidence 0%
// added
17 approved phrasings · 4 hook patterns
// removed
3 deprecated phrasings · 1 outdated proof point
// confidence shift
+4% on hook generation · −2% on long-form
// reviewer notes
"Tighten openers" — applied to next 12 drafts
4 reviewers · 211 grades this weekPromoted to production →
03Integrations

Adapter-first. Sits next to what you already pay for.

The platform doesn't ask you to migrate. We ship adapters into the tools your team is already operating — read-only first, two-way when you're ready.

Slack
Inline grading + approvals
Notion
Rubric + sample library
Linear
Reviewer queue
Google Docs
Side-by-side grading
04Claim Boundary

What this module is. What it isn't.

Audit-friendly bounds. We publish what's production-ready and clearly mark what isn't. No marketing-asterisk.

This
  • Rubric is owned and editable by your team
  • Every grade is logged and auditable
  • Memory diffs reviewable before promotion
  • Reviewer-level analytics (consistency, calibration)
Not this
  • No black-box "AI scores"
  • No autonomous rubric changes
  • No memory writes without operator review
Outcomes > output

Stop publishing.
Start compounding.

See the system on your own data. Bring a campaign or a quarter of CRM — we'll show you the brief, the assets, the test plan, and what the loop would ship in week one in 30 minutes.

30 min · with your data · no slideware
0
content channels per cycle
0D
lead scoring · fit · engagement · intent
0
live data adapters · GA4 · GSC · Firecrawl · Mailgun · LinkedIn
Daily
crew run cadence