Playbooks
From a working prompt to a bot you can actually trust with customers
A support-bot prompt that answers well in testing is a genuine starting point. Getting it production-ready needs specific, real engineering — not a longer prompt.
Last updated Aug 15 · 12 min read
Step 1: chunking your knowledge base correctly
Before anything else, get chunking strategy right — this single decision affects retrieval quality more than almost any other choice in a RAG-based support bot.
Step 2: hybrid retrieval, not vector search alone
Tune hybrid retrieval — combining dense vector similarity with sparse keyword matching catches exact-term queries a pure vector search sometimes misses, which matters a lot for support queries referencing specific product or error names.
Step 3: guardrails for what the bot should never do
Design a real guardrail policy — stated explicitly, covering what the bot should escalate to a human rather than answer unilaterally, not left to hopeful inference.
Step 4: red-team it before customers do
Run a genuine prompt-injection red-team exercise — testing whether malicious or unusual customer input can hijack the bot's behaviour before an actual adversary finds the gap.
Step 5: observability so failures are debuggable
Build a real observability and tracing spec — when a customer reports a wrong answer weeks later, you need to be able to trace exactly what happened, not guess.
Step 6: an evaluation suite, run continuously
Build an evaluation benchmark suite and run it on a schedule, not once at launch — a bot's accuracy can quietly degrade as your product or knowledge base changes underneath it.
Where this genuinely needs a real engineering team
Every step here is real engineering work, not a longer prompt — this is exactly what Scult's AI agents team builds, or book a meeting if you have a validated prompt ready to become a real production system.
Need this built into your business?
The free tools and prompts on this site handle the small, solved problems. If what you need is bigger — AI agents & automation, built and maintained for you — that's Scult's day job.
