Section 08
Risk Analysis
I wouldn't bring you something without being honest about the risks. This section assumes failure and catalogs every plausible way it could happen. Every disaster below is predictable. Most are preventable.
Pre-Mortem: Why Could This Fail?
It is February 2027. Twelve months have passed since launch. The business has failed completely. What went wrong?
Risk Matrix
Risk Assessment Matrix
Top Risks (Expandable)
HIGH Catastrophic operational 1. Jake burnout / key person dependency
1. Jake burnout / key person dependency
Mitigation Strategy
Hire part-time contractor by client 6. Build deployment automation to reduce per-client hours. Document everything so others can deliver. Cap active clients at 5 for first 6 months.
Medium Catastrophic technical 2. OpenClaw project dies or pivots
2. OpenClaw project dies or pivots
Mitigation Strategy
Position platform-agnostic. Maintain capabilities across 2-3 frameworks. Fork stable branch internally. Build abstraction layers for migration within 2-4 weeks.
Medium Catastrophic technical 3. Security breach at a law firm client
3. Security breach at a law firm client
Mitigation Strategy
Zero-access architecture (team cannot see client data). Enterprise API agreements with zero data retention. Cyber liability insurance. Incident response plan. SOC 2 pursuit by Month 12.
HIGH Catastrophic technical 4. LLM hallucination causes professional harm
4. LLM hallucination causes professional harm
Mitigation Strategy
Mandatory disclaimers on all AI output. RAG architecture for all deployments. Citation verification for legal. Human-in-the-loop checkpoints. Contractual requirement for professional review.
Medium Major legal 5. Attorney-client privilege challenge
5. Attorney-client privilege challenge
Mitigation Strategy
Research and document legal framework before first client. Work with partner to create privilege-preserving architecture. Get written opinion from ethics counsel. Include explicit disclaimers in contracts.
HIGH Major financial 6. Slow sales cycle / cash flow gap
6. Slow sales cycle / cash flow gap
Mitigation Strategy
Start with partner's warm network. Offer paid assessment ($2,500-$5,000) as low-commitment entry. Require 50% upfront on all engagements. Maintain 9-12 months financial runway.
HIGH Major legal 7. Data privacy regulation exposure (HIPAA/SEC/State laws)
7. Data privacy regulation exposure (HIPAA/SEC/State laws)
Mitigation Strategy
Build compliance into deployment architecture from day one. Separate compliance checklists per vertical. Require BAAs for medical clients. Monitor regulatory changes monthly.
HIGH Major market 8. Big tech offers competing managed service
8. Big tech offers competing managed service
Mitigation Strategy
Compete on hyper-customization and white-glove service. Emphasize data sovereignty vs cloud. Target the gap between generic enterprise AI and specific professional needs.
Medium Major market 9. Hype cycle deflation
9. Hype cycle deflation
Mitigation Strategy
Undersell and overdeliver. Start with narrow high-value use cases. Build case studies showing measurable ROI. Position as realistic advisor, not hype merchant.
Medium Major operational 10. Partnership dissolution
10. Partnership dissolution
Mitigation Strategy
Operating agreement before first client with equity split, vesting, decision authority, exit provisions, dispute resolution. Monthly partner check-ins.
HIGH Major operational 11. Scope creep destroying margins
11. Scope creep destroying margins
Mitigation Strategy
Precise SOW with change order process. Fixed-scope setup phase then managed service with defined SLA. Quote 30% above estimated effort.
Low Major financial 12. API cost spikes
12. API cost spikes
Mitigation Strategy
Multi-model routing (Haiku for simple, Sonnet for standard, Opus for complex). API cost pass-through clauses. Monitor per-client spend daily. Maintain ability to switch providers within 48 hours.
Medium Major market 13. Service commoditization
13. Service commoditization
Mitigation Strategy
Differentiate on vertical expertise (legal, medical, financial). Build proprietary deployment playbooks and compliance templates. Create switching costs through deep workflow integration.
CRITICAL: Attorney-Client Privilege
ABA Opinion 512 Overview
ABA Formal Opinion 512 (July 2024) established the first comprehensive ethics guidance for lawyers using generative AI. It addresses competence (Rule 1.1), confidentiality (Rule 1.6), communication (Rule 1.4), candor (Rules 3.1/3.3), and supervisory responsibilities (Rules 5.1/5.3). Since then, Texas, New York, Oregon, and Vermont have all issued their own guidance.
The Unsettled Question
Attorney-client privilege can be waived by disclosure to third parties. When an AI system processes privileged communications through an API: Is the AI vendor a "third party" for privilege purposes? Does sending privileged information through an API constitute disclosure?
The International Bar Association has flagged: "Digital strangers in litigation: does sharing with AI breach privilege?" This is an actively contested legal question with no settled answer. Enterprise API agreements with zero-data-retention policies are widely considered acceptable under current guidance, but this has not been tested in court.
THIS MUST BE RESOLVED BEFORE FIRST CLIENT
Non-negotiable for credibility and liability. Before signing any law firm client, we need a written opinion from ethics counsel on AI systems and attorney-client privilege.
What We Need
- * Written opinion from ethics counsel
- * Architecture that enforces zero data access by our team
- * Enterprise API agreements with zero data retention
- * Legal AI Services Agreement (analogous to HIPAA BAA)
- * Documented informed consent process for law firm clients
Insurance Requirements
| Coverage Type | Annual Cost (Est.) | Coverage |
|---|---|---|
| E&O | $1.2K - $2.4K | $1M per occurrence |
| Cyber Liability | $1.8K - $3.6K | $1M per occurrence |
| General Liability | $0.3K - $0.6K | $1M per occurrence |
| Total | $3.3K - $6.6K/yr | — |
Important: The ABA has explicitly warned that professional liability insurance may NOT cover AI-related mistakes. Confirm with insurer that AI-related errors are included in E&O coverage. The cyber insurance market is currently "buyer-friendly" (2025-2026) — lock in multi-year terms if possible.
Top 5 Kill Shots
Ranked by combined probability and impact — the scenarios most likely to destroy the business:
Jake burns out while being the only technical person
Security breach at a law firm client exposing privileged data
LLM hallucination causes professional harm and lawsuit
Hype cycle deflation combined with big tech commoditization
Partnership dissolution with unresolved equity/IP disputes