Meet Entelligence AI: An AI Code Review Agent That Can Catch and Fix Bugs in Your IDE

The endless cycle of writing code, submitting a pull request, and waiting for a human review might be on its way out. As you may know, coding isn't a solo activity, but review cycles often feel slow and stalled with pull requests stacked up, context is lost, and minor mistakes turn into late-night fixes. Fortunately, there is a new category of AI agents that we are seeing more of that live directly inside your code editor, offering feedback in real-time. One such tool is Entelligence AI, a code review agent.

Entelligence AI Code Review Agent

Entelligence AI is a code review agent that can provide review feedback straight into the editor before the code ever leaves a developer's laptop. Instead of a formal, often delayed, review process, this approach integrates analysis directly into the coding workflow, catching potential problems before they are even saved.

Entelligence AI promises faster iterations, fewer bugs in production, and happier engineers, all without a single tab switch by fusing large language model (LLM) analysis with full-project awareness inside VS Code, Cursor, and Windsurf.

The idea is to provide developers with immediate, contextual feedback. Rather than waiting for a teammate to spot a potential issue hours or days later, the agent flags it as it's being typed. This immediacy promises to reduce the back-and-forth that often slows down development teams. By analyzing code as it's written, these tools can identify not just simple syntax errors but also more complex problems that might otherwise go unnoticed until much later.

Why developers should care

Time is money, and traditional review blockages drain them both. Entelligence AI compresses code review delays into real-time feedback, helping teams deploy sooner and sidestep the hidden costs of rework.

Here are some of the main functions of the Entelligence AI agent:

• Real-Time, In-Editor Reviews: The agent works within popular code editors like VS Code, providing feedback on your work as you go. It can analyze uncommitted code, meaning you get suggestions without having to formally save or submit your changes.

• Whole-Project Awareness: Unlike tools that only look at the file you have open, this agent analyzes your entire codebase. This allows it to understand how your current changes might affect other parts of the project, helping to prevent unintended consequences.

• Context-Sensitive Suggestions: The feedback is designed to be more than generic advice. The agent learns your team's coding conventions and patterns to offer suggestions that are relevant to your project's specific standards. It can spot architectural issues, missing tests, and performance slowdowns.

• Interactive Fixes: When the agent identifies a problem, it can also suggest a solution. You can apply the fix with one click or choose to ignore the suggestion, keeping you in the flow of your work.

This approach to code review with AI agents could have a strong impact on how software is built. For individual developers, it offers a form of continuous quality control, acting as a second pair of eyes. For teams, it has the potential to speed up development processes by reducing the time spent on manual reviews.

There are plenty of code review AI agents like Tabnine's Code Review Agent, CodeRabbit, GitHub Copilot, and Bito AI Code Review Agent that can catch issues early and provide relevant feedback, just like Entelligence AI. Choose the right AI agent that suits your workflow to possibly free up your time to focus on more substantial coding problems.