Building your first agentic workflow with Google Anti-Gravity

Most automation platforms require users to understand every node, connector, and execution detail before anything works. Google’s Anti-Gravity takes a different approach. Instead of assembling workflows visually, users describe what they want in natural language and let the system build, debug, and improve the workflow over time.

This article breaks down a complete agentic workflow built with Anti-Gravity, based on a real example: scraping Google My Business listings, enriching lead data, scoring prospects, generating outreach copy, and exporting everything into Google Sheets.

TL;DR

  • Problem: Traditional automation tools require deep platform knowledge and constant debugging.
  • Solution: Google Anti-Gravity builds and improves workflows through natural language instructions.
  • Outcome: Faster setup of complex agentic workflows with less manual maintenance.

What Anti-Gravity is designed to do

Anti-Gravity is an agentic development environment that allows users to build workflows by chatting with an AI agent. Instead of manually wiring steps together, users describe the desired outcome and let the system generate the necessary structure and execution logic.

Unlike visual automation tools, Anti-Gravity operates as a blank slate. Users are not limited to predefined connectors or templates and can build custom solutions tailored to specific problems.

Core interface components

Anti-Gravity is structured around four main areas:

  • File explorer on the left, similar to Google Drive folders
  • Agent panel on the right, where users communicate with the AI
  • Workspace in the center, where files and scripts are created
  • Terminal at the bottom, used to execute workflows and view results

The agent behaves like a junior developer that writes, revises, and improves code based on instructions.

The DO framework: directive, observation, experiment

To structure interactions with Anti-Gravity, the workflow uses the DO framework:

  • Directive: clearly state what the system should do
  • Observation: review what the agent generates
  • Experiment: iterate and improve results over time

This framework acknowledges that outputs are rarely perfect on the first attempt and encourages continuous refinement.

Creating the initial scaffolding

The workflow starts by creating a project folder and a master markdown file called agent.md. This file defines the high-level instructions for the system.

When instructed to read agent.md and build scaffolding, Anti-Gravity automatically generates:

  • Folder structure
  • Directive files
  • Execution scripts
  • Environment configuration
  • Temporary output directories

Sensitive information such as API keys is stored in environment files rather than hard-coded into scripts.

Self-healing execution model

A key difference between Anti-Gravity and traditional automation platforms is self-healing. When the system encounters an error during execution, it:

  • Detects the failure
  • Updates the relevant code
  • Prevents the same error from recurring

This significantly reduces manual debugging, which is often the most time-consuming part of automation work.

Step 1: scraping Google My Business listings

The first directive instructs Anti-Gravity to scrape Google My Business listings for a specific niche and location, such as plumbers in Miami.

The system automatically generates a script that extracts:

  • Business name
  • Category
  • Address
  • Phone number
  • Website
  • Ratings and hours

Results are stored in temporary output files and can be validated against live listings.

Step 2: enriching lead data

Basic listings often lack critical information. The next directive expands the workflow by visiting each business website and extracting:

  • Email addresses
  • Social media profiles
  • Additional business signals

At this stage, the workflow becomes more practical for lead generation rather than simple data collection.

Step 3: scoring and outreach generation

The workflow then applies a scoring system to each lead. In this example:

  • Base score for being a service business
  • Additional points if an email address exists
  • Additional points if social profiles are present

Using the enriched data, the agent also generates a short cold email introduction tailored to each business.

All of this logic is generated and maintained automatically by Anti-Gravity.

Step 4: exporting results to Google Sheets

Temporary files are useful for testing, but persistent storage is required for collaboration. The final step exports all results into Google Sheets.

This requires:

  • A Google Sheets ID
  • A service account
  • A credentials JSON file
  • Enabling Google Drive and Google Sheets APIs

Once configured, Anti-Gravity posts structured data directly into a spreadsheet, including lead details, scores, and generated outreach text.

Execution flow overview

The complete workflow operates as follows:

  1. Scrape Google My Business listings
  2. Visit each website for enrichment
  3. Score leads based on defined criteria
  4. Generate outreach copy
  5. Export structured data to Google Sheets

Each step is orchestrated automatically by the agent without manual wiring.

Anti-Gravity vs traditional automation tools

Anti-Gravity and visual automation platforms serve different use cases.

Strengths of Anti-Gravity

  • Natural language workflow creation
  • Custom solutions beyond predefined connectors
  • Self-healing error handling
  • Faster iteration for complex logic

Limitations

  • Runs locally by default
  • Less visual than drag-and-drop builders
  • Debugging is harder if deep code issues arise
  • Not ideal for mission-critical uptime without cloud deployment

Verdict

Google Anti-Gravity shifts automation from node-based configuration to agent-driven execution. By allowing users to describe outcomes instead of assembling steps, it lowers the barrier to building advanced workflows.

For experimentation, custom data pipelines, and rapid prototyping of agentic systems, Anti-Gravity offers flexibility that traditional platforms struggle to match. It is best suited for builders who value adaptability over visual simplicity.

FAQ

Do you need to know Python to use Anti-Gravity?

No. The system generates and maintains the code automatically.

Is Anti-Gravity cloud-based?

No. It runs locally unless deployed to a cloud environment.

Can it replace traditional automation platforms?

Not entirely. It complements them for custom or experimental workflows.

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