Mastering Anti-Gravity Artifacts: Task Lists, Implementation Plans, and Walkthroughs

In the rapidly evolving landscape of AI-assisted development, tools like Google DeepMind’s Anti-Gravity represent a fundamental shift. We’re moving away from simple code completion and into a new era of agent-driven workflows. But to truly harness the power of an AI coding partner, developers must learn a new language-not of code, but of collaboration. This language is built on a foundation of what Anti-Gravity calls “Artifacts.”

These artifacts-the Task List, the Implementation Plan, and the Walkthrough-are more than just log files or status updates. They are the living, breathing consciousness of your AI agent. They are your window into its thought process, your lever for steering its strategy, and your final quality gate before a single line of code is committed. Mastering them is the key to graduating from simply prompting an AI to truly partnering with it.

Beyond Code Gen: Moving from Prompting to Partnership

The old paradigm was about asking an AI to generate a snippet of code. The new paradigm is about giving an AI a high-level goal and managing the entire lifecycle of that task. This requires a different set of skills centered on strategic oversight, review, and direction.

The Three Core Artifacts: Your Agent’s Plan, Proof, and Progress

Think of the artifacts as a complete, transparent project management system for every task you assign. Instead of a black box where you send a prompt and hope for the best, Anti-Gravity provides a clear, three-act structure for every unit of work:

• The Task List: The agent's real-time to-do list, showing its current focus and what's next.
• The Implementation Plan: The agent's research and strategic blueprint, presented for your review and approval before it writes code.
• The Walkthrough: The agent's final report, delivering the completed feature along with proof of its work, including screenshots and test recordings.

This guide will dissect each artifact, providing you with the strategic framework to use them not just as notifications, but as your primary control panel for AI-driven development.

Deep Dive 1: The Task List - Your Agent’s Real-Time To-Do List

The Task List is the most granular and dynamic of the three artifacts. It’s the agent externalizing its internal monologue, breaking down a complex request like “Build a flight tracker app” into a series of concrete, actionable steps. It’s the first place you should look to understand how the agent has interpreted your request.

Anatomy of a Task List

A typical Task List includes:

• Checked Items: Steps the agent has already completed (e.g., `run create-next-app`).
• Current Task: The single item the agent is actively working on, often highlighted.
• Upcoming Tasks: The sequence of steps the agent plans to take next.

This isn’t just a simple checklist. The agent constantly updates it, adding new steps as it discovers dependencies or removing them if a chosen path proves fruitless. It’s a dynamic reflection of its problem-solving process.

Strategic Use: How to Monitor Progress and Identify Blockers

The Task List is your early warning system. While you can let the agent run in the background, a quick glance at the list can reveal if it’s heading in the wrong direction. If you see it getting stuck in a loop or adding tasks unrelated to your goal, you know it’s time to intervene with a clarifying comment. This passive supervision is far more efficient than constant babysitting.

Pro-Tip: Use the Task List to gauge the complexity of your request. A short, straightforward list means the agent has high confidence. A long, convoluted list with many research-oriented tasks might indicate an ambiguous prompt that needs refining.

Deep Dive 2: The Implementation Plan - The Blueprint for Success

This is arguably the most critical artifact and your primary point of interaction. The Implementation Plan is a formal proposal from the agent, created after it has completed its initial research and before it modifies your codebase. It stops the workflow and explicitly asks for your approval, embodying the “human-in-the-loop” philosophy.

Anatomy of an Implementation Plan

These detailed markdown files are rich with information, typically including:

• Summary: A high-level overview of the agent's understanding of the task.
• Research Findings: Links to documentation it read, API schemas it analyzed, or conclusions it drew from exploring your existing code.
• Proposed Changes: A list of files it plans to create, modify, or delete.
• Component Breakdown: For UI tasks, it might outline new components, their props, and state management strategy.
• Verification Steps: A clear description of how it intends to prove the task is complete (e.g., "Run the dev server and test the form with a sample flight number").

The Review Process: Your Most Critical Interaction Point

Reviewing an Implementation Plan is like conducting a pre-code review. Your job is to act as the senior architect, validating the agent’s strategy. Ask yourself:

1. Does the agent correctly understand the goal?
2. Is its proposed technical approach sound and aligned with my project's patterns?
3. Has it identified the correct files to modify?
4. Are its verification steps sufficient to prove success?

This is your chance to prevent wasted effort. A five-minute review here can save hours of work correcting a flawed implementation.

Pro-Tip: How to Provide Effective Feedback and Comments

Anti-Gravity allows you to comment directly on the Implementation Plan, just like in a Google Doc. This is your primary tool for steering the agent. Be specific and directive:

Instead of: “That’s wrong.” Try: “Use the API key I provided in the .env.local file, do not hardcode it.”

Instead of: “I don’t like this.” Try: “Implement this logic in a utils folder so it can be reused. Do not modify the main route file directly yet.”

By providing clear, actionable feedback, you refine the agent’s plan, teach it your preferences, and ensure the resulting code meets your standards before it’s even written.

Deep Dive 3: The Walkthrough - The AI-Generated Final Report

After you approve an Implementation Plan and the agent completes its work, it generates the final artifact: the Walkthrough. This is the agent’s deliverable, a comprehensive report that summarizes what it did and, crucially, provides evidence of its success.

Anatomy of a Walkthrough

The Walkthrough serves as a dynamic, AI-generated pull request description. It typically contains:

• Features Implemented: A bulleted list of the changes made, described in user-centric terms.
• Verification Evidence: The most powerful part. This section includes concrete proof, which can be:
  • Screenshots: Images of the UI showing the new feature.
  • Screen Recordings: Short videos of the agent interacting with the app, filling out forms, or clicking buttons to test the full user flow.
  • Terminal Output: Logs from commands it ran, such as passing unit tests.
• Links to Code: Direct links to the modified files for final review.

The Final Quality Gate: Best Practices for Reviewing

The Walkthrough is your final check. Don’t just skim it. Scrutinize the evidence. Does the screenshot match the requirements? Does the screen recording show the correct behavior, including handling of edge cases? The agent’s ability to automatically test its own code via the integrated browser is a game-changer, and the Walkthrough is where you reap the benefits of that capability. If the proof is solid, you can commit the code with high confidence.

A Strategic Framework: Integrating Artifacts into Your Daily Workflow

To truly master Anti-Gravity, you need to map its artifact-driven workflow to your existing development habits. The new process supercharges the old one by offloading cognitive and manual effort to the agent.

• From Jira Ticket to Implementation Plan: Your initial prompt to the agent is like the title of a ticket. The subsequent review of the Implementation Plan is the new "backlog grooming" or "sprint planning," where you and the agent align on the scope and approach before any work begins.
• From Pull Request to Walkthrough: The Walkthrough replaces the manual process of writing a PR description and taking screenshots. The review process is similar, but instead of just reviewing code, you're reviewing a holistic report that includes the code, its purpose, and its proven functionality.
• Managing Multiple Agents: The Anti-Gravity Agent Manager acts as your central hub. It allows you to triage artifacts across multiple tasks and projects. You can kick off a long-running research task, switch to a quick bug fix, and be notified when the Implementation Plan for the research is ready for your review. This enables a new level of parallelization in your work.

Common Pitfalls and Advanced Tips

Avoiding common anti-patterns is key to a successful partnership with your AI agent.

• Anti-Pattern: The Vague Prompt. Giving a one-line, ambiguous prompt like "Fix the login page" will likely result in a rambling, incorrect Implementation Plan. Be specific and provide context to get a high-quality plan on the first try.
• Anti-Pattern: The Rubber Stamp Approval. Blindly clicking "Approve" on every Implementation Plan without a critical review defeats the purpose of the system. This is your main chance to course-correct the agent; use it wisely to prevent wasted cycles.
• Anti-Pattern: Ignoring the Verification Evidence. Accepting a Walkthrough just because the code looks plausible is a mistake. The real value is in the proof. If the agent's screen recording doesn't test the edge cases you care about, reject the Walkthrough and ask for more thorough verification.
• Advanced Technique: Mastering the Feedback Loop. Don't be afraid to reject artifacts. A powerful workflow is to reject a Walkthrough with a comment like, "The implementation is correct, but you forgot to add unit tests." The agent will then start a new sub-task, generate a new Implementation Plan for adding the tests, and submit a revised Walkthrough. This iterative process is how you coach the agent to produce production-quality work.

Conclusion: Artifacts Aren’t Just Reports, They’re Your Control Panel

The introduction of Anti-Gravity and its artifact-driven workflow signals a profound change for developers. The most valuable skill in this new paradigm is no longer just writing code, but effectively directing, reviewing, and refining the work of a powerful AI agent. The Task List, Implementation Plan, and Walkthrough are the essential levers for that direction.

By mastering these tools, you transform the development process from a solitary act of creation into a dynamic collaboration. You become the architect, the strategist, and the quality lead, empowering your AI partner to handle the implementation details at a speed and scale previously unimaginable. This isn’t just a new way to code; it’s a new way to build.

What part of the artifact workflow are you most excited to integrate into your daily routine? Share your thoughts in the comments below!