Pisgah Forest, NC

Sam
Schuemacher

I consult selectively, run a market garden that supplies fresh produce to my community and brings me into local schools to deliver talks on the intersection of tech, sustainability, and agriculture, and am building a life skills course with my bestie, all at once, all on AI systems I direct: I specify the architecture, debug the failures, and let AI implement it. My edge is operational leverage that actually ships.

AI Systems Builder Consultant, Technology Advisory Operator, Schuelace Farms Creator, Own Your Life

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Sam Schuemacher

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About

Operator who builds
his own tools.

I'm a consultant, farmer, and builder based in the Blue Ridge Mountains of Western North Carolina. I advise financial firms on AI governance and technology adoption, run a microgreens operation, and am building an online life skills course for the next generation, all at the same time.

My relationship with AI isn't theoretical. I direct the systems I run my work on, from the assistant that writes my daily brief to the automation layer that keeps three businesses moving without three times the overhead. I specify the architecture and debug the failures; AI does the implementation.

What drives me: the gap between what AI can do and what most people are actually using it for. I'm interested in closing that gap, starting with my own work, and eventually helping others do the same.

Consulting

Technology Advisory

AI governance and technology platform advisory for financial services firms. Architecture, compliance guidance, and workflow automation.

Operations

Schuelace Farms

Microgreens production in Pisgah Forest, NC. From seed to delivery, and AI-automated from the first harvest weight to the weekly sales report.

Education

Own Your Life

Life skills course for teenagers and young adults. Building the practical knowledge schools don't teach. Finances, health, communication, decision-making.

Methodology

Diagnose. Design. Deliver.

I don't touch tooling until I understand the problem. Every engagement, every build, every recommendation follows the same sequence. I won't skip steps.

01 / DIAGNOSE

Diagnose

Map the actual workflow before proposing a solution. Identify where the friction is, where decisions stall, and what "solved" looks like in measurable terms. Most problems that look like technology gaps are process gaps in disguise.

02 / DESIGN

Design

Architecture before code. Define the data model, integration points, failure modes, and success criteria before writing a single line. A system built on a clear design is one that can be maintained, explained, and handed off.

03 / DELIVER

Deliver

Ship when it's right, not when it's fast. Real-world validation, monitored rollout, and iteration from live data. A working system on real inputs beats a polished spec that's never been tested against reality.

This is non-negotiable. Skipping diagnosis produces solutions to the wrong problem. Skipping design produces systems that work once and break under change. Skipping validation produces confidence without evidence. All three, every time.

Selected Builds

AI systems I use
every single day.

These aren't demos or side projects. They're production tools running on real data, solving real operational problems across my businesses.

01 / 03
Slack-Based Personal Operations Assistant

An AI agent workforce running across three businesses: a Chief of Staff (Atlas) that routes every message to one of seven specialized Directors, a Ledger watchdog that monitors everything I do daily and flags drift from my goals, and 13 scheduled jobs that keep it all moving without my attention.

View live dashboard →
Claude (Sonnet) Atlas Chief of Staff Slack Bot API FastAPI Notion API SQLite n8n Google Calendar Brevo SMTP Little Bird
7 Directors Domain-specialized advisors across growth, consulting, farm, product, finance, PM, and R&D
Daily drift check Ledger reads activity every evening, silent when on track
13 scheduled jobs Fully automated, no manual triggering
0 manual monitoring Health check + Ledger surface issues proactively

What it does

  • 7am daily brief: prioritized must-dos from Notion, calendar, and email across all projects
  • Atlas Chief of Staff: routes every Slack message to the right Director, farm → Forge, WesTech → Athena, product decision → Vector
  • Ledger watchdog: reads daily activity summary + Slack interactions vs goals every evening; Slack flag only when drift detected
  • Farm ops via Forge Director: harvest schedules, chef accounts, crop planning. Same interface, specialized context injected
  • 30-min pre-meeting packet: attendees, last commitments, open decisions, email thread context
  • Weekly Ledger review: full week analysis every Sunday, patterns, blind spots, neglected goals posted to Slack

What I directed

  • Specified an Atlas routing layer that classifies domain in a single LLM call and responds as the right Director with domain-specific context injected
  • Designed the Ledger memory system: SQLite ledger_log + Little Bird email integration, with a daily drift check and a Sunday deep review posted to Slack
  • Set goals.md as the system's north star (active projects, goals, and explicit non-priorities), and had Ledger read it on every review
  • Called for prompt caching on the Atlas system prompt to clear the 1024-token minimum on every call, cutting token cost across all Slack interactions
  • Scoped 13 APScheduler jobs: daily brief, meeting briefs, EOD capture, email sync, health check, Ledger daily + weekly, relationship digest, and more
02 / 03
Voice-Enabled Farm Operations App

A dictation-first app for logging harvest weights, planting dates, and packaging details by variety, size, and market, generating packaged-vs-sold reporting and weekly AI-assisted social media planning without manual tracking.

Voice Dictation SQLite Python / Flask Claude Email Automation
Zero Manual spreadsheet entry for harvest tracking
Weekly Automated email: sales insights + social content plan

What it does

  • Dictation-based input for harvest weights, planting dates, and packaging details, no typing, no spreadsheet
  • Generates packaged-versus-sold reporting without manual tracking
  • Automated weekly email: sales insights, operational schedules, AI-assisted social media recommendations and content
  • Visibility into inventory movement and market performance across varieties
03 / 03
Regulatory Signal Intelligence Agent

A fully automated overnight intelligence system for a financial services client. Monitors regulatory filings, industry publications, and competitive signals across three lanes. Classifies each by tier, routes T1s as immediate Slack alerts, and archives everything to a structured Notion database. Zero manual monitoring. Nothing slips through.

n8n Notion API Claude Slack Webhooks CRON triggers Webhook routing Python
3 lanes Regulatory, industry, and competitive signals monitored in parallel
T1 in minutes High-urgency signals bypass the digest and fire immediate Slack alerts
Zero manual Monitoring previously done by hand, now fully automated
Full audit trail Every signal classified, timestamped, and archived in Notion

n8n workflow architecture

  • Three parallel trigger types: CRON (scheduled overnight runs), webhooks (inbound push from monitored sources), and RSS pollers. Each lane routes independently through its own n8n subflow
  • Tier classification node: Claude evaluates each signal for urgency, relevance, and required action, and returns T1 (immediate) or T2 (digest) with a structured rationale
  • T1 routing branch fires an immediate Slack Incoming Webhook notification with signal summary, source link, and recommended action, no batching, no delay
  • T2 signals are written to Notion and held for the weekly digest workflow, which compiles, formats, and delivers them as a structured briefing
  • Error handling at every node: failures log to Notion with a status flag and trigger a fallback Slack alert so nothing silently drops

Notion backend

  • Signal inbox database: Source, Lane, Tier (T1/T2), Status (New / Reviewed / Actioned / Archived), Summary, Action Notes, Timestamp
  • Each signal is written by n8n via API on arrival. Human review happens directly in Notion, and status updates flow back into the weekly digest logic
  • Provides a durable audit trail and a searchable archive for compliance reference

What I directed

  • Architected the full n8n workflow graph: multi-trigger ingestion, lane-specific routing, tier branch logic, Slack delivery, and Notion write, wired as a single deployable workflow set
  • Wrote the Claude classification prompt spec: evaluate signal text against a client-specific relevance rubric, output structured JSON (tier, rationale, recommended action)
  • Designed the Notion database schema for the signal inbox and archive, with status field logic that feeds back into the digest workflow
  • Specified Slack notification templates for T1 alerts: signal title, source, tier rationale, direct Notion link for one-click review

Experience

10 years of building
things that actually ship.

2025 – present

Consultant

Independent

AI governance and technology advisory for regulated financial services clients. Architecture, compliance guidance, and workflow automation.

2025 – 2026

Senior Director, Solutions Engineering

Visory (formerly Swizznet)

Built and led a 5-person pre-sales function from scratch; standardized discovery and technical validation frameworks across enterprise deals, improving win rates by 40%.

2023 – 2025

Director, Product & Solutioning

Visory (formerly Swizznet)

Led cross-functional product and commercial strategy; supported the company's largest enterprise agreement at $4.2M ARR serving 600+ end customers.

2021 – 2023

Product Manager

Visory (formerly Swizznet)

Go-to-market strategy for managed services in regulated verticals; built solution frameworks that cut SE ramp time by 9 weeks across a 12-person sales org.

2019 – 2021

Senior Manager, Sales & Client Success

Visory (formerly Swizznet)

Built the client success function from the ground up; scaled a partner channel that drove 60% of new deal volume across 30 key partnerships.

2016 – 2019

Inside Sales Account Manager

Visory (formerly Swizznet)

Full-cycle sales and onboarding for SMB and mid-market accounts; built early foundations in value-based selling and translating technical capabilities for non-technical buyers.

2022

Certificate in Product Strategy

Kellogg School of Management, Northwestern University

2020

Master of Business Administration

Louisiana State University Shreveport

2013

Bachelor of Arts, Biological Anthropology

Florida Atlantic University

2025 – 2026

Guest Speaker: Technology & Agriculture

Local Schools, Pisgah Forest, NC

Delivered talks to sixth-grade science students on technology in agriculture, the future of farming, and the intersection of AI and sustainable food production. Included a live microgreens demonstration and provided take-home grow kits so every student could grow their own.

2016 – 2020

Assistant Scoutmaster

Boy Scout Troop 111

Supported troop leadership and youth development. Redesigned and redeployed the troop website and created a structured Webmaster playbook so the Scouts could manage the site going forward independently.

2014 – 2022

Active Member & Volunteer

West Palm Beach Elks Lodge

Eight years of active involvement in community service, charitable giving, and lodge programming.

How I think about AI

Practical, not performative.

Most AI hype is about what AI could do. I'm interested in what it actually does, for a specific person, with specific data, solving a specific problem.

⚙️

Build for reliability

A system that fails silently is worse than no system. Everything I build degrades gracefully. Failures are logged, fallbacks are explicit, and nothing breaks the day if a single node is down.

🔁

Close the loop

An insight that doesn't turn into an action is noise. Every output from my AI systems connects to a decision, a task, or a record. Each one can be tracked and improved over time.

📍

Context is everything

Generic AI answers are useless. The value comes from injecting the right data (your calendar, your commitments, your priorities) so the system knows what matters to you right now.

🧱

Ship, then improve

A working rough version beats a perfect spec. I build the minimum that's actually useful, run it on real data, and iterate from there, not the other way around.

👁️

Watch, don't just act

The most valuable agent in my system does no work. It watches what the others do (and what I do outside AI entirely) and flags when something's drifting. Doers and judges get all the attention. The watchdog is what makes the whole system actually learn.

How I Partner

Trust is the seat.
Everything else is a leg.

Trust is becoming the scarcest currency as AI takes over more of the systems people used to run by hand. I think of it as a stool: Authenticity, Transparency, and Follow-Through are the three legs holding the seat up. Take one away and it doesn't hold.

01 / AUTHENTICITY

Authenticity

Genuine curiosity, not performance. I listen to understand before I respond, and I don't walk into a conversation assuming I already know the fix. That assumption is exactly where trust breaks down.

02 / TRANSPARENCY

Transparency

Set expectations early, and reset them the moment there's real risk to keeping them, not at the last minute. If I don't know something, I say so, then go find the answer or the person who does.

03 / FOLLOW-THROUGH

Follow-Through

Deliver on what I promised, with ego left out of execution. Own mistakes fast and fix them to the other person's satisfaction, not just mine.

Proof, not a slogan. A partner's several hundred end customers were hitting performance issues on one specific product version, scattered complaints, hard to see as a pattern at first. Listening across dozens of them long enough to find the real cause meant discovering a vendor was quietly degrading a version it still called "supported." I brought it to the vendor directly, got their own engineers to confirm the root cause, and built a staged upgrade plan with them. Result: renewed trust with the partner, and a contract renewal that year.

Get in touch

Let's talk.

I'm open to the right opportunity. If you're building a team around AI-native operations, solutions engineering, or partner success, I'd like to hear about it. Messages go straight to my Slack.

or reach me directly

sam@samschuemacher.com LinkedIn