Cursor IDE and Make: Building Parallel Agentic Workflows for Power Users

TL;DR

• Cursor IDE is a game-changing AI code editor that understands your entire codebase.
• Make (formerly Integromat) is a visual automation platform that connects thousands of apps.
• Combining them allows you to build parallel agentic workflows, where multiple AI agents handle distinct development tasks simultaneously.
• You can automate code reviews, issue tracking, and deployment updates directly from your IDE to your project management tools.

Are you tired of jumping between your code editor, Slack, Jira, and GitHub, trying to keep every part of your development process in sync? For power users and solo developers, context switching is the ultimate productivity killer. Enter the dynamic duo of Cursor IDE and Make.

By harnessing the AI-native intelligence of Cursor alongside the visual orchestration power of Make, you can build parallel agentic workflows—systems where multiple AI "agents" operate simultaneously to write code, review PRs, update tickets, and notify stakeholders.

In this deep dive, we'll explore how to connect these two powerhouse tools to create an automated, agentic development environment that feels like having a team of senior developers working right alongside you.

Why Cursor IDE is the Foundation of Agentic Coding

If you haven't checked out our full Cursor IDE Review, here's the short version: Cursor is a fork of VS Code built from the ground up for AI-assisted programming.

Unlike basic Copilot extensions, Cursor has codebase context. It can read your entire repository, reference documentation, and understand the intricate relationships between your files. Features like Cursor Composer allow you to generate entire features across multiple files with a single prompt.

But where Cursor truly shines for power users is its ability to act as the primary interface for your developer intent. You aren't just writing code; you are directing an AI to build systems.

The Shift to "Agentic" Workflows

An agentic workflow is one where an AI system doesn't just autocomplete your thoughts—it takes a high-level goal, breaks it down, executes it, and verifies the results. Cursor's new features are increasingly moving in this direction. However, an IDE is inherently sandboxed. It knows your code, but it doesn't natively talk to your CRM, your customer support tickets, or your social media accounts.

That's where Make steps in.

Make.com: The Orchestration Layer

Make is a visual automation platform that lets you connect APIs without writing glue code. Think of it as a more powerful, developer-friendly version of Zapier. (We cover this extensively in our Make.com Automation Guide).

While Cursor handles the code generation and logic, Make handles the routing, notifications, and cross-platform integrations. By triggering Make webhooks directly from your Cursor environment (via custom scripts or AI commands), you can kick off massive parallel workflows.

Building a Parallel Agentic Workflow

Let's walk through a real-world scenario for a power user building a SaaS application.

The Goal

When you finish coding a new feature in Cursor, you want the following things to happen simultaneously (in parallel):

1. Code is committed and pushed to GitHub.
2. An AI agent reviews the code for security vulnerabilities.
3. Your Linear or Jira ticket is moved to "Done" and populated with a changelog.
4. A notification is sent to the #engineering Slack channel.
5. A draft tweet is created for your marketing account announcing the feature.

Step 1: The Trigger in Cursor

To kick off a Make scenario from Cursor, the simplest method is a lightweight bash script or a Node.js script that fires a webhook. Because Cursor allows you to run terminal commands natively and even has its AI agent run them for you, you can instruct Cursor:

"I'm done with the billing feature. Run the deploy script and summarize my changes for the webhook."

Cursor can analyze the git diff, generate a concise human-readable summary, and pass that summary as a JSON payload to a Make Webhook URL via a curl command.

# Example webhook trigger script
curl -X POST -H "Content-Type: application/json" \
     -d '{"feature": "Stripe Integration", "diff": "...", "status": "completed"}' \
     https://hook.eu1.make.com/your-unique-webhook-id

Step 2: Designing the Make Scenario

Inside Make, you start with a Webhooks module listening for that payload. From there, you use a Router module to split the workflow into parallel paths.

Path A: The Security Auditor Agent (OpenAI + GitHub)

Make receives the diff from Cursor. It sends this diff to an OpenAI API module with a system prompt: "You are a strict security engineer. Review this diff for vulnerabilities. Return 'PASS' or list the issues."

If the AI returns issues, Make automatically creates a GitHub issue labeled security-audit-failed and pings you on Discord. This acts as a secondary, objective reviewer working in parallel to your own checks.

Path B: Project Management Sync

Simultaneously, Make takes the "feature name" and searches your Notion or Jira for the corresponding ticket. It updates the status, drops in the summary generated by Cursor, and logs the time of completion.

Path C: Marketing Drafts

Why wait to do marketing? Make takes the technical summary, passes it to Anthropic's Claude API (or ChatGPT), and says: "Translate this technical update into an engaging, 280-character tweet for a SaaS audience." Make then saves this draft directly into your Buffer or X (Twitter) drafts folder.

Why Parallel Execution Matters

If you were to do these tasks sequentially, it would take you 20-30 minutes of administrative overhead per feature. If a sequential script fails at step 2, steps 3-5 never happen.

By using Make's Router, these agentic tasks happen in parallel. Your marketing draft is generating at the exact same millisecond your code is being security-scanned. This is the essence of a 10x Developer Workflow.

Advanced Techniques for Power Users

Once you have the basic webhook-to-router setup, you can scale this massively.

1. Two-Way Communication

Make shouldn't just receive data; it can send data back. You can configure Make to trigger a GitHub Action that modifies a file, or write to a cloud database that your local environment is polling. You can even use Make to fetch new customer bug reports from Intercom and drop them directly into a todo.md file in your active Cursor workspace.

2. Multi-Agent Debates

In a complex Make scenario, you can have two different LLMs review the code sent from Cursor. For example, GPT-4o checks for logic, while Claude 3.5 Sonnet checks for UI/UX consistency. You can use an Iterator in Make to consolidate their feedback into a single Slack message.

3. Integrating with Local LLMs

For the privacy-conscious, instead of routing your diffs to OpenAI, your Cursor terminal script can route them to a local instance of Ollama running Llama-3, process the review locally, and only send the results to Make for the routing and notifications.

Best Practices for Reliability

When building AI workflows, things will inevitably get weird. LLMs hallucinate, APIs timeout, and payloads get malformed.

1. Structured Outputs: When asking Cursor to send data to Make, force it to use JSON schemas. Do not rely on loose text formatting.
2. Error Handlers in Make: Always attach error handler routes to your API calls. If the OpenAI API times out, Make should send you a quick Slack message rather than silently failing.
3. Keep the Humans in the Loop: Notice that the workflow creates a draft tweet and a draft PR review. Until your agents prove 100% reliable, use them to prepare work for your final approval, not to execute destructive actions.

Conclusion

The convergence of AI-assisted coding and visual automation is creating a new paradigm for solo developers and small teams. By treating Cursor IDE not just as an editor, but as the command center for parallel agentic workflows orchestrated by Make, you can effectively clone yourself.

You write the code; the agents handle the bureaucracy.

Ready to level up your stack? Check out our guide on The Best AI Tools for Developers in 2026 to see what else you should be integrating into your Make scenarios.

Have you built an interesting workflow between your IDE and an automation platform? Reach out on X/Twitter and let us know!