AI Knowledge Base
From AI fundamentals and practical tools to reliable workflows.
Explore methods for learning, work and collaboration.
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Getting Started with AI
Start with a small task whose result you can check yourself.
Choose a task, explain it clearly and check the answerUsing AI Tools
Understand inputs, settings and limits, then work through practical tool problems.
Choose tools for your materials and troubleshoot their useAI at Work
Turn source material into presentations, notes and deliverables you can revise and hand over.
Produce useful, editable workAI Workflows & Teams
Organize processes, materials and responsibilities so work can be repeated and shared.
Make a one-off method repeatable and transferableAI Trends
Read technical and industry changes in context, separating events, evidence and interpretation.
Understand changes, evidence and their effect on workFeatured articles
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- AI Workflows & TeamsHow to Use OpenAI dot for Work: Lessons from Real TasksLessons from using OpenAI dot for research, content and website work, with a reusable task brief, decision handoff and guidance for reviewing deliverables.
- Getting Started with AICodex Tutorial for Beginners: From Choosing an Interface to Finishing Your First TaskChoose a Codex interface, prepare a local folder, and turn fictional feedback into a checked handoff table. Includes practice files and translations of verified Chinese outputs.
- AI at WorkWhen you hand work to Codex, what can you deliver—and what must you still decide yourself?Choose manual work, chat, or Codex file-based work. Check sources, revisions, and handoffs while keeping unapproved decisions and commitments with the right people.
- Using AI Toolsvideo-use subtitle burn-in failed? Check the FFmpeg subtitles filterPreserve your generated SRT, identify the FFmpeg executable video-use actually uses, and check its subtitles filter before changing builds.
- Using AI ToolsChatGPT Attachments Missing from Project Sources After Moving a Chat?Find the correct original, check for duplicates, add it through Project Sources, and verify the contents. Know what to record if the process still fails.
- AI at WorkNarration and Scene Timing: A Manual Audio-First WorksheetPlan scene cuts from audio durations, distinguish separate chapter files from one continuous track, and review transitions. Includes a copyable blank worksheet and a fictional worked example.
- AI at WorkPPT Master: Edit Selected Slides While Preserving the DesignScope a selected-slide update with PPT Master’s documented Edit Native PPTX workflow. Confirm the plan and check untouched slides, shared resources, and export records.
- Using AI ToolsPresenton Custom Template 504: Separate Timeouts from Processing FailuresDiagnose a 504 during Presenton custom PPTX template import. Match browser and backend records, test a sanitized one-slide copy, and prepare a useful issue report.
- Using AI Toolshtml-video Exports Default Text? Compare the Preview and Render InputsTrace html-video preview and export mismatches in Studio or the CLI. Check saved HTML, template variables, versions, and output files, then collect a minimal report.
- Using AI ToolsChatGPT missed PDF table rows? Check pages, row counts, and fieldsBefore totaling a PDF table in ChatGPT, compare expected rows, source locations, and field values. Use a six-row example and a copyable prompt to check gaps.
- Using AI ToolsJianying Skill: Diagnose Missing Media in DraftsA source-based guide to missing media in Jianying Skill drafts: check paths, IDs, cloud music and macOS errors, then prepare a useful issue report.
- Using AI ToolsLibrary vs. SDK vs. Framework vs. API: Who Calls Whom?Compare libraries, SDKs, frameworks, and APIs by tracing who calls whom, how data moves, and where errors occur in a runnable Python exercise.
- Using AI ToolsFrom a Python Script to a Small Project You Can RerunStructure a small rerunnable Python project with an entry point, input, helper module, JSON persistence, and README, then verify the result from a fresh process.
- Using AI ToolsHow Does Python Process Data? From Variables and Containers to Conditions and FunctionsTrace Python data from values and types through containers, conditions, loops, functions, and return values so you can predict behavior, locate failures, and verify output.
- Using AI ToolsWhere Is Python Actually Running? Understanding Anaconda, Jupyter, Terminal, and EnvironmentsTrace Python from interface and shell to interpreter, kernel, environment, packages, and working directory so you can diagnose common setup failures with evidence.
- Getting Started with AILLMs Are Not Knowledge Bases: Why Next-Token Prediction Can Produce Confidently Wrong AnswersUnderstand why fluent LLM output is not factual verification, and when AI applications need external data, retrieval, tools, validation, permissions, or human review.
- Using AI ToolsIs a Longer Context Always Better? From Tokens and Context Windows to Context EngineeringLearn how tokens, context windows, state, memory, and context engineering fit together—and why better-selected context matters more than simply adding more tokens.
- Getting Started with AITransformer Without the Math: What Attention and Embeddings Actually DoUnderstand Attention, Embeddings, and KV Cache without deriving matrices. Connect context, semantic search, RAG, and inference cost for AI application engineering.
- Using AI ToolsPrompt Is Not Magic: Structured Output, Tool Calling, and NondeterminismLearn how prompt constraints, Structured Output, Tool Calling, temperature, top-p, and invariant-based testing turn an LLM into a more reliable AI application component.
- AI Workflows & TeamsThe Model Can Be Fine and the System Can Still Fail: What Does Production AI Reliability Actually Mean?Learn why model quality alone does not make an AI application reliable, and how retrieval, tools, validation, fallback, observability, latency, cost, and evaluation shape production outcomes.
- Getting Started with AIWhat Exactly Is an AI Agent? From Chatbots to Closed-Loop Decision SystemsLearn why an AI Agent is more than an LLM with tools, and how Goal, State, Observation, Decision, Action, and Feedback form a closed-loop system.
- AI Workflows & TeamsLLM, RAG, Workflow, or Agent? Choosing the Minimum Necessary ComplexityLearn when to use deterministic code, an LLM, Retrieval or RAG, a Workflow, an Agent, or Multi-Agent—and why the simplest architecture that satisfies the task is often the strongest choice.
- AI Workflows & TeamsAn Agent Is More Than an LLM: How State, Tools, and Memory Form a Working SystemLearn how State, Context, Memory, Retrieval, Tools, and the Agent Runtime form a working closed loop—and why system truth should live outside model-generated text.
- AI Workflows & TeamsAction Space, Permissions, HITL, and Stop Conditions: How to Give an Agent Capability Without Losing ControlLearn how Action Space, least privilege, runtime permissions, HITL, reversibility, budgets, and Stop Conditions keep an Agent capable without giving it unlimited agency.
- Using AI ToolsCC Switch Setup: Verify a Provider Change and Switch BackConfigure one provider in CC Switch, verify requests and billing records, and test restoring your previous Codex CLI configuration.
- AI at WorkAI Video Editing: Start with a Talking-Head Rough Cut and SubtitlesPlan a first AI-assisted edit with explicit cut decisions, subtitle timing checks and a reviewable rough cut. Understand external transcription requirements.
- Using AI ToolsCodex Permission Mode Unavailable: A Four-Layer Diagnostic ChecklistCheck your Codex environment, workspace scope, file and network boundaries, approval policy and managed profiles before changing settings.
- Using AI ToolsExport HTML Animation to MP4 with Playwright and FFmpegRender a six-second HTML animation at 24 fps, encode 144 frames with FFmpeg, and verify the dimensions, duration and animation timing.
- AI TrendsAI Technical Weekly | 2026-W37: Agent Permissions and Inference Routing Move into RuntimeGitHub agent permissions, SageMaker prefix-aware routing, and CUDA 13.4 show production AI control moving into runtime policy, cache locality, and GPU isolation.
- AI Workflows & TeamsHow to Build AI Long-Term Memory with a Memory RouterBuild a small Memory Router that controls scope, retrieval, context injection, and version status without loading an entire knowledge base into every AI conversation.
- AI at WorkHow to Create an Editable AI PowerPoint—and Prove It Is EditableA PPTX filename does not prove editability. Use this three-slide exercise to verify native text, chart data, separate images, save, and reopen behavior.
- Using AI ToolsCan Claude Watch Videos? A Transcript-and-Frame WorkflowLearn what a transcript can prove, when frames are needed, and how to request a timestamped video summary without pretending Claude received the full video.
- AI at WorkHow to Build Traceable AI Notes in ObsidianUse five portable Markdown files to preserve sources, separate judgment from evidence, limit what AI receives, and verify the answer chain.
- Using AI ToolsHow to Back Up and Restore Codex Work When Moving ComputersSeparate projects, configuration, conversation context, and credentials; then verify file integrity and a real work path in an isolated migration exercise.
- AI TrendsAI Technical Weekly | 2026-W36: GPT-6 Astra, Gemini 3.8 Flash, and Agentic VideoGPT-6 Astra, Gemini 3.8 Flash, and agentic video understanding bring distinct questions about runtime control, GA model evaluation, and demand-driven multimodal retrieval.
- AI TrendsAI Technical Weekly | 2026-W35: Inference Chips, Hardware Agents, and Multimodal ModelsOpenAI Jalapeño, Anthropic MHS, and Gemini Omni 1.1 Flash move inference efficiency, hardware-agent control, and multimodal workflows forward without proving production readiness.
- Getting Started with AIHow to Complete Your First Reviewable Task With CodexComplete your first Codex task with safe source material, a bounded request, and a review checklist that lets you verify every important result.
- Getting Started with AIShould You Add Context, Examples, or a Reference Format?Diagnose why an AI result missed the mark, then add only the context, examples, or reference format that solves the specific gap.
- Getting Started with AIHow to Fix an AI First Draft Without Starting OverKeep what works, describe the expected result, actual result, and gap, then run one focused revision you can review against the original task.
- AI at WorkHow to Check Whether AI Citations and Numbers Are RealVerify that each AI citation exists, locate the exact supporting passage, recalculate important numbers, and check the surrounding context before use.
- AI at WorkHow Should You Verify AI Facts, Inferences, Advice, and Decisions?Classify AI output before checking it: trace facts to evidence, test inferences, compare recommendations, and keep final decisions with a named person.
- Using AI ToolsHow ChatGPT Data Access Changes Across Personal, Managed Accounts, and AppsUnderstand who can access ChatGPT data, how managed accounts differ from personal accounts, what connected apps can receive, and what to check about retention and permissions.