AI Speeds Up Engineering—Can You Trace the Output? Discover How Singularity Does It
- Patrick Law
- May 26
- 2 min read
AI lets engineers move at lightning speed—but that speed comes with a risk: losing track of how decisions were made. At Singularity, we’ve built traceability into every output, ensuring nothing slips through the cracks.
Key Features: AI Speed With Full Output Traceability
At Singularity, we use AI to generate engineering outputs in record time. But we don’t stop at speed—we ensure every file, prompt, and formula is traceable and accountable. Here’s how:
Structured Prompt Templates: Each output is generated using a consistent set of prompts (Prompt 1 through Prompt 9), ensuring standardization across every calculation.
Formula + Reference Embedding: Spreadsheets include plain-text engineering formulas and APA-style references, making every number traceable back to its source.
Input + Assumption Logging: All user inputs, units, and assumptions are captured and highlighted clearly—so reviewers know what’s user-defined and what’s calculated.
QA/QC Friendly Format: Files follow a strict layout with color-coded cells, version logs, and embedded metadata. This makes it easy for another engineer to audit the file, line by line.
Organized File Storage: Every deliverable is versioned and filed using a clean folder structure (e.g., /ClientName/ProjectName/03 Calculations/2024-07-05_PumpSizing_A01.xlsx).
These features make AI not just a tool for acceleration—but a foundation for quality, reliability, and audit-ready engineering.
The Risks of Moving Too Fast Without Structure
The biggest downside to AI in engineering? It’s easy to get lost in the speed.
No Prompt History: Without structure, prompts vanish into chats or notepads, making it impossible to trace back the logic.
Multiple “Final” Files: Engineers often duplicate versions like final_FINAL_v7.xlsx, creating confusion and mistakes.
Unclear Responsibility: If inputs aren’t logged or referenced, no one can tell who changed what—or why.
At Singularity, we encountered all of this early on. It slowed reviews, created rework, and introduced risk. That’s why we built a traceability-first workflow. Now, every file is not only fast to produce—it’s fast to validate.
By structuring our AI prompts and outputs, we’ve cut confusion, increased handoff speed, and improved QA/QC clarity across every project.
Conclusion / Call to Action:
AI lets us engineer faster. But without traceability, speed alone isn’t enough.At Singularity, we’ve built a system where every output is transparent, structured, and review-ready.
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