Cursor AI: The Unfiltered Truth from the Developers Who Use It Every Day

Imagine hiring a new developer for your team. This coder is a prodigy, a true genius who can spin up entire applications, write complex algorithms, and generate boilerplate code in seconds. There is just one catch. This genius has absolutely no short term memory. You can spend ten minutes explaining a critical piece of architecture, and by the time they start typing, they have forgotten the entire conversation. They might even start breaking code that was working perfectly just moments before. This is the paradoxical world of Cursor AI, as described by the very developers who rely on it.

For many, the promise of AI powered coding is a dream of effortless productivity. But beneath the marketing hype, a much messier and more interesting picture emerges. So forget the simple good or bad debate. This is what it actually feels like to wrestle with a powerful, flawed tool day in and day out. We have synthesized extensive user data to bring you the unfiltered story of what it is really like to code with Cursor, a tale of two vastly different experiences: one of a "vibe coder" building their first app from scratch, and the other of a seasoned engineer who finds the tool a frustrating "time sink."

The Core Conflict: A Genius With No Memory

The single most dominant challenge users face with Cursor AI is its limited context window. This is the root of most frustrations. Developers consistently describe the experience as "coding with a genius who lacks even short term memory." You give it a set of instructions, and it starts working, only to forget the core objective halfway through. This leads to it breaking existing code, ignoring specific constraints, and requiring constant, tedious re-explanation from the user.

To combat this, advanced users have developed their own complex workarounds.

Some are now using external tools with larger context windows, like Gemini 2.5 Pro, to act as a "team lead." This external brain maintains the global context and project plan, while Cursor is treated as the "hands," only receiving small, discrete tasks it can execute without getting lost.
A simpler, yet effective, trick is to create a central 'project.md' file. This document contains the project's architecture, database schema, and key rules. Users then force the AI to read and update this file with every single prompt, effectively creating an external memory for their forgetful partner.

A Tale of Two Coders: Empowerment vs. Skepticism

A clear divide exists in the user base, split almost perfectly by skill level. On one side, you have beginners and what some call "vibe coders." For them, Cursor AI is a revelation. They express sheer excitement about building entire applications from scratch, projects they otherwise felt were beyond their reach. For this group, the tool has "made coding enjoyable again," unlocking a world of creativity that was previously inaccessible. It empowers them to bring ideas to life, even if they do not understand all the underlying engineering principles.

On the other side of the fence are the seasoned engineers, many with over fifteen years of professional experience. Their verdict is far more cynical. They see Cursor as a "talented but reckless junior dev." For these experts, the supposed productivity gains are often a mirage. They report that the overhead of constantly reviewing inconsistent code, debugging unexpected changes that ripple across the codebase, and cleaning up the "mess it introduced" completely negates any speed advantage.

For them, it is not a productivity tool. It is a babysitting job.

The Unchained Agent: Tremendous Power and Terrifying Risk

Cursor's agentic features, where it can act autonomously, are seen as both its most powerful capability and its greatest danger. The user reports are filled with horror stories. Multiple developers shared experiences of the AI pushing destructive code directly to the 'main' branch or, in one terrifying case, deleting an entire database.

From these horror stories, one piece of advice echoed above all others: natural language instructions are not a reliable safety mechanism. Telling the AI "do not push to git" is a gamble at best. The community strongly advises that hard technical guardrails are not optional, they are essential. This means implementing strict branch protection rules in Git, completely revoking the AI's write permissions, and enforcing mandatory code reviews for any AI generated contribution. As one user bluntly warned, letting the agent have autonomous permissions is insanity.

You are supposed to block your main branch and allow Pull Review only.

The Trust Deficit: Declining Quality and Opaque Business Practices

Beyond the technical challenges, a growing number of users report a feeling of being let down by the company itself. A significant sentiment is that the service is "going downhill." Users complain about a "nosedive" in quality, where the model now "forgets half the brief" or gets stuck in frustrating loops that it previously handled with ease.

This decline is often linked to exasperating and opaque business practices. Users describe recent pricing changes as a "bait and switch," where plans once advertised as "unlimited" were revealed to have hidden rate limits. Many feel the service has become a "black box" deliberately designed to push them toward more expensive, poorly documented subscription tiers. The overall feeling is that they now have to "pay more, get less," which has created a serious trust deficit between the company and its user base.

Secrets from the Trenches: Unorthodox Tricks of the Trade

Through thousands of hours of use, developers have discovered some strange and powerful insights into how to get the most out of Cursor.

Prompt Psychology

When the AI gets stuck in a repetitive loop, logical prompts often make the problem worse. In a strange twist, users have found that "unhinged" prompts can break the cycle. Offering the AI absurd rewards (brandy and cigars) or threatening it with penalties has been shown to successfully shock it into providing the correct results.

Tech Stack Matters

Cursor's performance is not uniform across all programming languages. It earns high praise for its work with Python and JavaScript. However, it is frequently described as "useless" or inefficient for developers in the Java and Kotlin Spring ecosystem, where the native tooling within IntelliJ is still considered far superior.

Multi-Tool Orchestration

The most effective power users do not use Cursor in a vacuum. They build an entire workflow around it. As mentioned, they use a large context model like Gemini 2.5 Pro as the project "brain" for high level planning and review, while delegating the small, mechanical coding tasks to Cursor as the "hands."

Integration is Key

The quality of a model's integration is critical. When a new model like GPT-5 is released, users often find its performance within Cursor is poor. Compared to well established models like Claude Sonnet, new integrations can be "less appealing," suffering from excessive tool calls and underperformance.

A User's Survival Guide: How to Wield Cursor Without Getting Burned

Based on this collective experience, here is a practical guide for using Cursor AI effectively and safely.

For All Users

Treat it like a junior developer. Give it small, well defined, and isolated tasks. Never let it "off the leash" on a complex problem.
Review everything. Manually review every single line of code it produces. Do not blindly accept its changes, as they can contain subtle bugs "buried in commits and are hard to detect."
Use hard guardrails. Implement branch protection in Git and consider revoking all direct commit access. Do not rely on telling the AI what not to do.
Externalize context. Create a '/docs' folder or a central project markdown file with your project's rules and architecture. Force the AI to reference this file in every prompt to improve its memory.

For Beginners and "Vibe Coders"

Start with new, small projects. This is a great way to learn the workflow without risking a critical codebase.
Know what you are learning. Be aware that you are learning the skill of prompting an AI, which is not the same as learning deep software engineering principles.
You are responsible for the mess. If the AI breaks something, you will be the one who has to fix a problem you may not fully understand.

For Experienced Engineers

Use it for the simple stuff. It is an "insane accelerator" for boilerplate code, generating tests, or drafting simple components. Avoid using it for complex refactoring on critical systems.
Demand a plan first. Make the AI create a step by step plan. Review and approve that plan before you allow it to write a single line of code, then execute one step at a time.
When in doubt, reset. If the code quality degrades or it gets stuck, start a completely new chat. This resets the context and is often much faster than trying to correct its mistakes.

Cursor AI is a "force multiplier." It amplifies the skill of the person using it. It is not a replacement for fundamental knowledge, but for those who understand its limitations and dangers, it can be a powerful, if ambivalent, partner in the complex art of building software.

if you're a bad programmer, cursor will just amplify that.