Summary

SLAtech LTD is an Israeli software development company, operating since 2004. We help teams and product owners whose code was written with Cursor: we check the architecture, security and tests, find the places nobody has read end to end, take the project to production and keep developing it. The code stays in your repository. People define the architecture and make the decisions; AI only proposes.

Cursor projects

Your Cursor project is stuck? We will check it, fix it and take it to production

Cursor speeds up development: the agent in the editor writes and changes code across many files at once, and cloud agents carry out tasks on their own and open pull requests. The trouble starts when there is more code than the team can read. Changes are accepted wholesale, the architecture blurs, and the tests are written by the same agent as the code. We audit Cursor projects, continue their development, or rewrite what is not worth fixing. What we fixed, we stay accountable for.

Tell us about the project Go straight to the audit

What Cursor does well

Works where developers already work. An editor based on VS Code, familiar extensions and Git.

Sees the whole project. The agent reads the files it needs and changes code in several places at once.

Project rules. Rules files hold the standards and constraints the agent follows.

Change review. Bugbot reviews pull requests and leaves comments.

That is why code written with Cursor usually does not need to be thrown away. More often it needs to be checked in a way nobody has checked it so far.

Where Cursor projects usually get stuck

Code nobody has read end to end

The agent changes dozens of files at a time, and the changes are accepted wholesale because reading them takes long. A few months later nobody on the team can explain how the system works.

Blurred architecture

Each task gets solved wherever is easiest for the agent. The same logic ends up in three places, and a fix in one never reaches the others.

Tests by the same author

If the tests are written by the same agent as the code, they check what it did, not what was intended.

AI reviewing AI

Automated pull request review is useful, but it can miss the same things the agent missed. Responsibility for a change still lies with a person.

Outdated rules

Rules files are written once, while the project changes. The agent keeps following old agreements.

Unneeded and made-up dependencies

The agent adds libraries for each task, sometimes outdated ones or ones with names that look like real packages.

What we check in a Cursor project

1

Architecture: where each piece of logic lives and where it is repeated.

2

Security: access rights, input validation, handling of secrets.

3

Tests: what they actually check and which main scenarios are not covered.

4

Dependencies: unneeded, outdated and vulnerable libraries.

5

Keys and secrets: in the code, in the change history, in configuration files.

6

Agent rules: whether they match how the project is built today.

7

Database work: queries, indexes, migrations.

8

Errors and logs: whether the team will see a failure before users do.

9

Deployment: branches, checks before merging, a separate environment for checking.

The result: a written report in plain language, a list of issues ranked by risk, and a plan of fixes.

Three ways forward

Audit

A check against the list above, a written report and a plan of fixes. A fit if you carry on yourself or with your own team.

More about the audit

Continued development

We join your team or run the product ourselves: we close the critical issues and keep developing it. What we fixed and wrote, we are accountable for.

Discuss continuing

Rewriting a part

Usually not everything needs rewriting, only the one area where the logic is most scattered: access rights, payments, data handling.

Discuss a rewrite

How we choose between these paths is described in detail on the page about helping vibe-coded projects.

How we use AI ourselves

In Cursor, an AI agent writes and changes code right in the editor. We work differently. On client projects, people define the architecture and make the decisions. AI proposes a solution to a task a person has set, and we bring it into the project ourselves, after review. The AI agent gets no access to the code, databases, keys or passwords, and there is not a single line in the code that a person does not know about.

Frequently asked questions

An outside view sees what the team has grown used to. And the audit answers a question that is hard to answer from inside: how reliable the system is if it was written faster than it was read.

No. We are not against AI tools. What matters is that tests, human review of changes and a clear system design sit alongside them. The audit shows where these are missing.

Automated review catches a lot within a single change, but it does not see the system as a whole: repeated logic, outdated decisions, gaps in access rights. That is a job for a person who understands the product.

Read access to the repository. We sign an NDA if needed. Access to the database and production is discussed separately, and only when it is really needed.

It depends on two things: the size of the project and how far it has drifted, that is, how much in it needs changing and fixing. After the initial assessment we name the scope of work and the price, before any work starts.

Other AI tools

We work the same way with projects built on other tools. The general page: help for vibe-coded projects.

Tell us what you built with Cursor

Describe the product and what is holding it back. We will take a look and suggest where to start: an audit, continued development or rewriting a part.

Tell us about the project Go straight to the audit