BP2.0: OilyRag Budget
Bootstrap reality: Internal transformation on existing resources
The Reality: BP2 is About Working Differently, Not Spending More
BP2.0 isn't about hiring—it's about transforming how the existing team works. The investment is in AI tools, training, and process change. The team already has the skills; they need the right augmentation and permission to work differently.
Monthly $750 Allocation
| Category | Monthly | % | What It Buys |
|---|---|---|---|
| AI Tools | $400 | 53% | Claude Team, Copilot, automation tools |
| Training & Enablement | $150 | 20% | AI literacy courses, prompt engineering |
| Process Documentation | $100 | 13% | SOPs, runbooks, knowledge base |
| Experimentation | $100 | 13% | New tools, pilot programs, rapid tests |
| TOTAL | $750 | 100% |
The Hidden Investment: Founder Time
8 hrs/week driving transformation. This is the real cost—not the $750. But it's the highest-leverage use of founder time because it multiplies the entire team's capability.
The OilyRag AI Stack: $400/month
| Tool | Cost | Use Case | Expected ROI |
|---|---|---|---|
| Claude Team | $150 | Ticket triage, response drafting, documentation | 30% reduction in Tier 1 time |
| GitHub Copilot | $100 | Script writing, automation, code review | 2x engineer velocity |
| Zapier/Make | $50 | Workflow automation, integrations | Eliminate manual handoffs |
| Notion AI | $50 | Knowledge base, documentation, search | Faster knowledge retrieval |
| Buffer/Experiments | $50 | New tools as they emerge | Stay on cutting edge |
Transformation Phases: OilyRag Edition
Phase 1: Foundation (Month 1-2)
Get the team using AI daily. No process change yet—just tool adoption.
- • Deploy Claude Team to all staff
- • 2hr weekly AI office hours (founder-led)
- • Challenge: Use AI for 1 task per person per day
- • Measure: Track prompts/day, self-reported time savings
Phase 2: Ticket Triage (Month 3-4)
AI-assisted ticket classification and response drafting.
- • Build ticket classification prompt library
- • Create response templates for common issues
- • Implement AI-draft → human-review workflow
- • Target: 40% of Tier 1 tickets have AI-drafted response
Phase 3: Self-Service (Month 5-6)
Knowledge base + AI search reduces ticket volume.
- • Build comprehensive runbook library
- • Deploy AI-powered search for clients
- • Create client-facing AI chat (constrained)
- • Target: 20% reduction in Tier 1 ticket volume
Phase 4: Proactive (Month 7+)
AI identifies issues before clients do.
- • Anomaly detection on monitoring data
- • Predictive alerts (disk space, cert expiry, etc.)
- • Automated remediation for known issues
- • Target: 30% reduction in reactive tickets
KPIs: Efficiency Gains
| Metric | Baseline | M3 | M6 | M12 |
|---|---|---|---|---|
| Tier 1 Resolution Time | 45 min | 35 min | 25 min | 15 min |
| Tickets/Engineer/Day | 12 | 15 | 20 | 25 |
| First Contact Resolution | 60% | 65% | 75% | 85% |
| Client CSAT | 3.8 | 4.0 | 4.2 | 4.5 |
| Effective Capacity Increase | — | +25% | +50% | +100% |
Founder Time: The Real Investment
Weekly Time Budget (8 hrs)
| AI Office Hours | 2 hrs |
| Process Design | 2 hrs |
| Tool Evaluation | 1 hr |
| Metrics Review | 1 hr |
| Team 1:1s (AI focus) | 2 hrs |
Why Founder-Led
Transformation fails without executive sponsorship. The team needs to see the founder using AI, evangelizing AI, and removing barriers to AI adoption. This can't be delegated in Phase 1.
How BP2 Levers Up the Whole Beast
Frees Founder Time → More Time for GTMs
An efficient BP2 team means less firefighting for the founder. That time goes to Litebooks sales and RiskSense partnerships.
Capacity Increase → Fund Other GTMs
2x capacity without hiring saves $150K+/year in potential hires. That funds SDRs, dev work, marketing.
AI Competency → Competitive Advantage
A team skilled in AI becomes a selling point. "We use AI to deliver faster service" differentiates from commodity MSPs.
Playbook → Productizable
The BP2 transformation playbook could become a product for other MSPs. Document everything—it's future IP.
Kill Criteria: Transformation Edition
Pause & Reassess Triggers
- ⚠ M2: Team AI usage <3 prompts/person/day
- ⚠ M4: No measurable efficiency improvement
- ⚠ Any time: Team actively resisting AI tools
Accelerate Signals
- ✓ Any time: Team member builds new AI workflow unprompted
- ✓ M3: 25%+ efficiency gain measured
- ✓ M6: Client comments on improved service