Phase 6: Maintenance & Strategic Refinement (Points 86–100)
Point 86: Hallucination Mitigation: Implement a "Faithfulness Metric" to ensure the agent doesn't invent job requirements.
Weaknesses: Metrics like RAGAS are compute-heavy; no real-time enforcement.
Opportunities: Self-consistency checks (multiple generations), with rollback on failures.
Point 87: Data Provenance Tagging: Mark all leads as "Primary" (SEC/WIPO) or "Secondary" (Media/Social) to maintain Donovan-level rigor.
Weaknesses: Tagging manual-prone; hybrids blur lines.
Opportunities: Automated via source metadata, with query filters for purity levels.
Point 88: Security Audit: Regularly rotate the API keys and credentials stored in OpenClaw's YAML config files.
Weaknesses: YAML plaintext risky; audits infrequent miss drifts.
Opportunities: Vault integration (e.g., HashiCorp), with weekly scans via Trivy.
Point 89: Prompt Optimization: Use "Chain of Thought" or "Tree of Thoughts" for complex matching logic.
Weaknesses: Increases token costs; ToT can explode combinatorially.
Opportunities: Pruned ToT with beam search, benchmarked on custom eval sets.
Point 90: Local Vector Search: Use ChromaDB or Pinecone locally to index your growing archive of company research.
Weaknesses: Local Pinecone not truly local (cloud?); index drift without refreshes.
Opportunities: Qdrant for hybrid search, with upsert hooks on new data.
Point 91: Model Drift Monitoring: Set an alert if the agent's "Match Accuracy" falls below 90%.
Weaknesses: Accuracy hard to ground-truth; alerts fatigue if noisy.
Opportunities: Canary tasks (known leads) for ongoing eval, with auto-retrain triggers.
Point 92: Adversarial Testing: Occasionally "feed" the agent fake, low-quality jobs to ensure its filters are working.
Weaknesses: Fakes may poison memory if not isolated; limited coverage.
Opportunities: Dedicated test suite in Pytest, with coverage reports on filter branches.
Point 93: Ethical Guardrails: Configure the agent to never scrape data from private password-protected employee areas (staying within OSINT limits).
Weaknesses: Guardrails bypassable via skill mods; no logging for audits.
Opportunities: Constitutional AI prompts, with ethical review checklists per phase.
Point 94: Human-in-the-Loop (HITL) Scaling: Only automate outreach for "Short-term Gigs"; keep 6-month and co-founder roles as "Manual Send" only.
Weaknesses: Scaling HITL creates bottlenecks as volume grows.
Opportunities: Delegate low-stakes to semi-auto (drafts only), with escalation queues.
Point 95: Docker/K8s Deployment: Package your OpenClaw setup in a Docker container for "One-click" migration if you need to scale to a cloud NPU.
Weaknesses: K8s overkill for solo; container bloat from deps.
Opportunities: Slim base images with multi-arch builds, Helm charts for cloud deploys.
Point 96: Temporal Fact Tracking: Use Graphiti to track how a company's tech stack evolves over months to catch the "pivot" point.
Weaknesses: Evolution signals weak without baselines; graphs memory-intensive.
Opportunities: Delta queries for change detection, alerting on >20% stack shifts.
Point 97: Source Provenance Policy: Establish a policy that mandates human validation before any "Synthetic Data" is added to your core ICP.
Weaknesses: Human validation slows; synthetics useful for gaps.
Opportunities: Tiered validation (low-risk auto), with provenance blockchain for audits.
Point 98: Continuous Benchmarking: Measure "Time Saved" and "Response Rate Improvement" monthly to justify the infrastructure cost ($5–$10/day in tokens).
Weaknesses: Metrics self-reported biased; ignores opportunity costs.
Opportunities: Automated dashboards in Grafana, with cohort comparisons to manual baselines.
Point 99: Keel of the Ship: As Donovan advised, "Lay the keel" by starting with one narrow skill (e.g., SEC monitoring) before building the full mesh.
Weaknesses: Phased rollout risks incomplete value early; motivation dip if slow wins.
Opportunities: MVP loops with user stories, celebrating micro-milestones like first alert.
Point 100: The Strategic Individual: Conduct a monthly "Self-Intelligence Audit" to ensure your private network is providing a definitive information advantage over the "Mass Media" public.
Weaknesses: Audits subjective; no quantifiable "advantage" metric.
Opportunities: Score via lead conversion rates vs. public sources, with network health KPIs like intro success.