From task to shipped PR: how TaskNeuron's GitHub integration works

The gap between "the task says done" and "the code is actually merged" is where a lot of software plans quietly drift out of sync with reality. Someone marks a task complete before the PR lands; someone else finishes a PR but forgets to move the card; a week later the board and the repository tell two different stories and nobody trusts either. TaskNeuron's GitHub integration closes that gap by wiring your tasks to the pull requests that fulfill them. It's a paid integration for software projects on the Pro plan: install the GitHub App, connect a repository, and your board starts reflecting what's really happening in the codebase.

Getting connected

Setup lives in a software project's Settings. On the Pro plan, you install the GitHub App and connect a repository — the same App-based model GitHub uses everywhere, so access is scoped to the repositories you choose and revocable from GitHub itself. Once a repo is connected, the project knows how to associate its tasks with that repository's pull-request activity. There's no per-task configuration to maintain; you connect once and the rest keys off normal Git workflow.

Linking a PR to a task

You can let the link happen automatically — TaskNeuron matches a pull request to a task by its id in the branch name, the PR title, or the body. In practice that means a branch named with the task id (e.g. task_…) links itself the moment the PR opens, with zero extra steps for the person writing the code. If you'd rather link by hand, the task's Pull requests section takes a PR URL or an owner/repo#number reference. Either way, the task and the PR become the same story told in two places, kept in step.

This is deliberately forgiving. Teams name branches differently, some people open PRs before they remember the task exists, and legacy work predates any convention — so both the automatic and the manual paths are first-class rather than one being a fallback.

The board follows the code

Once linked, the task tracks the PR's lifecycle automatically. Opening the PR moves the task to In progress, marking it ready for review moves it to In review, and merging it moves the task to Completed. The columns on your board stop being something people remember to update and start being a live readout of the repository.

It goes deeper than status. The PR's message and every commit message are mirrored into the task's discussion, so the task page becomes a running record of how the work actually came together — the reasoning in the PR description, the commits that built it, all next to the plan that asked for it. When you come back to a finished task months later, the whole history is in one place instead of scattered across two systems.

Non-destructive by design

Completing a task comments back on its open PRs to note the change, but it never merges or closes them. That boundary is deliberate and worth stating plainly: TaskNeuron reflects and annotates your Git activity — it does not take irreversible actions in your repository on your behalf. The integration reads status and writes comments; it doesn't ship code. You stay in control of what actually lands, always.

Add the AI Code Assistant

The base integration keeps the board and the repo honest. The optional AI Code Assistant add-on, enabled per repository, adds a layer of AI review on top — three capabilities, each posting back to the PR where your team already works.

Code review posts a review of each PR's diff, so a first pass of feedback is waiting before a human even opens it. CI failure analysis watches your checks and, when one goes red, posts a comment with a likely cause and a suggested fix — turning a cryptic red X into a starting point. And PR summaries post a plain-language overview of what a change does, which is the difference between a reviewer understanding a large diff in a minute versus reverse-engineering it for twenty.

Because these are additive, new capabilities slot in without changing how repositories are connected. You wire up the repo once; the AI layer grows underneath it without a migration.

Where it fits the bigger picture

Put together, this is what "AI that executes" looks like in practice for software teams. The plan lives in TaskNeuron as development-grade, PR-sized tasks. AI agents — connected over MCP — can pull those tasks and open pull requests. GitHub activity flows back to move the board and enrich the task history, and the AI Code Assistant reviews the work as it arrives. Every layer reinforces the others, and through all of it a human still approves every merge. The plan and the code stay a single, honest story.