Case studies from the production floor.

Context & Problem

A mid-size ecom operator had been 'launching' their DTC platform for 9 months. Three different teams had touched it. Nobody owned the dependency map. Customers were onboarding through a mix of email, spreadsheets, and Slack messages.

Constraints

• Legacy monolith with undocumented APIs
• Rotating engineering team with no onboarding docs
• Compliance requirements baked into manual processes
• Multiple payment processor integrations in various states of completion

What Changed

• Mapped all 47 dependencies and identified 12 circular blockers
• Established clear ownership model: one team, one backlog, one definition of 'done'
• Built doc collection + verification workflow with status visibility for customers
• Automated 3 manual compliance checks without breaking audit trail

Outcomes

• Portal shipped in 6 weeks after 9 months of stalling
• Customer onboarding time reduced from ~14 days to ~3 days
• Support ticket volume related to onboarding status dropped 60–70%
• Internal team velocity improved with clear ownership and fewer handoffs

Context & Problem

A multi-channel ecommerce operator couldn't answer a simple question: 'What did we actually make last month?' Orders came from Shopify, Amazon, and a wholesale portal. Payments went through Stripe and a legacy processor. COGS lived in a spreadsheet. Inventory counts were 'approximate.'

Constraints

• Five data sources with different schemas and update frequencies
• Historical data with known gaps (no one knew which gaps)
• Finance team running manual reconciliation every month-end in Excel
• No engineering capacity — had to work with existing systems

What Changed

• Built a reconciliation engine that ingested all five sources nightly
• Created drift detection: alerts when order counts, payment totals, or inventory diverged beyond tolerance
• Automated COGS calculation from supplier feeds + landed cost rules
• Replaced the monthly Excel ritual with a live dashboard with drill-down

Outcomes

• Month-end close went from 8–12 days to 2 days
• COGS accuracy improved from ~85% to ~97%
• Identified ~$40K–60K in annual revenue leakage from unreconciled transactions
• Finance team got 3 days/month back from manual reconciliation

Context & Problem

A SaaS platform wanted to 'add AI to support' after seeing a demo. They'd already tried bolting a chatbot onto their help center — it hallucinated answers, leaked internal pricing, and frustrated customers. The support team had lost trust in automation entirely.

Constraints

• Support team skeptical of any AI after failed chatbot attempt
• PII and pricing data in knowledge base required strict access controls
• High ticket volume (~2,000/week) with complex product-specific questions
• No existing tagging or categorization system for tickets

What Changed

• Scoped to one use case: auto-categorize and route tickets, not auto-respond
• Built classification model with confidence thresholds — low-confidence tickets go to humans
• Added guardrails: no PII in model context, no pricing in auto-responses, cost caps per request
• Created logging dashboard so support leads could review AI decisions daily

Outcomes

• Ticket routing accuracy: 87–92% (vs. 60% from previous manual tagging)
• Average first-response time dropped 40–50%
• Support team became advocates — started requesting more AI tools
• Monthly AI cost: ~$200–400 (with budget alerts if it spikes)

Context & Problem

Co-founded Sixpack Shortcuts as CTO and built the entire tech stack from zero — ecommerce platform, subscription billing, upsell funnels, and a media buying operation that scaled to ~$1M/month. Simultaneously grew a YouTube channel to ~3M subscribers through systems-driven content ops.

Constraints

• Bootstrapped tech team with no existing infrastructure
• Rapid scaling from $0 to $1M/mo ad spend required real-time performance visibility
• Subscription churn and billing complexity across multiple product lines
• Content production at scale needed repeatable systems, not one-off efforts

What Changed

• Built custom ecommerce platform with subscription management and upsell engine
• Created real-time media buying dashboards for campaign performance and ROAS tracking
• Designed content ops system that scaled YouTube output to ~3M subscribers
• Built a phone sales department from scratch that hit ~$1M in its first month

Outcomes

• Media spend scaled to ~$1M/month with full performance visibility
• YouTube channel grew to ~3M subscribers
• Phone sales department generated ~$1M in first month
• Tech and ops infrastructure supported multi-year growth trajectory

Context & Problem

Dollar Beard Club was growing fast but the backend couldn't keep up — subscription logic was fragile, fulfillment was manual, and customer lifecycle data lived in silos. The team needed systems that could scale with viral growth without falling apart.

Constraints

• Viral traffic spikes required infrastructure that wouldn't buckle
• Subscription billing logic spread across multiple tools with no single source of truth
• Fulfillment coordination between warehouse and customer-facing status was manual
• Customer support had no visibility into order or subscription state

What Changed

• Consolidated subscription management into a unified billing and lifecycle system
• Built automated fulfillment pipeline with real-time status visibility
• Created customer health dashboards connecting LTV, churn, and support signals
• Implemented scalable infrastructure to handle traffic spikes without downtime

Outcomes

• Subscription infrastructure scaled reliably through viral growth periods
• Fulfillment errors reduced significantly with automated pipeline
• Customer support response time improved with unified order visibility
• Churn reduced through better lifecycle tracking and intervention triggers

Context & Problem

A group of supplement brands were each running their own tech stacks, fulfillment processes, and customer support workflows. Margins were leaking through duplicated tooling, inconsistent COGS tracking, and zero cross-brand visibility into what was actually working.

Constraints

• Multiple brands with different platforms, SKUs, and fulfillment partners
• No unified view of inventory, COGS, or margin across the portfolio
• Each brand had its own support queue with no shared knowledge base
• Ad spend attribution was brand-level only — no portfolio-level optimization

What Changed

• Built a unified ops layer connecting inventory, orders, and COGS across all brands
• Consolidated support workflows with shared escalation paths and cross-brand visibility
• Created portfolio-level dashboards for margin, LTV, and ad spend performance
• Standardized fulfillment processes to reduce per-brand operational overhead

Outcomes

• Portfolio-wide margin visibility enabled smarter capital allocation
• Operational costs reduced by consolidating duplicated tooling and workflows
• Cross-brand inventory visibility prevented stockouts and overordering
• Support efficiency improved with unified queue and shared playbooks

Context & Problem

Job Crusher was an online training community and course center built to teach real-world marketing skills — from media buying to funnel building to paid traffic. The goal was to create a scalable education platform that could onboard students, deliver structured curriculum, and foster an active community without relying on manual cohort management.

Constraints

• Course delivery needed to scale without 1:1 instructor involvement
• Community engagement had to be built into the platform, not bolted on
• Student progress tracking and completion rates required real-time visibility
• Payment and subscription management across multiple course tiers

What Changed

• Built a course platform with structured modules, progress tracking, and certification workflows
• Created a community layer with discussion forums, live Q&A, and peer accountability systems
• Implemented subscription billing with tiered access and upsell paths to advanced training
• Designed onboarding flows that reduced time-to-first-lesson and improved completion rates

Outcomes

• Scaled student enrollment without proportional increase in support overhead
• Community engagement drove organic retention and word-of-mouth growth
• Course completion rates improved with structured progress visibility
• Recurring revenue stabilized through subscription model and tiered offerings