Skip to main content
PILLAR ships four BUILDER preset libraries. Each contains 5 starter rules tuned for a specific go-to-market motion. All start in shadow mode with shadow_started_at = NOW(), so the 7-day promotion clock starts on first install. These libraries are conversation starters, not products. The Implementation Engineer customizes every threshold to match the customer’s actual numbers before promoting any rule out of shadow. See BUILDER configuration for the full implementation methodology.

Quick selector

Pure private-market K-12 SaaS

EdTech

AI-platform / PLG-leaning curriculum

EdTech + AI-Automation

State / local / federal seller

Public-Sector (often standalone)

Hybrid district + family-direct

Family-Literacy + Public-Sector

Public-sector with PLG signals

Public-Sector + AI-Automation

Other vertical SaaS

Closest preset + author 3–5 customer-specific rules from scratch

EdTech library (5 rules)

File: scripts/seed-builder-preset-rules.ts Best fit: Private K-12 SaaS with district-level sales motion

Public-Sector library (5 rules)

File: scripts/seed-builder-presets-public-sector.ts Best fit: State / local / federal sellers (any public-sector segment)

AI-Automation library (5 rules)

File: scripts/seed-builder-presets-ai-automation.ts Best fit: AI-product / automation-platform sales (PLG + sales-led hybrid)

Family-Literacy library (5 rules)

File: scripts/seed-builder-presets-family-literacy.ts Best fit: Hybrid district + family-direct EdTech with family-engagement signals

Why four separate libraries instead of one

Different motions have fundamentally different leading indicators and handoff paths:

Handoff-path differences

EdTech’s “MQL handoff drift” rule assumes the AE → CSM handoff. Family-Literacy uses Marketing → Enrollment Specialist. Mixing the wrong preset would seed a handoff rule that doesn’t match the customer’s actual motion.

Cron timing differences

Public-Sector’s FY-end cron uses Monday-morning timing because public RFP responses go out Mon–Wed. AI-Automation’s monthly token-cost cron runs at 9am PT because most AI customers are West-Coast-headquartered.

High-impact differences

EdTech flags exec sponsor syncs as high-impact. AI-Automation flags contract restructure conversations. Public-Sector flags board-meeting agenda touchpoints. Each library gets the right is_high_impact defaults.

Vocabulary differences

A completion_rate predicate makes sense for Family-Literacy but not pure EdTech. A committed_spend_ratio makes sense for AI-Automation but not Public-Sector. Each library uses field names that match its motion.

Stacking rules across libraries

Multiple libraries can stack on the same org. The seed scripts are idempotent on (org_id, name) — running the same library twice skips duplicates. For a family-literacy customer that sells to districts, the recommended stack is Family-Literacy + Public-Sector — the family-engagement rules cover the family-direct motion, while the public-sector rules cover RFP / FOIA / coop-purchasing exposure on the district contracts. For a curriculum-SaaS customer with product usage telemetry, the recommended stack is EdTech + AI-Automation — the EdTech base covers district sales motion + renewal cadence, while the AI-Automation rules cover usage-spike expansion + rate-limit warning + engagement-decay signals from the product telemetry.

Adding a new preset library

When a new ICP emerges (e.g. healthcare-revenue-cycle or vertical-saas-finance), the right path is to:
1

Identify the 5 most-distinctive automation patterns for that motion

2

Write a `scripts/seed-builder-presets-<icp-slug>.ts` modeled on the existing four

3

Test against a real customer's data on dev before adding to docs

4

Add a new section to this page

5

Add the preset to the implementation methodology in [BUILDER configuration](/builder/configuration)