103건 · 관련도순
Prepare for the MCPA certification through interactive lessons, local Python labs, diagnostic assessments, and mock exams. Track progress, revisit weak domains, and resume learning, with guided support for learners who do not write code.
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Prepare for four Claude certification tracks through guided lessons, practical exercises, quizzes, and mock exams. The tutor checks understanding and learner-created work, records progress, and uses assessment results to guide review.
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Record and inspect source history, trust scores, and handling labels on AI-generated or modified files. Use AKF metadata, information attached to files, to support review, handoff, and advisory audit checks without treating labels as proof of compliance.
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Design or review command-line tools that AI agents can call. Use 98 proposed rules to define structured output, input validation, error handling, safety controls, and help information, with three levels for gradual adoption.
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Convert human-written CLAUDE.md instructions into a structured label format for AI agents. Use it to review lengthy rules, reduce instruction overhead, and prepare prompts for migration between AI tools while preserving the intended rules.
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Define ideal customers and a clear market position for an AI product. Use customer evidence to separate customer fit from buying intent, turn technical capabilities into business messages, and plan recurring checks of product-market fit.
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Plan pricing for AI products by comparing charges based on usage, tasks, or results. Use customer value and computing costs to shape pricing tiers, usage limits, hybrid plans, and margin improvement strategies.
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Fine-tune NV-Segment-CT VISTA3D on CT images and region labels in NIfTI format. Choose standard training or fixed-class softmax training, save model checkpoints and evaluation records, and optionally track training with MLflow.
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Help users interact with probabilistic models by designing interfaces that manage fluidity, intent, and agency while maintaining trust and control.
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Applies Geoffrey Moore's chasm-crossing strategy for B2B tech products moving from visionary early adopters to pragmatist mainstream. Use when a product has early traction but stalls before mainstream adoption, when planning a beachhead/niche strategy, when designing whole-product offerings, when positioning against established competitors, or when scaling from innovator usage to industry standard. Triggers include 'stuck between early adopters and mainstream', 'we need a beachhead', 'pragmatist customers won't buy', 'how do we go from 10 to 1000 customers'. NOT for PLG/freemium SaaS (Slack, Notion, Cursor), pure consumer apps, two-sided marketplaces, or AI-native products with bottoms-up viral adoption - their dynamics break the visionary-to-pragmatist sequence.
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Sets up how you and your team build and work with AI agents, and produces an Agent Workflow Charter (agent lanes, plan-mode loop, autonomy ladder with promotion criteria, rules file, review policy, security rules, rollout plan). Use when you ask 'how should we work with Claude Code / Codex / Cursor', 'how many agents should I run', 'should the agent be autonomous', 'plan mode', 'CLAUDE.md', 'AI-native team', 'roll out AI to my team', or 'my agent keeps screwing up'. Draws on 110 Lenny's Podcast guests incl. Claire Vo, Boris Cherny and Aishwarya Naresh Reganti.
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Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.
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The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA auditing.
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Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.
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Applies the reasoning, principles, and frameworks of Andrew Ng (machine learning pioneer, co-founder of Coursera and DeepLearning.AI, Stanford University, and former Google Brain lead). Use this skill whenever the user is navigating AI application development, agentic workflows, automation strategy, AI-native software engineering, or rapid prototyping. Trigger this skill when discussing career advice in the AI era, evaluating AI regulations, structuring machine learning projects, or deciding how to integrate AI into a business. It emphasizes task-based automation, data-centric ML, and driving the cost of proof-of-concepts to zero.
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Build comprehensive AI-native brand asset systems that maintain consistency across all AI-generated content. Train AI tools on brand guidelines, create reusable prompt libraries, and manage visual/voice assets at scale. Use when ", " mentioned.
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The enhancement layer for AI-generated content. This skill covers AI-powered visual effects, compositing, upscaling, restoration, and post-production magic—turning raw AI output into polished, professional content. AI generation gets you 80% of the way. Visual effects get you the remaining 20% that separates "clearly AI" from "how did they do that?" This skill covers ComfyUI workflows, Runway's AI tools, intelligent upscaling, rotoscoping, color grading, and the integration of AI elements into traditional footage. The practitioners of this skill are technical artists who understand both traditional VFX workflows and the new AI-native approaches that are revolutionizing post-production. Use when "AI visual effects, VFX, upscale, upscaling, composite, rotoscope, background removal, color grade, inpaint, outpaint, style transfer, enhance, ComfyUI, post-production AI, vfx, visual-effects, compositing, upscaling, post-production, comfyui, enhancement, color-grading" mentioned.
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The orchestration layer for AI-native creative production. This skill coordinates multiple AI tools—video, image, audio, digital humans, effects—into cohesive campaigns, productions, and creative systems. As AI tools proliferate, the challenge shifts from "can we create this?" to "how do we orchestrate these capabilities into something coherent?" The AI Creative Director thinks in systems, not tools. In pipelines, not one-offs. In brand consistency across AI-generated assets. This is where creative vision meets technical orchestration. The AI Creative Director doesn't just use AI tools—they compose them into creative instruments that produce at scales and speeds previously impossible. Use when "AI creative director, orchestrate AI, AI campaign, multi-tool, AI workflow, AI pipeline, coordinate AI, AI production, AI creative system, full AI production, AI at scale, orchestration, creative-direction, ai-production, workflow, pipeline, multi-tool, scale, quality-control" mentioned.
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AKF — The AI Native File Format workflow skill. Use this skill when the user needs The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA auditing and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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AKF — The AI Native File Format workflow skill. Use this skill when the user needs The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA auditing and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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AI Pricing Skill workflow skill. Use this skill when the user needs When the user wants to price an AI product, choose a charge metric, design pricing tiers, or optimize margins. Also use when the user mentions 'AI pricing,' 'usage-based pricing,' 'consumption pricing,' 'outcome pricing,' 'BYOK,' 'bring your own key,' 'per-seat pricing,' 'pricing tiers,' 'AI margins,' 'cost per token,' or 'pricing model.' This skill covers pricing strategy, packaging, and margin management for AI-native products. Do NOT use for technical implementation, code review, or software architecture and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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Applies the reasoning, principles, and frameworks of Andrew Ng (machine learning pioneer, co-founder of Coursera and DeepLearning.AI, Stanford University, and former Google Brain lead). Use this skill whenever the user is navigating AI application development, agentic workflows, automation strategy, AI-native software engineering, or rapid prototyping. Trigger this skill when discussing career advice in the AI era, evaluating AI regulations, structuring machine learning projects, or deciding how to integrate AI into a business. It emphasizes task-based automation, data-centric ML, and driving the cost of proof-of-concepts to zero.
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CTO-level architectural advisor for AI-native development. Use this skill whenever you encounter code design decisions, architecture discussions, system resilience questions, or any work touching: "architecture", "design", "scale", "dependencies", "state", "failure", "blast radius", "refactor", "migrate", "optimize", "resilience", "consistency", "observability", "bottleneck", "coupling", "monolith", "microservices", "distributed", "concurrency", "data flow", "system design", or any prompt suggesting code-first thinking when design-first thinking is needed. This skill integrates with Claude Code to review generated code for architectural soundness, define design systems via design.md, and guide teams toward CTO-level thinking. Trigger aggressively on architectural questions—this is where AI adds the most leverage.
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Generate standardized .agent-os directory structure with product documentation, mission, tech-stack, roadmap, and decision records. Enables AI-native workflows.
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