What does an AI workflow with Neovim look like?

A cycle of three steps: load context (the task, the rules, where the last session stopped), make a scoped edit, and verify with tests or type checks before moving on. The cycle repeats for each task, with progress saved before the session ends.

Why save progress outside the editor?

Neovim chat history is local to a session. When the session ends, that context is gone. Saving progress to an external record means the next session, in any editor or with any model, starts from the same known state rather than re-inferring it from the code.

How do I give a Neovim AI assistant project rules?

If the assistant supports MCP, connect it to fenbs and ask it to read the project context at the start of the session. If it does not, paste the key rules and the current task description manually. The rules tell the assistant what the team has already decided, so it does not need to infer or re-decide.

How specific should a task be before I ask the assistant to edit code?

Specific enough to have a check: a test that must pass, a type error that must be resolved, a linting rule that must be satisfied. A task with a check has a clear completion condition. A description without a check is resolved when the assistant decides it is done, which may not match your expectation.

Does fenbs support Neovim directly?

fenbs connects over MCP, a standard protocol that AI assistants use to read from and write to external tools. Whether your Neovim AI plugin supports MCP depends on the plugin. If it does, connect it from the integrations page. If it does not, you can still use fenbs from a separate terminal session or the web app.

AI Workflow With Neovim: From a Task to a Checked Change

A Neovim AI workflow pairs an AI assistant plugin with a clear task, a code edit, and a verification step. Here is how to organize that flow so the project rules and saved progress stay outside the editor, available in any tool.

June 15, 2026Updated October 21, 20265 min read

An AI workflow with Neovim pairs an AI assistant plugin — such as one built on MCP or a model API — with the tasks and rules that give the assistant its context. The workflow moves from a clear task to a code edit to a verified change, with each step having a defined result.

The challenge is that Neovim chat history is local to a session. Project rules, prior decisions, and where the work stands disappear when the session ends. Tools like fenbs hold that record outside the editor so the next session, in Neovim or any other tool, starts from the same known state. AI workflows for education, research, and advertising are covered on their own pages.

The anatomy of a Neovim AI workflow step

Each step has three parts: context in, action, check.

Context in: what the assistant reads before acting. This includes the task description, the relevant project rules, and where the last session stopped. Without this, the assistant infers context from the buffer, which is incomplete.
Action: the code edit or command the assistant produces. Keep each action scoped to one change with a clear outcome: the function is implemented, the test passes, the linting error is resolved.
Check: the verification that the action produced the expected result. Run the tests, check the type errors, read the diff. A check that does not happen is a change that may break something later.

Loading project rules at the start of a session

Before asking the assistant to do anything, give it the project rules that apply to this work. Rules might cover naming conventions, the architecture decisions that affect this file, or constraints the team has agreed on. An assistant that starts from the buffer alone will make the same mistakes the team already resolved.

If the assistant plugin supports MCP connections, connect it to fenbs and ask it to read the project context. It will load the rules first, then Where we left off, then the active task. If it does not support MCP yet, paste the key rules and the current task description manually at the start of the session.

How fenbs helps

Keep the rules outside the editor

fenbs holds the project rules and Where we left off that your Neovim assistant reads at the start of a session. Rules appear first: naming conventions, architecture decisions, constraints the team agreed on. Where we left off names the task, its current state, and the next step. Any connected AI tool reads the same record. Create a free account and add your first project.

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Scoping the task before the edit

Before asking the assistant to edit code, name the task and its completion condition. "Refactor the auth module" is a description of work; "Extract the token validation logic into a separate function with its existing tests still passing" is a task with a check.

A scoped task limits how far the assistant reaches. An assistant given a narrow task edits the files that task involves. An assistant given a broad description may touch unrelated files, rename things that other parts of the codebase depend on, or make decisions that belong to the team, not the current session.

Write the task in fenbs before the session starts. It takes two minutes and gives the assistant something specific to read rather than inferring the goal from the buffer.

Verifying the change

After the assistant makes an edit, verify before moving on. Run the tests in the terminal. Check the type errors. Read the diff in the Neovim buffer. Each of these is a different kind of check that catches a different kind of error.

When a check fails, record what failed and what the error was before asking the assistant to fix it. The assistant that made the edit has the context to understand the error; recording it also means the next session knows this path was tried.

Do not move to the next task until the current check passes. A backlog of unchecked edits is harder to untangle than a slow, verified progress.

Saving progress before the session ends

Before closing Neovim, record where the work stands. This does not need to be detailed: the task, what was completed, what the next step is, and anything that needs a decision. Save it to fenbs so the next session — in Neovim, in a different editor, or with a different model — starts from the same point.

An assistant that ends a session without saving progress leaves the next session to re-read the code and re-infer the state. Two minutes of progress notes saves fifteen minutes of reconstruction.

How to do this with fenbs

Create a free account and add your project in fenbs. Write the current task as a task card with its goal and the conditions for completion.
Connect your Neovim AI assistant from Integrations if it supports MCP. At the start of each session, ask it to read the project context: rules, Where we left off, and the active task.
Before each edit, confirm the task scope with the assistant. Ask it to state what it is about to change and why, then review before it proceeds.
After each significant edit, run the relevant checks: tests, type checker, linter. Record the result in the task note in fenbs.
Before ending the session, ask the assistant to save progress: completed steps, the next step, and anything waiting on a decision. Update Where we left off in fenbs.

fenbs does not replace Neovim's own plugin ecosystem for AI features. It holds the project record that makes those features more accurate: the rules that prevent repeated mistakes, and the progress notes that prevent repeated work.