Case Study — Featured Work
Agentic Partner Management Platform
An AI agent platform on MCP that automates the operational work of managing strategic partner relationships — built solo, then scaled org-wide to 80%+ adoption.
5–8hrs
saved per SA, per week
7systems
connected over MCP
80%+
org-wide adoption
10+
contributors via code review
The problem
The job around the job: partner-facing Solutions Architects lose hours every week to meeting prep scattered across seven systems, note-taking, action-item tracking, and executive updates — time that should go to the advising that actually earns partner trust.
What it is
An AI agent platform: a Model Context Protocol (MCP) framework connecting seven enterprise systems — email, Slack, ticketing, CRM, wiki, and developer docs — with canonical workflows (20 agent skills, 24 automation hooks) and per-harness adapters, so the same workflows run in any of the four AI coding agents an SA already uses.
Capabilities
Meeting prep in seconds
Auto-pulls emails, Slack threads, tickets, and meeting history — no tab-hopping.
Automated meeting notes
Paste raw notes → formatted files with action items extracted and TODO lists updated.
Partner health checks
Scored dashboards across five categories — Technical, Delivery, Communication, Action Items, Risk — with staleness detection and trend tracking.
Executive summaries
Polished HTML dashboards ready to send to leadership, generated on demand.
COE document builder
Correction-of-error documents with interactive 5 Whys analysis and self-review.
Partner handoffs
Handoff documents that adapt for temporary coverage vs. permanent transfer.
Ticket tracking
Paste a ticket URL → auto-tracked with status updates; bulk one-click refresh with stale-ticket flagging.
Proactive date alerts
Upcoming deadlines and overdue items surfaced across all partners.
Papercuts mechanism
SAs log operational friction to a shared doc from any conversation in under 60 seconds — giving managers visibility into systemic issues.
Self-learning loop
End-of-conversation hooks prompt saving new knowledge back to the knowledge base; in-conversation awareness catches gaps in real time.
Privacy controls
Per-partner choice of shared or local-only data with a single agent command.
Platform troubleshooting
The agent reads platform docs and crash/log output via MCP to diagnose partner app issues and draft technical responses with code examples.
Adoption & community
Built solo — then turned into a team platform.
- Hands-on workshops across the US, EU, and Japan — including a 1-hour SA Summit session with two live exercises — plus weekly office hours, a knowledge hub, and self-paced labs.
- A contribution pipeline built for non-developers: an automated pre-review agent handles mechanical checks, and a 5-SA code-review pool reviews every change — 10+ contributors have landed changes.
- Five releases shipped through a structured mainline/staging release process; kanban roadmap with 20+ tracked tasks.
- 12 weeks of Monday "power-user tips" covering context management, workflow patterns, and agent optimization.
- Wiki, README, workshop guide, and self-paced exercises for ongoing onboarding; weekly office hours.
- Teammates actively contributing hooks — an email digest, a gamified stats tracker — through a maintained review process.
Outcomes
Institutional knowledge compounds — every interaction feeds the partner knowledge base.
A governed data contract requires human validation before partner data promotes to shared systems — structured records to the CRM, narrative context to a knowledge base — keeping agent output auditable.
Staleness detection catches dropped items before they become problems.
In production use across multiple strategic partner relationships.