cover_letter / art_22QT_-AYyYU

Dear Asana Hiring Team, Asana sits at a genuinely interesting inflection point: the Work Graph already connects goals to tasks across millions of teams, and the next logical frontier is extending that connective tissue into the operational workflows of IT, HR, and Support — the departments that resolve the work that keeps everything else moving. That intersection of structured workflow, AI-native automation, and enterprise service management is exactly where I have spent the last several years, first as a Staff PM scaling Intuit's developer platform to 675M+ engagements, and now as a founder building multi-agent orchestration systems from scratch. --- **Technical and AI Foundation** My AI/ML work is not peripheral to my product career — it is the foundation of it. In 2004 I hand-coded a backpropagation-through-time neural network in C++ for protein structure prediction; that work was accepted at NeurIPS 2014. In 2025–2026 I rebuilt that system in PyTorch, scaling from 413 to 8B parameters across five architectures, with MLflow tracking, Optuna HPO, and FastAPI serving — a 19-million-fold parameter increase that required reasoning carefully about memory, throughput, and evaluation rigor. On the agentic side, I designed and shipped OpenClaw, a multi-agent orchestration framework with a gateway protocol, subagent delegation, profile management, and session switching — coordinating AI agent workflows across real estate, insurance, health/dental, and financial-markets verticals. I also built aeval, a local-first model evaluation platform with five core eval types, adversarial safety testing, bootstrap confidence intervals, Welch's t-test, and Cohen's d effect sizing — the kind of statistical rigor that separates a demo from a production-grade AI system. These are not research prototypes; they are shipped, instrumented systems I built to solve real operational problems. At Intuit, I operated at the intersection of developer platforms and enterprise infrastructure: I delivered the ICE Self-Service platform (DevPortal, GitOps config, ICE Playground), reducing developer onboarding from 2–3 weeks to under 24 hours for production, and scaled ICE throughput from 6K to 50K TPS via rSocket migration supporting ~1.5M concurrent connections at sub-25ms TP99. I know what it means to build platform infrastructure that other teams depend on at scale. --- **Why This Role** The ESM opportunity at Asana is a 0→1 incubation inside a platform that already has distribution, trust, and a Work Graph that no greenfield competitor can replicate. The challenge — defining how IT, HR, and Support teams resolve work through AI agents tightly integrated with that graph — is exactly the kind of ambiguous, high-leverage problem I am drawn to. My arc from enterprise platform PM to multi-agent AI founder maps directly onto what this role requires: the technical depth to reason about workflow engines and agent behavior, the customer obsession to co-develop with lighthouse accounts, and the GTM instincts to position and price a new product category. **Role-Specific Connection** I am particularly interested in the differentiation thesis: Asana's right to win in ESM is not feature parity with ServiceNow or Jira Service Management — it is the Work Graph connecting a resolved ticket directly to the project, goal, and team that owns the downstream work. Designing AI agents that operate natively within that graph, rather than bolting on a ticketing layer, is a product architecture problem I find genuinely compelling. The cross-functional GTM dimension — early lighthouse accounts, channel partner onboarding, pricing and packaging for mid-market and enterprise — is also familiar territory from my Intuit years, where I worked across Sales, Support, and Marketing to drive platform adoption at scale. --- **Selected Prior Experience** - **0→1 AI product leadership:** Led end-to-end product strategy, AI development, and go-to-market execution for Vantage (AI job search and interview prep) and Fintellect (AI financial education platform), from customer discovery through App Store launch — including pricing, monetization, and iterative roadmap refinement based on real user feedback. - **Multi-agent orchestration:** Designed and shipped OpenClaw, a multi-agent gateway framework with subagent delegation, profile management, and session switching, coordinating AI workflows across four industry verticals. - **Enterprise platform scaling:** At Intuit, achieved 275% YoY growth in ICE engagements, scaling to 675M+ in FY23 across QuickBooks, TurboTax, Mint, Mailchimp, and Credit Karma; delivered ICE Self-Service platform reducing developer onboarding from weeks to hours while mitigating $1M+ in projected opex growth. - **Developer SDK and tooling:** Extended Java and Python SDK Starter Kits with scaffolding templates, build configurations (Gradle/Maven), testing frameworks, and CI/CD integration — enabling developers to go from zero to production-ready microservice in minutes. - **Search and workflow infrastructure:** At Splunk, owned Search Service (Go microservices), Search Catalog (PostgreSQL metadata), and SPL/SPL2; delivered Scheduler Service end-to-end in ~4 months and achieved up to 10x query performance improvements for a beta enterprise customer. - **AI evaluation rigor:** Built aeval with five eval types, adversarial safety testing, statistical significance testing (Welch's t-test, Cohen's d), and CI/CD regression detection — establishing the measurement infrastructure that makes AI systems trustworthy in production. - **Enterprise logging and monitoring at scale:** At Kaiser Permanente, led development and enterprise rollout of Splunk Logging-as-a-Service (1.7 TB daily volume, 200+ internal enterprise customers) and ITSI Application Monitoring-as-a-Service — directly analogous to the IT service management workflows Asana's ESM product will need to support. --- Asana's mission — enabling teams to see the larger purpose behind their work — is not abstract to me. The most underserved part of that mission is the operational layer: the IT ticket that blocks an engineer, the HR request that delays an onboarding, the support escalation that never connects back to the product team. Building AI-native service management on top of the Work Graph is the right product bet, and I would bring to it the technical depth, 0→1 experience, and enterprise platform instincts to help make it real. I would welcome the opportunity to discuss how my background maps to what you are building. Sincerely, **O. Felix Amoruwa** famoruwa@berkeley.edu | 909-731-9011 | felixamoruwa.info