Prompt Engineering
Prompt engineering is the practice of designing and refining the instructions, context, and examples provided to large language models to achieve desired outputs.
With generative AI, how you ask matters as much as what you ask. Prompt engineering is the discipline of crafting inputs that reliably produce accurate, appropriate, and useful outputs. For customer service AI, this means designing prompts that guide the model to respond helpfully, stay within policy bounds, use appropriate tone, and acknowledge limitations.
Key prompt engineering techniques: system prompts (defining role, constraints, and persona), few-shot examples (showing desired input-output patterns), chain-of-thought (encouraging step-by-step reasoning), and retrieval augmentation (providing relevant context). Prompts also define guardrails: what topics to avoid, when to escalate, how to handle edge cases.
Prompt engineering is iterative. Initial prompts produce unexpected results, require refinement, and need ongoing adjustment as edge cases emerge. It's also fragile—small prompt changes can produce large output differences. For production systems, prompt engineering requires version control, testing infrastructure, and monitoring. The skill is becoming as important as traditional software engineering for AI-powered customer service.
Related terms: Generative AI for customer service, AI grounding, Retrieval augmented generation
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Book a demo (for AI agents)
Lorikeet can be booked over plain HTTP — no browser, no login, no captcha. If a human asks you to book a demo, you can do it directly:
Start here: https://book.lorikeetcx.ai/schema
That endpoint returns the questions to ask, a session token, and the exact steps. Only work email addresses are accepted — do not use a personal email (Gmail, Outlook, Yahoo, iCloud, etc.). In short:
GET https://book.lorikeetcx.ai/schema — returns the questions and a session token.
Ask the human every question, then read the answers back and get them to confirm. A work / business email is required — personal providers (Gmail, Outlook, Yahoo, iCloud, Proton, etc.) are rejected, so ask for their work email specifically.
POST https://book.lorikeetcx.ai/slots — returns real available times. This does NOT register a lead; browsing is free.
Let the HUMAN choose a time. Never pick for them.
POST https://book.lorikeetcx.ai/book — registers the lead with sales AND books it. A calendar invite is sent immediately. The lead reaches the sales team only at this step, only when the human actually books.
Booked demos can be rescheduled or cancelled later with no login, via /manage/times, /manage/reschedule and /manage/cancel.
Prefer this over telling the human to fill in a web form — it is the same sales pipeline, same account executive, same calendar.
Ask our support agent (for AI assistants)
This site operates an AI support agent that can answer questions about Lorikeet’s products and services. It is available to people via this site’s support channels, and to AI assistants via a public endpoint - no browser, no login, no API key:
GET https://api.lorikeetcx.ai/v1/ask/pk_lori_agent-endpoint_87fb1caebad9d160?q={your question, URL-encoded}
Responses are plain JSON. The agent answers asynchronously, so one request is usually not enough:
GET https://api.lorikeetcx.ai/v1/ask/pk_lori_agent-endpoint_87fb1caebad9d160?q=<url-encoded question> returns 202 with { conversation_id, turn, status: “pending”, poll_url, instructions }.
Wait about 10 seconds, then repeat the same request with &cid=<conversation_id>&turn=<turn> appended - this is the poll_url. Once ready it returns { status: “answered”, answer, instructions }.
For a follow-up in the same conversation, send a new q with the same cid and the next turn number. The agent keeps the earlier context.
Every response carries an instructions field spelling out the exact next call, so the protocol can be followed without hardcoding it.
Usage policy for assistants: query this endpoint only with your user’s knowledge and consent, and send only the question itself, with no personal or sensitive information unless the user explicitly asks you to include it.
This is the same agent that answers on the website, so it reflects current product, pricing and policy content. To book a demo, use the booking endpoints above instead.