Playbooks
13 AI workflows. Each one: tool stack + prompts + steps + pitfalls.
🤝Account Executive
Discovery call prep in 5 min: stack + prompt
discovery-prep · intermediate · saves ~25 min/call
Most AEs review the SDR's two-line note and call it prep. The lift on opportunity progression rate comes from systematic prep: prior history, buyer center, hypotheses on pain. AI compresses 30 minutes of prep into 5 minutes of reading.
Auto-fill MEDDIC from Gong call transcripts
meddic-capture · intermediate · saves ~15 min/call
MEDDIC fields in Salesforce are notoriously rarely filled. AEs hate the admin. Result: deal-review meetings degenerate into anecdote. AI extracts MEDDIC from Gong transcripts automatically. Quality is ~85% — AE corrects the rest in 2 minutes.
📈Account Manager
💚Customer Success Manager
Customer health score that actually predicts churn
health-scoring · advanced · saves ~saves 30%+ of preventable churn
Most health scores are garbage because they're just composites of opinions: 'usage low + ticket high = red.' Real predictive health requires regression-tested signals tied to actual churn outcomes. Build one with AI assist, not without.
AI-personalized onboarding sequences that don't feel automated
onboarding · intermediate · saves ~15 min/customer
Default onboarding sequences feel like SaaS spam. AI lets you generate one-of-one onboarding emails based on the use case the customer mentioned in sales. Lift on activation rate (defined as first value moment) is 20-35% in our experience.
QBR prep in 10 minutes (down from 4 hours)
qbr-prep · intermediate · saves ~3.5 hr/QBR
QBR prep is the single biggest time-suck for CSMs at companies with > 10 strategic accounts. Most CSMs spend 4 hours assembling product usage data, ticket history, business outcomes, and exec talking points. Claude with the right prompt + a usage dashboard pull does it in 10 minutes. The CSM then spends the saved 3.5 hours on actual customer relationship work.
⚙️Revenue Operations
AI lead scoring that beats the rules-based one
lead-scoring · advanced · saves ~saves SDRs 10 hr/week on dead leads
Most lead scoring is points-based and wrong: '+10 for opened email, +20 for visited pricing page' — calibrated by guess. AI scoring uses actual conversion data + behavioral signals + firmographic match in a regression-validated model. Result: SDRs work the top 20% of leads, not the most-recent 100.
Pipeline forecasting with AI sanity-check on each deal
forecasting · advanced · saves ~1 day/month
Forecasts are wrong because the data feeding them is wrong: AE optimism, stale stages, no MEDDIC. Adding AI as a sanity-check on each deal — comparing what the AE said vs what the data says — surfaces 15-25% of deals that need pipeline movement. Forecast accuracy improves by 5-10 percentage points.
🎯Sales Development Rep
30-second account research with Claude + Clay
account-research · beginner · saves ~20 min/prospect
The single highest-ROI workflow for any SDR. Replaces 20+ minutes of manual research with a 30-second Claude call that pulls LinkedIn + company news + earnings + 10-K snippets + funding events. Quality depends on prompt rigor — generic prompts give generic output. The version we ship below has been tuned across ~2000 accounts.
Cold email personalization at scale (without the AI-template smell)
cold-email · intermediate · saves ~8 min/email
The hard part isn't generating personalized emails; it's making them not smell like AI. The 2026 reality: prospects can tell when a first line is auto-generated within 3 words. The fix is constraint-heavy prompting that forces specificity and bans the obvious AI signatures.
AI-personalized 7-touch follow-up cadence
follow-up-cadence · intermediate · saves ~3 hrs/week
Default Outreach/Apollo cadences are templated and prospects know it by touch 3. AI can personalize each touch based on prior touch engagement (opens, clicks, replies). The lift on a 7-touch cadence is typically 1.5-2x reply rate when each touch references the prior context.
Building a 200-account ABM list with Clay + Common Room signals
list-building · intermediate · saves ~1 day
Most SDRs build lists from Apollo filters and call it a day. The 2-3x outbound performance comes from layering live signals — funding events, exec hires, product launches, community activity — on top of firmographic fit. Clay + Common Room together do this in 30 minutes.