Structured prompting imposes discipline—delivering consistent, audit-ready outputs with process documentation and control over quality. Multi-model optimisation enhances results further.
Unstructured, trial-and-error prompting leads to inconsistent answers, scalability limitations, increased risk and inefficient resource utilisation.
A four-part structure (E.C.H.O.) addresses gaps in enterprise AI—each pillar is practical, documented and builds internal capability.
Expertise prompts frame the AI’s role as an informed analyst, defining the professional context and expected standards. This creates a structured, expert dialogue—ensuring domain accuracy, meaningful business language, and responses that align with stakeholder needs.
Context gives the AI background, business constraints, regulatory scope and strategic aims—ensuring outputs are grounded in operational reality and support compliance from the outset.
How provides a logical route to solve the problem—encouraging multi-step, transparent reasoning that decomposes tasks and imposes quality checks at every stage.
Output clarifies the required deliverable, ensuring consistency, traceable metadata, audit readiness and compliance documentation as standard.
Greater accuracy, consistency, regulatory proof and cost-efficiency across teams.
Built-in oversight, audit trails, and template-driven processes reduce errors and support appropriate challenge.
Multi-model checks, domain-specific language and stepwise improvement underpin robust, audience-relevant results every time.
Using multiple AI models improves reliability, enabling cross-verification and reducing the risk of hidden errors
Structured feedback and iteration drive steady gains in output quality, transparency and operational efficiency
Industry-specific terms and standards increase answer relevance and ensure outputs reflect industry requirements
Tailoring communication matches outputs to user roles and decision contexts for greater business value
Embedded verification steps detect and correct errors, minimising hallucinations and assuring accuracy
Templates maintain uniformity, streamline workflows and meet compliance or documentation needs across use cases
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The ECHO Framework™
Prompt engineering by Eye For Business (Eye4B)