steadymade.ai
ENDE
Prompt Engineering & LLM Expertise

Precision before scale.

Prompt design, model selection and evaluation for production use in German and English. The difference between a demo that impresses and a system that runs.

Duration
1-3 weeks
Format
Workshop + delivery
Result
Prompt system
Price
Fixed price
How it works · 5 steps
  1. 01

    Baseline audit

    Current prompts and model usage reviewed against production targets. Failure modes, hallucination patterns, and latency bottlenecks surfaced before any changes are made.

  2. 02

    Prompt architecture

    System prompts, chain-of-thought, few-shot structures, and output formatting designed for your specific task. No copy-paste from the internet.

  3. 03

    Model selection

    GPT-4o, Claude, Gemini, Llama, Mistral: matched to task complexity, data sensitivity, budget, and latency. We run evaluations, not assumptions.

  4. 04

    Evaluation framework

    Structured test sets and scoring criteria for your use case. Regression testing so improvements don't break what's already working.

  5. 05

    Workshops & enablement

    Team sessions that build internal prompt literacy. Not theory, real tasks from your workflows, worked live.

Output quality improvement vs. default prompting
40-70%
Cost reduction through model right-sizing
30-60%
Reduction in manual review rate
60%
Models evaluated per engagement
3-5

What you get.

Prompt library

Documented, version-controlled system prompts, few-shot examples, and chain-of-thought patterns ready to deploy.

LLM evaluation report

Side-by-side comparison of models (GPT-4o, Claude, Gemini, Llama, Mistral) against your specific use case and quality bar.

System prompt architecture

Modular prompt structure that separates persona, instruction, context, and output format, maintainable by your team.

Quality baseline

Evaluation dataset and automated quality checks so you know when a model update degrades output.

Questions,
straight.

Common questions about Prompt Engineering. If yours is missing, ask us in the call.

What's included in prompt engineering?
Audit of your current system, redesigned prompts, structured output formats, test cases, and handover documentation. We cover system prompts, few-shot examples, and retrieval augmentation where applicable.
How do you choose the right model?
Based on task type, data privacy requirements, latency, and budget. We test candidates against your actual data, not benchmarks.
Can you work with our existing stack?
Yes. We adapt to your infrastructure, cloud or on-prem, API-based or self-hosted. We don't require platform lock-in.
What if we've already built a system?
We start with an audit. Often 2-3 targeted prompt changes produce a step-change in quality without a full rebuild.
How long does it take?
A focused prompt audit and redesign typically takes 2-3 weeks. Larger systems with evaluation frameworks run 4-6 weeks.
Do you cover RAG and multi-agent setups?
Yes. Retrieval-augmented generation, function calling, and multi-agent architectures are standard scope.
Free · 30 minutes · No obligation

Is Prompt Engineering the right first step?

In 30 minutes with a founder you find out, and what it would take in your business.

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