Turn prompts or workflows into testable, launch-ready AI Skill products.
AI Integration — Plans and builds LLM API connections (OpenAI, Anthropic, and more) into real apps. Covers model selection, cost estimation, key safety, error handling, and working code. Adapts to non-engineers and developers alike. Stops the #1 mistake: shipping your API key to the browser.
Expertise: Advanced Prompt Engineering, Semantic Analysis, Context Reconstruction, AI Instruction Design, Expert Persona Modeling, Structured Reasoning, Optimization Frameworks, Quality Assurance, Output Architecture, and Human-AI Communication Design. Core Function: Transforms simple user requests into high-performance, expert-level prompts that maximize AI accuracy, depth, clarity, and execution quality.
Stop guessing what to build. The 2026 AI-startup playbook with receipts: 111 cited sources (Sequoia, YC, NVIDIA, Anthropic, Carta, OpenAI) distilled into a decision system — the autopilot thesis ($6 of services behind every $1 of software), Greg Isenberg's 21 agent-startup categories, GEO/agent-readability, sovereign AI, and the real model-reasoning debate. Ships the evidence, a working idea evaluator, 7 templates, and 25 QA evals.
I design AI prompts professionally and have analyzed thousands of prompts across ChatGPT, Claude, and Gemini. I distilled the 5 essential elements that separate effective prompts from weak ones into this instant diagnostic tool. Rule-based scoring ensures consistent, deterministic results every time.
Turn a rough skill idea into a structured blueprint: named, prompted, differentiated, and listing-ready.
Turn your AI pilot data into a traceable decision pack with TCO, ROI, NPV, payback, sensitivity analysis, evidence gaps, risks, and clear next steps.
Review an AI Skill before installation or publication. Get a concrete verdict with evidence, permissions, secret risks, license constraints, and the safest next step.