AI & dataPolicy engines, evaluations, ingestion, and enterprise platforms
Chapter 01
Applied AI & Intelligent Agents
Production evaluation pipelines, automated drift detection, and runtime permission controls.
Spctre: Open-Core AI Policy & Control Engine
Architected an open-core policy engine for AI agents that lets engineering teams define, test, and enforce runtime boundaries on tool calls across multiple languages and frameworks (MCP, Node, Go, Python).
What it producedSub-millisecond evaluation in local Rust benchmarks · identical semantics across Node, Go, and WASM
Why it mattered & architecture
Why it matteredPrevents rogue actions and financial liability by intercepting unverified tool calls before changes happen; streams verifiable audit records to SIEMs (Splunk, Sentinel) for compliance.
Core ArchitectureCore rule evaluation in Rust (exposed via C ABI and napi-rs) shared across a Go background worker, Next.js dashboard, and WASM adapters, backed by Postgres RLS and SHA-256 hash-chain audit logs.
RustGoTypeScriptNext.js 16PostgreSQLOpenAPI 3.1MCPDocker
ML Platforms & EvalRelease gate for every model
ML Model Evaluation & Drift Monitoring Platform
Jungle Scout (VP era). Owned product strategy for the embedded data science team — setting the accuracy thresholds, regression test suites, and data drift monitors that gated what models were allowed into production.
What it producedSet the accuracy bar and the drift monitors that gated what reached production
Why it mattered & architecture
Why it matteredPrevented hallucinated predictions and silent model degradation under heavy production traffic before errors reached customer analytics dashboards.
Core ArchitectureAutomated evaluation pipelines measuring baseline feature shifts, semantic distance in query embeddings, and input boundaries before scoring live queries.
PythonPyTorchscikit-learnnumpyMLflowFastAPI
Agentic WorkflowsRan nightly without an analyst
Multi-Agent Competitor Intelligence Pipeline
Jungle Scout (VP era). Directed an automated pipeline of specialized AI agents that tracked competitor catalog changes, analyzed customer review sentiment trends, and summarized brand opportunities.
What it producedReplaced manual competitor tracking with a pipeline that ran unattended
Why it mattered & architecture
Why it matteredReplaced manual competitive research with automated nightly analysis, turning messy marketplace data and review sentiment into structured merchandising briefs.
Core ArchitectureCentral coordinator delegating to web-search agents, parallel sentiment classifiers, and vector search over product reviews.
PythonLangGraphOpenAI APIWeaviateFastAPI
Generative Catalog Scale1,000s of SKUs a day
AI Catalog Optimization & Copy Generation Engine
Jungle Scout (VP era). Set the quality and release standards for an automated catalog copy engine that ingested product specs, matched brand tone guidelines, and generated SEO-optimized Amazon listings.
What it producedThousands of SKUs a day, each gated by factual-consistency checks before publish
Why it mattered & architecture
Why it matteredCut listing optimization turnaround from hours to minutes for large merchants, with automated verification steps to ensure factual accuracy and brand voice alignment.
Core ArchitectureBrand tone matching via customized vector embeddings, parallel prompt assembly, and automated fact-checking steps to catch unsupported claims before publication.
PythonLangChainClaude APIPostgreSQLCelery
Chapter 02
Enterprise Data & Platform
High-concurrency marketplace ingestion, secure Snowflake data sharing, and the multi-tenant analytics platform enterprise brands query against.
Data Platforms & APIs$50B+ in transaction volume
High-Throughput Commerce Ingestion Engine
Designed streaming data pipelines and high-throughput seller analytics APIs that fed real-time pricing and demand forecasts across $50B+ in Amazon marketplace transactions.
What it producedReal-time ingest across $50B+ in Amazon transaction volume
Why it mattered & architecture
Why it matteredAllowed enterprise brands and sellers to react immediately to supply-chain shifts and demand surges with reliable, fresh market data.
Core ArchitectureEvent-driven stream processing, AWS Kinesis ingestion streams, and read-optimized columnar storage configurations.
JavaScalaAWS KinesisPostgreSQLAWS
Enterprise Analytics$50M+ ARR portfolio
Jungle Scout Enterprise SaaS Platform
Led product and architecture strategy for enterprise e-commerce tools, implementing multi-tenant permissions, secure Snowflake data sharing, and high-concurrency CSV processing pipelines.
What it produced$50M+ ARR portfolio · Snowflake data sharing launched for enterprise accounts
Why it mattered & architecture
Why it matteredWon more enterprise accounts while holding 100%+ Net Dollar Retention, and shipped Snowflake data sharing for them.
Core ArchitectureZero-copy Snowflake data shares, high-throughput analytical query optimization, and RBAC auth layers.
Ruby on RailsSnowflakeReactOAuth 2.0
Commercial productsPricing, retail media, seller tools, and mobile applications
Chapter 03
Commercial Systems: Pricing & Retail Media
What the platform charged for and how it was packaged: usage metering, multi-product attach, and the retail media products agencies and brands bought.
Monetization & Packaging100%+ net dollar retention
Enterprise Pricing, Packaging & Monetization Architecture
Restructured legacy all-inclusive pricing tiers into a modular, value-metric API and data platform packaging model, so customers paid in proportion to the data they actually used, including via Snowflake data shares.
What it producedEnterprise ARR Expansion | Multi-Product Attach | 100%+ NDR
Why it mattered & architecture
Why it matteredExpanded enterprise SaaS and data platform revenue, accelerated multi-product attach, and sustained 100%+ Net Dollar Retention across enterprise accounts.
Core ArchitectureMulti-tier usage metering, modular API quota enforcement, grandfathering transition cohorts, and CPQ-to-billing automated reconciliation pipelines.
Stripe BillingSnowflakeSalesforce CPQPostgreSQLData Warehousing
Retail Media Optimization & Ad Automation
Jungle Scout (VP era). Product leadership for retail media after the Downstream Impact acquisition: optimization and automation for agencies and brands running Amazon and Walmart DSP campaigns, plus Amazon Marketing Cloud and Sponsored TV measurement.
What it producedAgencies including WPP on the platform · direct partnership with Amazon Ads and Selling Partner teams
Why it mattered & architecture
Why it matteredAgencies and enterprise brands could plan, optimize, and measure ad spend against the same commerce data driving their merchandising decisions, instead of reconciling two separate pictures of the same market.
Core ArchitectureAmazon Marketing Cloud clean-room query pipelines, DSP campaign automation, and unified reporting joined to the commerce data warehouse.
Amazon Marketing CloudAmazon DSPWalmart DSPSnowflakeREST APIs
Chapter 04
SMB Products & Client Applications
Self-serve seller software, browser extensions with service-worker caches, and the native iOS and Android SDKs behind in-store wayfinding.
Indoor Location Intelligence$3M in new contracts
Spatial Retail Pathfinding & BOPIS Infrastructure
Engineered indoor location intelligence and automated wayfinding route-compilers using Apache Solr spatial indexing and native Android & iOS SDK integrations to connect shopper intent with in-store shelf inventory and BOPIS systems.
What it produced8/8 retail pilots converted to multi-year enterprise contracts | 150M+ sq. ft. mapped | CDP targeting (LiveRamp) for Target and Lowe's
Why it mattered & architecture
Why it matteredWon $3M in new enterprise contracts and put Buy Online, Pick Up In-Store (BOPIS) fulfillment into production at major retail brands.
Core ArchitectureA* and Dijkstra routing variants optimized for multi-level indoor topological graphs, Solr-based spatial indexing, geo-fences, and native iOS & Android local asset synchronization.
Node.jsApache SolrAndroid SDKiOS SDKPostgreSQL/PostGISRedis
Growth-Stage Analytics600K+ merchants
Jungle Scout SMB SaaS Suite
Directed the core seller product suite, scaling relational database search performance, listing optimization score algorithms, and real-time keyword analytics products for global sellers.
What it produced600K+ Active Sellers | $50M+ ARR scale
Why it mattered & architecture
Why it matteredSupported self-serve growth across 600K+ global merchants while maintaining fast sub-second search latency and high conversion onboarding funnels.
Core ArchitectureOptimized multi-million row Elasticsearch indexes, cached database query loops, and intuitive data visualizations.
Ruby on RailsElasticsearchPostgreSQLReact
Browser Extension & Scraping100K+ installs
Seller Intelligence Chrome Extension
Built a lightweight browser extension that let sellers validate a product on the page they were already looking at, with fast DOM parsing and asynchronous backend calls.
What it produced100K+ active installs · fast enough to use mid-browse without breaking flow
Why it mattered & architecture
Why it matteredBecame a daily-use tool for sellers, drove product-led signups, and attached at high margin.
Core ArchitectureFast Manifest V3 background service-workers, client-side DOM-scraping engines, token caches, and rate-limited API handlers.
JavascriptManifest V3Chrome Extensions APIWebpack
Platforms & teamsOpen-source operating systems and the organizations behind delivery
Chapter 05
OS Platforms & Infrastructure
AOSP customizations and kernel work, device bringup across 100+ hardware architectures, and the release, licensing, and privacy discipline that kept it shippable.
Operating Systems & AOSP10M+ CM · 3.0M+ LineageOS installs
CyanogenMod & LineageOS Core Platform
Architected low-level AOSP customizations, kernel-level power and concurrency configurations, and the distributed build automation behind CyanogenMod, which grew to 10M+ installs, and its LineageOS successor.
What it producedCyanogenMod 10M+ installs · LineageOS 3.0M+ active installs across 109 supported device models
Why it mattered & architecture
Why it matteredAn Android distribution that kept running on hardware its manufacturers had stopped supporting, extending the usable life of millions of devices rather than retiring them.
Core ArchitectureLow-overhead C/C++ memory abstractions, modular platform services, and multi-region distributed compilers.
C/C++AOSP KernelAndroid SDKGit/Gerrit
Device Platform & Maintainership109 devices · 100+ architectures
Device Bringup & Global Maintainer Network
Ported Android onto boards it was never shipped for, worked through the kernel and vendor-blob constraints each device presented, and kept that support alive across release cycles rather than landing it once. As the platform scaled, coordinated maintainers across 100+ hardware architectures.
What it produced109 supported device models · 100+ hardware architectures · device trees, kernel sources, and the per-device maintainer record public in git
Why it mattered & architecture
Why it matteredDevice support that survived past the point where its manufacturer walked away, maintained by a distributed volunteer network rather than a single team.
Core ArchitecturePer-device device trees and kernel sources, vendor-blob extraction and shimming, and Gerrit-based review across a distributed maintainer network.
AOSP KernelC/C++Device TreesGit/Gerrit
Open-Source GovernanceMonthly security patches, sustained
Release Cadence, Licensing & Privacy Compliance
Ran platform releases, monthly security patches, and CVE fixes across a global maintainer community, and owned open-source licensing compliance across a large multi-vendor codebase — tracking obligations for every component shipped.
What it producedMonthly patch cadence sustained across 109 devices · license obligations tracked for every shipped component
Why it mattered & architecture
Why it matteredPrivacy controls and license compliance were product requirements, not afterthoughts: user control over data collection and permissions held as a product pillar as European privacy rules tightened. It is the same discipline the AI governance work runs on now.
Core ArchitectureScheduled release trains, CVE tracking and backports across supported branches, per-component license obligation tracking, and user-facing permission controls.
AOSPGit/GerritCVE TrackingOSS Licensing
Chapter 06
Product Leadership, UX & Process
Cross-functional team topologies, dual-track agile discovery loops, design system governance, and data-driven product management operations.
Team Topology & ProcessCycle time down 40%
Cross-Functional Squad Topology & Discovery Loop
Designed and implemented a customer-centric dual-track agile framework and modular squad topology to accelerate feature discovery and align PM, UX design, and Engineering workflows.
What it producedFeature discovery cycle time down 40% · demand validated before engineering capacity was committed
Why it mattered & architecture
Why it matteredReduced product cycle times by 40% and elevated discovery-to-delivery validation confidence to over 90% across distributed global teams.
Operating FrameworkDual-track agile discovery (continuous customer research + rapid validation), cross-functional squads mapped to customer journeys, and collaborative Figma-to-production design pipelines.
FigmaJira/Confluence
UX Design & SystemsHandoff time cut 50%
Design System Governance & Enterprise UX Alignment
Established a centralized UI/UX design system and governance workflow to unify multiple disparate enterprise product portals, guaranteeing consistent user experiences and reusable component libraries.
What it producedShared component library and review guild across previously fragmented portals
Why it mattered & architecture
Why it matteredCut design-to-development handoff time in half and eliminated UI inconsistencies across fragmented enterprise acquisitions.
Operating FrameworkAtomic design principles, cross-team design review guild, automated Figma-to-code token sync pipelines, and localized usability testing protocols.
FigmaToken StudioStorybookReactWeb Accessibility (a11y)
M&A Integration & Strategy15K+ accounts migrated · 0 lost
Post-Merger Customer & Platform Integration (Downstream into Cobalt)
Directed post-acquisition product and data integration of Downstream Impact into Cobalt enterprise suite, consolidating unified data pipelines, ad-tech automation, and cross-sell roadmaps.
What it produced15,000+ Ad Accounts Migrated | 6-Month Timeline | 0 Accounts Lost
Why it mattered & architecture
Why it matteredMigrated 15,000+ enterprise advertising accounts in 6 months with no accounts lost in migration, consolidating retail media reporting onto one platform.
Operating FrameworkDual-write data ingestion bridges, automated tenant mapping services, unified RBAC credential federation, and phased zero-downtime migration scripts.
AWSOAuth 2.0SnowflakePostgreSQLReactREST APIs
Product Operations & GrowthSelf-serve activation up 22%
Data-Driven Product Management & Growth Loops
Engineered data instrumentation governance and operational cadences using Amplitude and Mixpanel to map customer activation funnel leaks and optimize product-led onboarding.
What it producedSelf-serve activation up 22% · board-level visibility into retention cohorts
Why it mattered & architecture
Why it matteredIncreased self-serve onboarding activation rates by 22% and established board-level operational visibility into product retention cohorts.
Operating FrameworkProduct-led growth (PLG) loops, cohorts/retention mapping, A/B testing frameworks, and weekly operating analytics cadence.
AmplitudeMixpanelSegmentOptimizelySQL