AI Product Development
Product skill, available on Zeplik
AI Product Development is a ready-to-run product management skill on Zeplik. Integration, safety and cost guidance for building or hardening a production LLM feature. Ask in plain language and Zeplik applies the skill's method for you inside the conversation, on whichever AI model you prefer.
The AI Product Development skill loads automatically when your request matches it, or you can invoke it directly by typing /ai-product in any chat. It works with attachments, connectors, and any model that supports the task, so you get the same expert method every time without setting anything up.
What the AI Product Development skill can do
- Validate LLM outputs against schemas instead of trusting raw text
- Design retrieval based context instead of stuffing full documents
- Add streaming, timeouts, retries and fallbacks for production reliability
- Produce a prioritized sharp-edges table with severity and mitigations
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How the AI Product Development skill works
AI Product Development
Ship LLM features that survive production, not just demos. Treat prompts as code, validate every output, and never trust an LLM blindly. Demos are easy; production is hard.
Patterns
Structured output with validation
Use function calling or JSON mode with schema validation. Reject and retry on parse failure rather than best-effort string parsing.
Streaming with progress
Stream responses token-by-token to show progress and cut perceived latency. Never make the user wait for a complete response before showing anything.
Prompt versioning and testing
Version prompts in code alongside the app. Keep a regression suite of representative inputs so a prompt tweak can't silently break prior behavior.
RAG over context stuffing
Retrieve only the relevant chunks and inject them; don't dump entire documents into the window. Calculate tokens before sending.
Anti-Patterns
- Demo-ware -- demos deceive, production reveals truth, and users lose trust fast the first time it breaks.
- Context window stuffing -- expensive, slow, hits limits, and dilutes the relevant signal with noise.
- Unstructured output parsing -- breaks randomly, formats drift, and opens injection risks.
Sharp Edges
| Issue | Severity | Mitigation |
|---|---|---|
| Trusting LLM output without validation | critical | Validate every output against a schema before use |
| User input placed directly in prompts | critical | Sanitize input; use defense layers / delimiters; treat input as untrusted |
| Stuffing too much into context window | high | Count tokens before sending; retrieve, don't dump |
| Waiting for the full response to render | high | Stream responses and show partial output |
| Not monitoring API costs | high | Track tokens and cost per request; alert on spikes |
| App breaks when the LLM API fails | high | Timeouts, retries, fallbacks, and graceful degradation |
| Not validating facts from responses | critical | Cite sources / cross-check factual claims before surfacing |
| LLM calls in synchronous request handlers | high | Move calls to async paths / queues to avoid blocking |
Output
An assessment of the proposed LLM feature: which patterns to apply, which anti-patterns it currently exhibits, and a prioritized sharp-edges table (severity + concrete mitigation) to make it production-ready.
How to use the AI Product Development skill
Sign in to Zeplik
Create a free Zeplik account or sign in. New accounts start with free credits, so you can try the AI Product Development skill right away.
Describe your product management task
Ask in plain language, or type /ai-product to invoke the skill directly. Zeplik recognizes the AI Product Development skill and applies its method.
Review and refine the result
Zeplik returns a clear, structured answer. Ask follow-ups in the same chat to refine it or take the next step.
Source and credit
- Author
- davila7 community
- License
- MIT
Adapted from the open-source davila7/claude-code-templates project and tuned to run natively on Zeplik. View source on GitHub.
Frequently asked questions
- What is the AI Product Development skill?
- AI Product Development is a ready-to-run product management skill on Zeplik. Integration, safety and cost guidance for building or hardening a production LLM feature. Ask in plain language and Zeplik applies the skill's method for you inside the conversation, on whichever AI model you prefer.
- How do I use AI Product Development on Zeplik?
- Sign in to Zeplik and ask in plain language, or type /ai-product in any chat to invoke it directly. The skill applies its method and returns a result you can refine in the same conversation.
- Which AI model does the AI Product Development skill use?
- Any model you choose. Zeplik works across every model in one chat, so the AI Product Development skill runs on your preferred model for the task.
- Where does the AI Product Development skill come from?
- The AI Product Development skill is adapted from the open-source davila7/claude-code-templates project (MIT) and tuned to run natively on Zeplik. The original source is linked on this page.
- How much does the AI Product Development skill cost?
- Using the skill is free to start. You only spend Zeplik credits when the assistant runs, and new accounts begin with free credits.
Related product skills
- Agile Product OwnerUse when writing INVEST user stories, acceptance criteria, or grooming and prioritizing a product backlog. Not for sprint ceremony planning (use sprint-planning).
- AI Product BuilderUse when building a paid product that wraps AI APIs: architecture, prompts as product, cost metering, differentiation. Not for calling the Anthropic API in code (use claude-api).
- Game-Changing FeaturesStack-ranked 10x opportunity analysis across massive/medium/small bets. Not for open-ended ideation (use product-brainstorming) or one idea into a spec (use idea-to-spec).
- Idea to SpecTurn a rough product idea into build-ready documents through staged gates: a clarifying interview in chat, then a design doc artifact, an optional UI brief, and an implementation plan. Use when the user has an app or feature idea and wants it captured, shaped, and specified before any code. Not for tasks that already have a clear spec (use plan or execplan) or for pure research questions.
- Pre-Build Risk ReviewUse for a pre-build risk review of demand, positioning, monetization, retention, distribution before committing to build. Not for turning an idea into a full spec (use idea-to-spec).
- Product Brainstorm PartnerUse as a product thinking partner -- exploring a new opportunity, generating solutions to a product problem, stress-testing an idea, challenging assumptions before converging on a direction. Not for exploring a code or feature design (use brainstorming) or writing the spec (use write-spec).
More on Zeplik
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