viktorbezdek

Expert guidance for writing, editing, and teaching stories across fiction, business, data, speech, UX, and interactive narrative. Covers canonical story structures (3-act, Hero's Journey, Story Circle, Save the Cat, Kishōtenketsu, Freytag, Fichtean), business narrative frameworks (StoryBrand, Pixar Spine, Before-After-Bridge), data storytelling (Knaflic, situation-complication-resolution), speech

Visual design systems, UI/UX styling, Tailwind CSS, CSS variables, component libraries (shadcn/ui, Radix UI), design tokens, accessibility (WCAG), responsive layout, dark mode, and Figma-to-code workflows. NOT for React component logic, hooks, or state management (use react-development). NOT for Next.js routing, SSR, or server components (use nextjs-development).

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization.

PM funnel workflow for turning user research into prioritized engineering stories — product story, user research to backlog, user needs to stories, PM workflow. Chains elicitation (deep interviews that surface real needs), user-journey-design (touchpoints, pain points, emotions), persona-definition (who we're building for), outcome-orientation (measurable success criteria), and prioritization (RIC

Systematically assess and mitigate risks using risk registers, probability-impact matrices, mitigation strategies, and contingency plans. Use when the user asks to assess risks, build a risk register, plan for failure modes, evaluate downside scenarios, prepare contingency plans, or quantify uncertainty before a decision or launch. NOT for finding conceptual flaws or blind spots in ideas (use crit

Research before craft for long-form technical content. Profile the audience (knowledge level, jobs-to-be-done, prior beliefs), tier sources (primary > peer-reviewed > authoritative > popular > vendor), triangulate every load- bearing claim across three sources, manage evidence types (data, expert quotes, demonstrations, case studies, source code), and apply citation discipline (when, how, link-rot

Identify and document boundary conditions, corner cases, error scenarios, and validation requirements that implementations must handle. Use when the user asks to find edge cases, identify corner cases, specify validation rules, enumerate error scenarios, harden a function against bad inputs, or think through what can go wrong at the boundaries of a system. NOT for writing the actual tests (use tes

EXTENDING effective context capacity — KV-cache optimization, observation masking, context partitioning, and retrieval strategies. Use when the user asks to "optimize context", "implement KV-cache", "partition context", "mask observations", or mentions extending context capacity or cache-friendly prompt design. NOT for reducing or compressing content via summarization (use context-compression), NO

Map user journeys with touchpoints, emotional states, pain points, and opportunities across the full arc of a user's experience over time. Use when the user asks to map a user journey, create a customer journey map, design a service blueprint, document touchpoints and friction points, or visualize the end-to-end experience of a user across multiple interactions. NOT for static navigation structure

Semantic image-text matching with CLIP and alternatives. Use for image search, zero-shot classification, similarity matching. NOT for counting objects, fine-grained classification (celebrities, car models), spatial reasoning, or compositional queries. Mention CLIP, embeddings, image similarity, or semantic search.

Design, evaluate, and iteratively improve prompts for LLMs — system prompts, few-shot examples, reasoning structures, and instruction templates. Use when the user asks to improve a prompt, write a system prompt, optimize LLM instructions, reduce hallucinations through prompt structure, test prompt variants, or apply prompting techniques (structured reasoning, ReAct, few-shot, structured output). N

Apply outcome-over-output product thinking — separating what gets built from what actually changes for the user, running the "so what" test to climb from output to outcome to impact, choosing leading vs lagging metrics, and identifying a North Star metric. Use when the user asks whether something is an outcome or an output in a product context, wants to run the "so what" test on a deliverable, wan