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Agentic coding

Development where AI acts through tools to edit and verify code.

An everyday example

An assistant edits the ledger rather than only explaining how.

See how these concepts connect
How an assistant moves from task to actionEveryday role → development concept
  1. Work orderPrompt & context
  2. Choose next actionModel
  3. Use equipmentTool call
  4. Inspect and decideAgent loop

A harness coordinates the loop: a model suggests actions, tools execute, and results are checked. Skills provide procedures; MCP can connect tools. Neither is the model.

Where this term is useful

These are related contexts, not prerequisites.

Back in the project

When it comes up: When extending or authorizing AI task execution.

What to do next: Identify the task, tools, permissions, and checks; grant only necessary access.

Open the related method and steps
What can this analogy leave out?

A skill is not a model, and MCP is not a plugin store; connectivity is not unlimited authorization.

Everyday examples explain roles and relationships; actual behavior follows the tool, language, or platform.

Find the starting point

Module shortcuts

What people build · AI revenue research · 50 ideas · GitHubComplete roadmap · idea to releaseWrite down the ideaI only know I want a websitePrepare a project briefUnsure how to describe the first flowOpen an AI tool that can edit filesInstallation, sign-in, or the screen differsCreate a folder for the projectDocuments or the folder is missingOpen that folder in the AI toolAI names a different projectCreate Git history and project instructionsCommit fails or asks for identityInspect a file AI actually createdPrevious files are missingAnswer one question at a timeAI asks about unfamiliar technical termsChoose only this version’s essentialsReducing scope left only a pictureKeep the agreement in plain languageThe document is too long to reviewDescribe how people will use itAI lists features without a user flowReview a key screen before buildingThe prototype may use simulated behaviorLet AI choose from actual conditionsI do not know local versus shared storageAsk AI for the next small taskThe first task just says “build frontend”Check the runtime and start the projectInstallation or startup failsOpen the first page of the projectThe preview will not openAdjust this page onlyA visual edit changed other behaviorMake Save retain real contentCannot save, or records vanish on refreshFinish the whole flow onceThe button responds but nothing happensTry blank input and repeated clicksBlank or duplicate records appearReopen it after stoppingThe address fails the next dayCheck it against the original ideaAI says done, but I cannot use itRecord the trial feedbackThe issue happens intermittentlyPlan the fix and its passing checksAI starts fixing without a planFix according to plan and hand back for retestingThe same action still fails after a claimed fixChoose: personal use or sharingThe shared local link does not openAssess readiness for deliveryReadiness is claimed without evidencePrepare and try the deliverableInstaller or deployed application failsApprove delivery and verify the real entryIt opens locally but not for othersOptional: publish a simple page on GitHub PagesThe public URL returns 404Continue next time without starting overAI wants to start over in a new chatChoose a tool · Codex Claude Cursor Qoder TRAE Kimi pricingHomeProject typesTalking to agents · prompts and troubleshootingChoosing a stackFrontend & UI · component dictionaryGlossary · AI and development · examples and diagramsOpen the tool and verify project accessPrepare the project, version history, and AI rulesDescribe the intended interface styleHelp AI change exactly one targetBackend: storage and accessTesting: check that it worksDeployment: deliver a real entry pointMaintenance: keep the product usableWebsites & web apps · The idea, one link away.Mini programs · Build where the users already are.Mobile apps · Turn a good idea into an everyday app.Desktop apps · Make a tool for repetitive tasks.

A practical guide for beginners

This bilingual practical guide has 6 stages, 18 milestones and 31 actions. App illustrations are examples; users verify their own project results.