What Is an Agentic AI Workflow?

A chatbot answers once. An agent loops: it plans, uses a tool, checks the result, and repeats. Learn when an agentic workflow beats a single prompt.

A Chat Answers. An Agent Acts.

A normal chat is one turn: you ask, the model writes, you read. That is the right tool for a headline, a summary, or a first draft. An agentic workflow is a loop. The model plans a step, uses a tool (read a file, run a command, search the web, generate an image), looks at the result, and decides what to do next — until the job is done or you stop it. The model is not just talking. It is working.

Tools are the agent's hands

Without tools, a model can only produce text. With tools it can inspect a repo, run tests, fetch a page, upload a file, or call Gab AI's image and video APIs. The loop is what makes those tools useful instead of a one-off trick.

The Loop, In Plain Language

Every serious agent — Pi, Hermes, Claude Code, Cursor, OpenCode, Codex, Prime Agent — runs some version of this cycle:

When a Single Prompt Is Enough

Do not start an agent for work that is one good reply. Agents cost more, take longer, and can edit files you did not mean to touch. Use a chat when the output is text you will review in place. Use an agent when the work requires looking at the real system.

Use a chat when

• You need a draft, outline, explanation, or rewrite
• The facts fit in the prompt (or one uploaded file)
• You will paste the result somewhere else yourself
• You are exploring an idea, not changing a codebase

Use an agent when

• The job lives in a repo, a folder, or a running app
• Success is measurable: tests pass, a file exists, a command exits 0
• The model must look at something it cannot see in the prompt
• The work is several steps that each depend on the last result

Two Kinds of Agents on Gab AI

Gab AI has in-app custom agents — reusable specialists with a job description, which you already covered in Custom Agents. Agentic CLIs are different: they run on your machine, hold tools, and spend API credits through your Gab AI key. You can use both. A custom agent is the brief that never forgets your voice. Pi or Hermes is the worker that can actually open the repo.

The CLIs run on the Gab AI API

When this course says Pi, Hermes, Cursor, or Claude Code, it means those tools pointed at Gab AI — not at OpenAI or Anthropic. Next lesson: create a Gab AI API key and set the base URL to https://gab.ai/v1. In-app custom agents already run on Gab AI; they do not need a key.

Function calling is not optional

The loop only works on models that support tool/function calling. If the agent never calls a tool and just dumps a plan as markdown, switch to a Gab AI model from GET https://gab.ai/v1/models with function_calling enabled — or use auto and let Gab AI pick one that can.

Tools are the agent's hands

Without tools, a model can only produce text. With tools it can inspect a repo, run tests, fetch a page, upload a file, or call Gab AI's image and video APIs. The loop is what makes those tools useful instead of a one-off trick.

1. 1. Observe — Read the brief, the repo, the error, or the last tool result. The agent should look before it writes.
2. 2. Plan one step — Not the whole project. The next move: which file, which command, which search. Big plans rot the moment the first tool returns something unexpected.
3. 3. Use a tool — Call the function — read_file, bash, web_search, gab_generate_image, whatever the harness exposed. This is the part a chatbot cannot do.
4. 4. Check, then repeat or stop — Did the test pass? Did the file actually change? If the definition of done is met, stop. If not, loop. If the same step failed twice, stop and ask you — do not burn credits on a retry spiral.

The CLIs run on the Gab AI API

When this course says Pi, Hermes, Cursor, or Claude Code, it means those tools pointed at Gab AI — not at OpenAI or Anthropic. Next lesson: create a Gab AI API key and set the base URL to https://gab.ai/v1. In-app custom agents already run on Gab AI; they do not need a key.

Function calling is not optional

The loop only works on models that support tool/function calling. If the agent never calls a tool and just dumps a plan as markdown, switch to a Gab AI model from GET https://gab.ai/v1/models with function_calling enabled — or use auto and let Gab AI pick one that can.

• A chatbot produces text. An agent loops: observe, plan one step, use a tool, check the result, repeat or stop.
• Use a chat for drafts and explanations. Use an agent when the work requires files, commands, tests, or other tools.
• Gab custom agents remember the brief in the app. Pi, Hermes, and similar CLIs do the tool-using work on your machine — through the Gab AI API.
• Pick a Gab AI model that supports function calling, or the loop never starts.

Last updated: 2026-08-21