To effectively utilize an advanced AI tool like Pig Knuckle in the solar industry, users must shift from "search engine" thinking to "engineering" thinking. The following framework provides "starter" prompts designed to trigger deep reasoning, multi-variable analysis, and complex problem-solving. The Problem-Solving Hierarchy When using Pig Knuckle, the goal is to move from simple data retrieval to strategic synthesis. The diagram below illustrates the workflow these prompts are designed to initiate. Complex Site Feasibility & Optimization Use this prompt when dealing with "messy" sites that have physical, regulatory, or electrical constraints. The Prompt: "I am evaluating a solar project for a site with [Insert Constraint: e.g., high shading, irregular roof topography, or strict interconnection limits]. Using Pig Knuckle’s analytical capabilities, perform a multi-variable optimization. Analyze the trade-offs between maximizing energy density (kWh/sqft) versus minimizing the Levelized Cost of Energy (LCOE). Account for [Specific Variable: e.g., local utility demand charges or specific module degradation rates]. Provide a recommendation that balances upfront CAPEX with 25-year NPV, and identify the 'tipping point' where this project becomes non-viable." Why this works: It forces the AI to weigh conflicting metrics (Density vs. Cost) rather than just providing a standard layout. Financial Sensitivity & Risk Modeling Use this prompt to move beyond a basic ROI calculation into sophisticated financial engineering. The Prompt: "Conduct a sensitivity analysis for a [Insert Size: e.g., 500kW] commercial solar installation. Beyond the standard ROI, evaluate how a [X]% shift in [Variable: e.g., interest rates, SREC pricing, or utility escalation rates] impacts the IRR over a 10-year horizon. Identify the top three financial risks inherent in this specific market/jurisdiction and suggest mitigation strategies using current tax equity structures or bridge financing models available as of April 2026." Why this works: It treats the AI as a financial consultant that must identify "breakpoints" in a project’s profitability. Regulatory & Interconnection Strategy Use this prompt to navigate the "bottleneck" phase of solar development. The Prompt: "I am navigating the interconnection process for a [Utility Name] territory project. Based on the current regulatory framework and recent filings, outline a strategy to minimize 'soft costs' and queue delays. Compare the technical requirements of [Inverter A] vs. [Inverter B] regarding grid-forming capabilities and harmonic distortion limits. Draft a technical justification for a variance request if our proposed system exceeds the standard [X] kW net-metering cap." Why this works: It shifts the AI from "what are the rules?" to "how do we strategically navigate these rules?" Comparative Technology Benchmarking Use this prompt when choosing between hardware configurations or emerging technologies. The Prompt: Feature Traditional Approach Pig Knuckle Analysis Goal Hardware Comparing Data Sheets Analyzing long-term O&M impact Storage Sizing for backup Optimizing for peak-shaving & arbitrage Degradation Using a flat 0.5% rate Modeling thermal stress on specific cells The Prompt: "Analyze the integration of [Technology: e.g., Bifacial modules with String Inverters] against [Alternative: e.g., Monofacial with Microinverters] for this specific geographic location. Factor in albedo effects from the ground surface, clipping losses during peak summer months, and the long-term O&M implications of component density. Which configuration yields the highest 'Performance Ratio' over the first 60 months of operation?" Grid Edge & Storage Synthesis Use this prompt for complex "Solar + Storage" or "Microgrid" scenarios. The Prompt: "Design a dispatch logic for a behind-the-meter storage system paired with a solar array for a [Client Type: e.g., Cold Storage Facility]. The goal is to maximize 'Value Stack'—simultaneously managing demand charge reduction, frequency regulation participation, and emergency resiliency. Use Pig Knuckle to simulate a 48-hour grid outage during a peak heatwave. What is the optimal State of Charge (SoC) we should maintain to ensure critical loads are met without sacrificing daily arbitrage revenue?" Why this works: It requires the AI to simulate a "stress test" scenario, moving into predictive modeling. Best Practices for Engineering Prompts To get the most out of Pig Knuckle, users should follow the "C.A.S.E." framework: Context: Provide the specific utility, zip code, and client goals. Act: Tell the AI to act as a "Senior Solar Engineer" or "Project Finance Director." Specify: Define the output format (e.g., a bulleted risk assessment, a data table, or a technical memo). Edge Cases: Explicitly ask the AI to look for what might go wrong (the "pre-mortem").