Cheat sheet · Earn independently
AI video and design for clients cheat sheet (AI video)
Opens with creditsA quick-revision companion to the AI video edition of the roadmap: video formats clients buy, hooks and pacing, generators, avatars, voice and editors, shot lists and references, rights and labels, offers, clients, and the aspect ratios, safe zones and exports each platform wants.
Chapters
8 chapters · 64 concepts
1What clients buyThe formats businesses pay for, how they judge them and what the demand data really says.8 concepts
- 1Demand signalEvidence that clients pay for a service: dated reports such as Upwork In-Demand Skills 2026 (AI video generation and editing +329 percent, AI images +95…
- 2Ad creativeThe image or video an advertiser runs in a paid placement, usually made in several sizes and versions so the best one can be found by testing.
- 3UGC-style adAn ad made to look like a real customer filming on their phone: talking to camera, casual framing, quick cuts.
- 4Explainer videoA short video, often 30 to 90 seconds, that shows what a product or process is, how it works and why it matters, usually with a voiceover.
- 5Short-form videoVertical 9:16 video for Reels, TikTok and YouTube Shorts, where the first one to two seconds decide whether anyone keeps watching.
- 6ThumbnailThe small image that represents a video and decides whether people click.
- 7Brand kitA brand's logo files, colour codes, fonts, image style, tone of voice and examples of what to do and avoid.
- 8Creative testingRunning several versions of an ad, each changing one thing such as the hook or image, and keeping the winner by numbers like click-through rate and conversions.
8 in this chapterOpen this chapter2Creative fundamentalsThe decisions AI does not make for you: what the viewer sees first, the story, the pace, colour, type and brand consistency.8 concepts
- 1HookWhatever stops someone scrolling: the first one to three seconds of a video, or the single element that reads instantly in an image.
- 2Story structureA simple shape for the message: problem, product, proof, call to action for ads; what it is, how it works, why it matters for explainers.
- 3Shot typesWide shots show where we are, medium shots show a person and action, close-ups show detail or emotion.
- 4Pacing and cuttingHow long each shot stays on screen and why you cut.
- 5Sound and voiceVoiceover, music and small sound effects, mixed so the voice sits clearly above the music.
- 6Colour and contrastPalettes built from harmonies (complementary, analogous, triadic), brand colours given as HEX codes, contrast that keeps text readable, and grading that makes…
- 7TypographyHow text looks: typeface, size, weight, leading (line spacing) and kerning (letter spacing).
- 8Brand consistencyUsing the same colours, fonts, logo placement, tone and image style in every asset, checked against the brand kit.
8 in this chapterOpen this chapter- The tool stackWhich kind of tool does which job. Names and versions are as of October 2026; plans, prices and terms change, so check the official page before client work.8 conceptsOpens with credits
- Prompting and consistencyPrompt patterns, references and habits that give the same character, product and style every time.8 conceptsOpens with credits
- Rights, consent and labelsWhat you may do with what you make. Not legal advice: a checklist that tells you when to read the official terms or ask a lawyer.10 conceptsOpens with credits
- Portfolio and offersProof first, then packages with clear deliverables, turnaround, revisions and usage rights.7 conceptsOpens with credits
- Finding and keeping clientsMarketplace gigs, outreach to businesses already advertising and retainers. Platform setup lives in the Freelancing roadmap.7 conceptsOpens with credits
- Delivery and specsBriefs, versions, the sizes and formats each platform wants, and a clean handover. Specs read on official pages in October 2026: recheck before big jobs.8 conceptsOpens with credits
- 9Glossary, A to ZEvery concept in the sheet and the smaller terms it uses, in one list.121 terms
About this sheet
Ads, shorts and visuals made with AI tools.
Related on Sefism
Picked from the other libraries by shared topics.
Roadmaps
See allBest practices
See all- Best Practices for Building LLM AppsHow to build LLM apps and agents that hold up in production: prompts, evals, prompt injection, tool permissions, cost, logging and privacy.
- Prompt Engineering Best PracticesHow to write prompts that work the same way on the hundredth input as on the first: clear instructions, structure, examples, reasoning, output control and testing.
- Best Practices for AI Coding AssistantsHow to get reliable code from AI coding assistants and agents: instruction files, task prompts, verification, review, security, dependencies and session hygiene.
Checklists
See all- RAG Production ChecklistA RAG production checklist: chunking, embeddings, hybrid search, reranking, per-user permissions, citations, evals, re-indexing and cost, with how to verify each check.
- LLM Evaluation ChecklistAn LLM evaluation checklist: success criteria, eval datasets, code and model graders, judge calibration, agent evals, safety tests and production monitoring, with how to verify each check.
- AI Feature Launch ChecklistAn AI feature launch checklist: use case fit, evals, UX for errors, disclosure, human override, abuse filters, rate limits, cost caps, prompt privacy, monitoring and rollback.
Project structures
See all- GenAI RAG app (FastAPI) project structureFor developers turning a "chat with your documents" demo into an app people can rely on. A FastAPI backend where every layer has a home: ingestion workers, retrieval, prompts as versioned files, model clients with fallbacks and cost caps, guards, evals that gate CI, and tracing, so a wrong answer can be traced to the step that caused it.
- AI agent with an MCP server project structureFor developers who want to give AI assistants safe access to their own data or API. A TypeScript MCP server built on the official SDK, organised by feature (tasks, projects) with each feature owning its tools, resources and prompts, served over stdio for local hosts and Streamable HTTP with OAuth for remote ones, plus a small agent and the evals that prove a model can use it.
- Machine learning project project structureFor students and analysts whose model works in a notebook and now needs to be reproducible, reviewable, served and watched. It starts from the Cookiecutter Data Science v2 layout (immutable raw data, numbered notebooks, a real Python package) and grows into versioned data with DVC, typed parameters, data validation with pandera, experiment tracking and a model registry with MLflow, a FastAPI prediction service, drift monitoring and, for a team, scheduled retraining, model cards, fairness checks and shadow deployment.
Career questions
See all- Which freelance skills is AI replacing, and what should I switch to?AI is squeezing basic, repetitive freelance work first: plain data entry, simple transcription and translation, generic articles, basic logos and simple product descriptions. Work that combines a skill with judgement, client context or systems is holding up better, including automation, AI integration, analytics, specialist writing and full projects that own a business outcome.
- Which AI tools do employers expect junior developers to know in 2026?Employers rarely require a specific brand. They expect you to use an AI coding assistant well (in the editor and in the terminal), to review and test what it produces, to call an LLM API in a small feature, and to explain when you would not use AI. Pick one assistant, learn it properly, and show judgement in your projects.
- How do I use AI to become a better engineer instead of becoming dependent on it?Decide the job AI does before you open it. Use it as a tutor, reviewer and sparring partner that explains and challenges, not a vending machine that hands you finished code. Attempt first, ask second, and always be able to explain and defend what you ship.
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