Systems in production. Outcomes you can measure.
Every engagement follows the Hendricks Method: study the operations, build the agents, deploy the system, manage it in production. Below are three deployments running today. Real systems, real numbers.
Autonomous campaign operations across five locations
A multi-location workspace company operating across 5 locations in Texas.
Google Ads campaigns across 5 locations, different budget allocations, Search and Performance Max. Each location required independent budget discipline, every dollar deployed, no spend ever crossing location boundaries. Manual monitoring consumed hours per week. Performance shifts went undetected for days.
- →Deployed autonomous Google Ads management agents across all 5 locations with hard-coded guardrails enforcing per-location budget rules
- →Real-time anomaly detection that flags performance shifts before they impact spend efficiency
- →Zero-sum budget reallocation within each location, shifting spend toward whichever campaign type converts better
- →Paid-organic bridge: high-converting paid queries become organic content targets automatically
- →Automated weekly intelligence briefings covering spend, conversions, and anomalies across all locations
“We went from spending hours every week watching dashboards to having a system that watches everything for us and only surfaces what actually needs a human decision.”
Operations Lead
Multi-client autonomous Google Ads management
A digital marketing agency managing Google Ads for multiple clients across different verticals.
3 clients, Demand Gen + Performance Max + Search + Video, $5K+ per day in ad spend. The agency owner was spending 10+ hours per week checking performance, adjusting bids, monitoring budgets, adding negative keywords. Every new client scaled the workload linearly. Needed automation with tight guardrails.
- →Built a multi-client autonomous Google Ads agent monitoring, analyzing, and executing optimizations across all accounts from a single system
- →Per-client guardrails stored in Firestore: tCPA floors and ceilings, maximum change percentages, cooldown periods, daily execution limits
- →Every optimization follows a strict protocol: validate guardrails, read state, execute, log full audit trail with before/after and rollback
- →Agent handles tCPA adjustments, budget reallocation, and negative keyword management within defined limits
- →Anything outside guardrail boundaries escalates to a human, the system knows what it can and cannot do
“I was spending 10 hours a week manually checking dashboards and tweaking bids. Now the agent handles it and I only get involved when something genuinely needs a strategic decision.”
Agency Owner
Autonomous content engine for thought leadership
A professional services firm building thought leadership across two brands.
Maintaining consistent thought leadership content across two separate websites while the founding team focused on client work. Content creation was sporadic, weeks would pass between publications. The firm needed daily, high-quality content without adding headcount or diverting the founder from revenue-generating work.
- →Built an autonomous content engine that generates, publishes, and promotes articles daily, with zero manual intervention
- →AI selects topics from defined content pillars aligned with the firm's positioning and audience
- →Generates long-form articles with original hero images
- →Auto-publishes to both websites via direct repository integration (Vercel auto-deploys on push)
- →Creates LinkedIn and X social post drafts for review
- →Sends daily email briefing summarizing what shipped
“We went from publishing once or twice a month, when we could find the time, to fresh, relevant content every single day.”
Founder
20 minutes. Walk away with the line your firm needs.
We will look at your operation, tell you exactly which assembly line would ship first, what it would cost, and how long it would take. If it is not a fit we say so on the call.