Prompt Engineering
Prompts Are Code. We Treat Them That Way.
Systematic prompt engineering with version control, testing, and evaluation—because "just tweak the prompt" doesn't scale.
The Hidden Engineering Challenge
Infrastructure is table stakes. The difference between AI agents that work and agents that embarrass is in the prompts.
Most teams discover this the hard way. The demo works beautifully with curated inputs. Then production brings typos, edge cases, adversarial users, and domain-specific terminology. The agent hallucinates, gives inconsistent answers, and breaks in ways nobody anticipated.
The instinct is to "tweak the prompt." Fix one problem, create another. The fix cascades into new failures. Confidence erodes.
The issue isn't the prompts themselves—it's treating prompt development as casual iteration rather than disciplined engineering.
Our Approach
We treat prompts with the same rigor we apply to software: version control, testing, code review, documentation, and continuous improvement.
Structured Prompt Development
Clear requirements for every prompt: what it should accomplish, what inputs it receives, what outputs it must produce, and what failure modes are unacceptable.
Version Control
Prompts live in your codebase, not in configuration UIs. Every change gets a commit. You can diff versions, trace regressions, and roll back.
Testing and Evaluation
Before any prompt change deploys, it runs against an evaluation harness that measures quality across your use cases.
Documentation
Every prompt includes documentation: why it exists, what it handles, known limitations, and decision history.
Code Review
Prompt changes receive the same review as code changes. Someone evaluates clarity, safety, and regression risk before approval.
What We Deliver
Custom Prompt Libraries
Domain-specific prompts tailored to your use cases. Not generic templates—prompts engineered for your terminology, tone, workflows, and edge cases.
Reasoning Patterns
Chain-of-thought structures, tool-use routing logic, and multi-turn conversation management encoded as reusable patterns.
Safety Guardrails
Constraints that prevent harmful, off-brand, or legally problematic outputs. These guardrails work as layers—not per-prompt additions.
Evaluation Frameworks
Automated testing infrastructure that scores prompt quality, detects hallucinations, and catches regressions.
Decision Logs
Documentation of what was tried, what worked, and what didn't. Future maintainers understand the reasoning behind design decisions.
Prompt Library Advantage
Modular, tested components that encode what works in your domain. New agents assemble from proven patterns.
- Different instruction templates produce wildly different performance—even when semantically identical.
- Extra spaces, punctuation changes, and example ordering cause significant quality fluctuations.
- ReAct-based agents are described as "extremely brittle to minor perturbations."
The fix isn't finding the "perfect" prompt. It's building process and tooling that makes prompts reliable despite inherent model variability.
Ongoing Optimization
Prompts aren't static. User behavior evolves. Edge cases surface. Models change behavior across versions. Production data reveals failure modes that evaluation sets missed.
We offer ongoing optimization retainers: monthly or quarterly cycles analyzing agent performance, testing prompt variants, and deploying improvements. You get continuous improvement without large project fees.
Not locked in—your team can handle optimization internally using the frameworks we build. We're available when you want expert support.
Your agents are only as good as your prompts.
Let's discuss your current quality challenges and show you what disciplined prompt engineering looks like.