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 designed and built myself. 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

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've built 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.

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 — and 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 / 04
Slack-Based Personal Operations Assistant

A full AI operating layer across three businesses — consulting, farm, and course — delivered through a single Slack interface backed by Claude, Notion, SQL, and n8n. If you turned it off tomorrow, I'd immediately feel like I was working with one hand tied behind my back.

Claude (Sonnet) Slack Bot API FastAPI Notion API SQLite n8n Google Calendar Brevo SMTP
90 min → 10 Daily planning time reduced per morning
0 missed Meaningful deadlines since rollout
~2 hrs/day Saved on meeting prep on heavy days
11 intents Natural language commands handled

What it does

  • 7am daily brief: prioritized 3–5 must-dos synthesized from Notion, SQL, and email across all projects
  • 1pm reminder: next 24 hours of deliverables grouped by project and urgency, posted to Slack
  • 30-min pre-meeting packet: attendees, last meeting commitments, open decisions, email thread context
  • Conversational commands: "What are my top three priorities before Friday?", "Create a follow-up task for Client X"
  • Recommendation loop: AI scores backlog by due date, impact, and work-hour cap → I accept → n8n updates Notion and notifies Slack with rationale

What I built

  • Notion database schema for projects, tasks, meetings, and clients — mapped to API calls
  • SQL tables for farm operations; queries used in daily brief and analytics
  • Prompt architecture and system design for Claude: interprets Slack commands, decides read vs. write, outputs structured JSON for downstream systems
  • n8n workflows: CRON triggers, webhook and Slack event handling, error handling with fallback messaging
  • Prompt caching across all Claude calls: system prompts and shared context cached at the API level, cutting token cost and latency on every Slack interaction
  • Docker containerization for portable deployment
02 / 04
Telegram Farm Operations Bot

A conversational interface for Schuelace Farms that queries Notion and SQL in natural language — growth metrics, sales, upcoming tasks, inventory — and writes back to both systems.

Telegram Bot API Notion API SQLite Shopify API Python
Read + Write Bidirectional: query and update farm records
Natural lang Interface over SQL and Notion simultaneously

What it does

  • Queries Notion for growth metrics, upcoming tasks, and time-allocation insights through natural language
  • Writes new tasks to Notion and updates SQL records for seed lot tracking
  • Supports workflows for adding new product varieties to Shopify
  • Removes the need to open Notion, a browser, or a database client for routine farm lookups
03 / 04
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
04 / 04
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 — 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 written by n8n via API on arrival — human review happens directly in Notion, status updates flow back into the weekly digest logic
  • Provides a durable audit trail and a searchable archive for compliance reference

What I built

  • 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
  • Claude classification prompt: evaluates signal text against a client-specific relevance rubric, outputs structured JSON (tier, rationale, recommended action)
  • Notion database schema for the signal inbox and archive, with status field logic that feeds back into the digest workflow
  • 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 30%.

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.

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 — something that 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 genuinely useful, run it on real data, and iterate from there — not the other way around.

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