Introduction

Announcing the launch of the Entelligence AI extension for VS Code, Cursor, and Windsurf, an in‑IDE code reviewer that gives you immediate feedback before you even open a pull request.

In this post, we'll walk through how Entelligence AI stacks up against Cursor (BugBot). Whether you're focused on deep code reviews, quick fixes, or streamlined workflows, you'll see which tool fits your style and why Entelligence AI might be just what you need.

What Is Entelligence AI?

Entelligence.AI is your team's AI-powered engineering intelligence platform that streamlines development, enhances collaboration, and accelerates engineering productivity. It works as a quiet companion around your codebase, helping your team stay aligned without changing how you work.

Instead of asking you to follow new processes, it supports everyday tasks like reviewing pull requests, onboarding, and tracking team performance. It's built to handle the important things that often get missed.

It also respects your privacy, your code is never used for training, and you can self-host it if needed.

What Is BugBot?

BugBot is Cursor's built-in tool for reviewing pull requests on GitHub. Once installed, it runs automatically (or when you ask via bugbot run) and scans your PRs for potential bugs or issues.

Here's how it works:

• Pull request checks: Every time you open or update a PR, BugBot reviews the changed code and leaves comments on any possible mistakes.
• Quick fix flow: If BugBot finds something, it adds a "Fix in Cursor" link, click it to open your editor with the problem context pre-loaded.
• Flexible setup: You can set it to run all the time or only when called, and decide whether to show outcomes when no issues are found.
• Team settings: Repo admins can enable or disable it per repo, set cost limits, and manage permissions across teams.

BugBot is part of Cursor's version 1.0 release and comes with a 7-day free trial. After that, it requires a subscription to Cursor's Max mode.

Comparison: Entelligence AI vs Cursor's BugBot

Choosing a code review tool that works inside your IDE can be tricky, especially when multiple tools feel similar at first. To make it easier, we tested both Entelligence AI and Cursor's BugBot in a simple React app called Should I Do It?

It uses an open API and basic async logic, so we could check how each tool handles real-world code: fetch requests, error handling, component structure, and async bugs.

Instead of going broad, we focused on things that matter during actual development, not just what's on a landing page.

Code Review

One major difference between Entelligence AI and Cursor's BugBot is when they let you review your code.

Entelligence AI

With Entelligence, you don't have to wait to raise a pull request. It reviews your changes directly in the editor, so you can get suggestions as you go, before your code even leaves your branch.

We tested this on our intentionally badly written fetchAnswer.js function.

const fetchAnswer = async () => {
  try {
    const url = 'https://yesno.wtf/api';

    const config = {
      method: 'GET',
      headers: {
        'Content-Type': 'application/json',
        'Accept': '*/*',
        'Cache-Control': 'no-cache',
        'Pragma': 'no-cache',
      },
      redirect: 'follow',
      referrerPolicy: 'no-referrer'
    };

    let result, data;

    try {
      result = await fetch(url, config);
    } catch (networkErr) {
      console.log('Maybe the internet is down? Or maybe not.');
      console.error(networkErr.message || 'Some error happened');
      result = null;
    }

    if (!result) {
      console.warn('Fetch result is empty or undefined or null or broken');
      return { answer: 'maybe', image: 'https://placekitten.com/200/200' }; // placeholder nonsense
    }

    if (result.status === 200 || result.status === 201 || result.status === 204) {
      try {
        data = await result.json();
      } catch (jsonError) {
        console.log('JSON might be corrupted or evil');
        console.error(jsonError);
        return { answer: 'error-parsing-json', image: '' };
      }

      if (!data || typeof data !== 'object') {
        console.log('Data is not what we expected, but let's just go with it');
        return { answer: '¯\_(ツ)_/¯', image: '' };
      }

      if (data && Object.keys(data).length > 0 && data.answer && data.image) {
        return {
          answer: `${data.answer}`,
          image: `${data.image}`
        };
      } else {
        console.log('Something was missing, but let's not worry too much');
        return {
          answer: 'almost',
          image: 'https://http.cat/404'
        };
      }
    } else {
      console.warn('Status was weird: ', result.status);
      return {
        answer: 'uncertain',
        image: 'https://http.cat/500'
      };
    }

  } catch (err) {
    console.error('Global meltdown', err);
    return {
      answer: 'panic',
      image: 'https://http.cat/418'
    };
  }
};

export default fetchAnswer;

Here's what Entelligence pointed out:

• Unnecessary console logs clutter the code
• Use of let for url when const would be more appropriate
• Overuse of template literals like ${data.answer} when data.answer would work fine
• Incorrect handling of HTTP status codes, like treating 204 (No Content) the same as 200

Not only did it highlight these problems, it gave inline suggestions to fix them. You could accept changes right there, no extra steps, no separate review window.

Even after raising a PR, Entelligence doesn't stop helping.

• It summarizes the pull request.
• Provides a walkthrough of what the PR contains, including a helpful sequence diagram.
• You can give feedback using 👍 / 👎 emojis to help it learn your review preferences.
• If the PR looks good, it auto-comments with LGTM 👍
• It shows which review settings are enabled and lets you customize them directly in the Entelligence AI dashboard

You can even track analytics inside your dashboard, like how many PRs are open, merged, or in review, and the overall quality of your team's contributions.

BugBot

With Cursor's BugBot, you need to raise a pull request first. BugBot then auto-reviews the code (if enabled), or you manually run it by commenting bugbot run.

On running it against the same file, here's what BugBot flagged:

• Redundant data validation
• Casual and inconsistent console messages
• Use of unnecessary string interpolation
• Confusing HTTP status logic

BugBot gave detailed, structured feedback, and included a "Fix in Cursor" button that opened Cursor with the changes ready to apply. It worked well, but the extra step of needing a PR or comment made it slightly slower in terms of feedback loop.

In short:

• Entelligence AI gives you feedback while coding and continues to assist after a pull request is raised, with summaries, diagrams, and customizable reviews. It's built to stay with you throughout the entire workflow.
• BugBot gives good suggestions too, but only kicks in after you raise a pull request or trigger it manually.

Bug Detection

After code review, the next big test is bug detection, especially how quickly and deeply these tools can catch small issues that often slip through until runtime or production.

To test this, we created a simple but buggy React component: AnswerBox.jsx.

import React from 'react';

const AnswerBox = ({ answer }) => {
  return (
    <div style={{ textAlign: 'center', padding: 20, fontFamily: 'sans' }}>
      <h2>Your answer is:</h2>
      <p>{answer.answer || 'No answer available yet'}</p>
      {answer.image ? (
        <img
          src={answer.image}
          alt="answer"
          width="300px"
          height="auto"
          style={{
            marginTop: 20,
            border: '3px dashed purple',
            borderRadius: 4,
            boxShadow: '0px 0px 20px rgba(0,0,0,0.2)',
            objectFit: 'coverd'
          }}
        />
      ) : (
        <p style={{ color: '#888' }}>No image provided</p>
      )}
    </div>
  );
};

export default AnswerBox;

It looks harmless, but it's filled with small logic flaws, accessibility issues, and style bugs that are easy to miss.

Entelligence AI's Detection

Entelligence AI gave real-time suggestions as we wrote the file, without waiting for a pull request. It immediately pointed out:

• Incorrect CSS Property - Spotted objectFit: 'coverd' and suggested 'cover' a common but tricky typo.
• Invalid Font Family - Caught fontFamily: 'sans' and correctly recommended 'sans-serif'.
• Accessibility Concerns - Flagged the alt="answer" as too vague and suggested more meaningful alt text for screen readers.
• Performance Suggestions - Highlighted that the image is not lazy-loaded, which could impact performance on slower connections.
• Inline Styling Feedback - Recommended switching from inline styles to reusable CSS modules or styled-components for better maintainability.
• Error Handling - Mentioned the absence of fallback behavior when the image fails to load.
• Responsive Design Gaps - Warned that fixed width: "300px" might break responsiveness across screen sizes.
• Prop Safety - Noted the component didn't validate props using PropTypes, which can cause runtime issues in large apps.

These suggestions came up before raising any PR, saving review time and making it easier to fix issues as they arise.

Cursor (BugBot) Review

To get suggestions from BugBot, we had to first raise a PR. Once active, BugBot analyzed the diff and left a helpful review with several suggestions:

• Caught the same objectFit: 'coverd' typo.
• Noticed the invalid font and corrected it to 'sans-serif'.
• Flagged missing PropTypes and even shared how to define them.
• Recommended avoiding inline styles and suggested externalizing CSS.
• Warned about potential crashes from missing answer props and suggested fallback handling.
• Offered a neat refactored version of the component using better structure, error handling, and accessibility.

Both tools flagged key issues, but what really sets them apart is when and how they do it.

If you're someone who likes catching mistakes before they go anywhere, Entelligence AI fits more naturally into your day-to-day. Cursor, meanwhile, is a solid safety net for teams focused on structured code review checkpoints.

Code Generation & Fixes

As part of the PR process, I tried something different. Instead of making changes, I added this placeholder in a file to see if they understand what I need to add in this file.

Add a dropdown with 'yes', 'no', and 'maybe' options. The answer and image should only display if the user selection matches the fetched API response.

This was the perfect opportunity to observe how both Entelligence AI and Cursor behave when reviewing and contributing to live code changes.

Cursor

Cursor didn't just edit. It wrote the whole feature from scratch, fetching the API response, managing user selection, handling loading and error states, and displaying the answer/image only when they matched.

{apiResponse && userSelection && userSelection === apiResponse.answer && (
  <div>
    <h3>API Answer: {apiResponse.answer}</h3>
    <img src={apiResponse.image} alt={apiResponse.answer} />
  </div>
)}

It even wrapped everything with clean error boundaries and a proper loading experience. This wasn't a tweak, it was a production-ready implementation that respected UI flow, UX states, and code style.

Cursor handled:

• API integration
• Dropdown state logic
• Matching condition
• Loading + error boundaries
• Clean inline styling and accessibility

Entelligence AI

Entelligence AI took a more incremental approach. Instead of building the feature end-to-end, it scanned the existing component and inserted just the logic needed to satisfy the new condition, in diff-style.

+ const [selectedOption, setSelectedOption] = React.useState("yes");

+ {answer.answer.toLowerCase() === selectedOption && (
    <>
      <h2>{answer.answer.toUpperCase()}</h2>
      <img src={answer.image} alt={answer.answer} />
    </>
  )}

It worked quickly, but didn't have the full user flow awareness like Cursor did. There was no API fetching, no user feedback for loading or errors, and no structured fallback.

Entelligence AI handled:

• Local dropdown logic
• Conditional rendering
• Minimal context awareness
• Diff-first suggestion mode

Documentation Generation

When it comes to keeping documentation up-to-date, Entelligence AI takes the lead and does it quietly in the background.

Automatic & Inline Updates

As soon as a PR merges or changes happen in the codebase, Entelligence auto-updates relevant documentation. Whether it's a function, a component, or even a newly added file, the tool reads the code, understands the context, and updates the associated docs in real-time.

No need to switch tabs or open a separate tool. You can also trigger updates manually from the IDE using a simple command:

/updateDocs

The best part? It's not locked. You can easily modify the generated docs to suit your tone, add notes, or expand on context, all without writing from scratch.

Cursor's Limitation

Cursor currently doesn't offer automatic or assisted documentation generation. While it can help you write a comment if you explicitly ask it to, it does not track changes or maintain up-to-date documentation as your project evolves. You're still on your own for writing and managing docs, which can lead to outdated, inconsistent, or missing documentation over time.

Which One Should You Choose?

If you prefer a tight feedback loop, catch bugs before PRs, and want auto-generated documentation, Entelligence AI is a clear win.

If your team has a PR-first workflow and you want full code rewrites inside your editor, Cursor (and BugBot) are still a powerful choice.

Conclusion

Both Entelligence AI and Cursor bring serious AI firepower into your coding workflow, but in very different ways.

• Entelligence AI acts like a quiet, senior engineer on your shoulder, helping you review, fix, and document your code as you write it. It's perfect for developers who want to stay in flow, catch bugs early, and keep their project healthy with minimal overhead.
• Cursor (BugBot) is like a structured reviewer that steps in after you're done. It's reactive, helpful, and writes great code, but you'll need to raise PRs or trigger it manually to benefit from its insights.

In a world where code is moving fast, having a tool that grows with your thought process, not just your diffs, makes a big difference.

If you're building daily, Entelligence feels like a partner. The cursor feels like a reviewer.

Pick what fits your team's rhythm.