About Ben Schauerhamer

I’m Ben Schauerhamer.

I started developing in first grade on an old Apple II. I got into the source code for Lemonade Stand, figured out BASIC, modified the game, and started building my own things. By age 15, I had already shipped software professionally — building a control panel for a local web hosting and dial-up company.

After high school I served in the U.S. Army as an Apache Longbow-Delta (AH-64D) Electrician and Armament specialist — one of the “Armament Dogs.” That experience taught me early lessons in complex systems, troubleshooting under pressure, strict standards, and maintaining mission-critical equipment where failure could mean the death of your fellow soldier.

Professional Spine

I operate as a Forward Deployed Enterprise Architect with deep experience designing and delivering scalable enterprise platforms. My Salesforce journey spans more than 15 years across Sales Cloud, Service Cloud, Field Service, Experience Cloud, Revenue Cloud, Life Science Cloud, Government and OEM/ISV solutions. I’ve led complex implementations, migrations from Classic to Lightning, DevOps transformations (Gen 1 to Gen 2 packaging), and large-scale integrations with NetSuite, Zuora, AWS, and other enterprise systems.

I specialize in turning fragmented, siloed environments into governed, scalable platforms — replacing brittle point-to-point integrations with modern middleware, serverless data pipelines, and architectures that support both operational excellence and emerging AI capabilities.

The Real Work

The longer I build, the clearer it becomes: the highest-leverage work isn’t writing more code. It’s understanding the problem deeply, designing the right system, defining constraints, anticipating failure modes, and establishing boundaries.

Quality isn’t inspected in at the end. It’s designed in from the start — a principle I learned from W. Edwards Deming and have applied across every serious project, whether in military systems, enterprise platforms, or AI-native architecture.

Most software and AI problems are not coding problems. They are system problems: design, process, boundaries, ownership, and architecture.

Architected Acceleration

I use AI developers heavily. They remove massive operational burden — boilerplate, tests, refactors, documentation, scaffolding, repetitive implementation, and especially knowledge transfer.

But AI does not replace the architect.

AI reduces the operational burden around the architect.

This is the core of Architected Acceleration — human architecture first, AI-accelerated execution second. The approach works far beyond software development. It applies to nearly any job that involves a computer. Simply ask yourself: “What are the most labor-intensive tasks that are not the best use of my time?”

It’s the difference between faster chaos and disciplined, reliable systems. I’ve used this approach across enterprise Salesforce ecosystems and now apply it full-time to my own work.

What I’m Building

I’m pressure-testing this philosophy through Axiom Core — an intelligence layer designed to sit underneath real applications, focused on retrieval, reasoning boundaries, memory, source authority, governed state, and trust.

This architecture is being proven across three primary projects:

• Mammoth Central — Live hockey intelligence platform testing real-time reasoning, contextual understanding, and fan-facing explanation layers.
• ClassicMUDs — AI-native persistent text world exploring long-term memory, evolving state, bounded agency, and governed autonomy.
• TrialPulse — Clinical trial intelligence focused on provenance, citations, relationships, and high-trust reasoning.

I also maintain HammerTavern as my self-hosted systems workshop. Infrastructure ownership and clear separation of concerns matter.

This Site

Showerhammer.com is my personal field journal. It is a living example of Architected Acceleration — built intentionally so both humans and AI systems can read it cleanly and reliably.

You’ll find writing here on AI systems architecture, operational burden, enterprise integration, RAG and retrieval, Salesforce architecture, self-hosting, project field notes, and the practical realities of building serious systems in the age of AI.

I also share non-technical applications — how I use the same principles in everyday projects such as vehicle repair, DIY home improvement, and other real-world tasks where AI reduces operational burden and improves outcomes.

The through line is simple: I’m interested in useful, grounded, explainable systems that carry standards and reduce operational burden without outsourcing judgment.

If my name is on it, the work carries my standards.

Welcome to the journal.

Hammer it out.