I Used Grok 4.5 for 2 Weeks: 9 Things Every Developer Should Know Before Switching

I used Grok 4.5 every day for two weeks while building a real C# and React web application in Cursor. Here’s my honest review, including performance, speed, coding quality, SQL limitations, pricing, practical tips for better prompts, and whether I’ll continue using it after the discount ends.

Grok 4.5 recently landed as a model option in Cursor, and like every new frontier model, it arrived with a wave of benchmark charts — SWE-bench scores, token throughput numbers, leaderboard positions. Useful, but not the thing that tells you whether a model will actually hold up in your codebase.

What’s rarer is a review written from inside a real project: the kind of work where you’re chasing a null reference exception at 4pm, refactoring a service class that’s grown too many responsibilities, or asking a model to review a pull request before it goes out. So I used Grok 4.5 as my primary assistant in Cursor for 13 days straight, on actual client and product work, and tracked what held up and what didn’t.

This article is that log, condensed into nine things worth knowing before you make Grok 4.5 your default model.

🧪 My Testing Setup

When I Started Using Grok 4.5

I ran this test from July 9 through July 21 — thirteen consecutive working days. No sandbox repos, no “write me a to-do app” prompts. Grok 4.5 was set as my default model in Cursor for whatever showed up in my actual queue that day, from a one-line bug fix to a multi-file feature.

Technologies I Worked With

The stack stayed consistent across the two weeks, which made it easier to notice patterns instead of one-off flukes:

• C# — services, domain logic, unit tests
• ASP.NET Core — controllers, middleware, dependency injection, API design
• React — function components, hooks, form-heavy UI
• MS SQL Server — queries, joins, stored procedures
• Bug fixing — reproducing, isolating, and patching real defects
• Refactoring — cleaning up existing, working code without breaking it
• Code reviews — using Grok 4.5 as a second set of eyes on pull requests

Benchmarks test isolated problems with a clean answer key. Daily development is messier — half-finished context, legacy patterns, and code that has to fit into a system that already exists. That gap is exactly where a lot of models quietly fall apart, and it’s what this review is trying to capture.

✅ What Grok 4.5 Did Well

Extremely Fast Responses

This is the first thing you notice and it doesn’t wear off. Grok 4.5 returned multi-file edits and full function rewrites noticeably faster than the reasoning-heavy models I’d been using before it. For small, iterative changes — rename this, adjust that condition, add a null check — the speed alone changed how I worked. I stopped batching questions to “save a round trip” and just asked things as they came up.

// rough feel, not a lab benchmark
small edit (1 file) ......... near-instant
medium refactor (3–5 files) . a few seconds
large multi-file feature ... noticeably faster than heavier reasoning models, still worth watching output closely

// rough feel, not a lab benchmark
small edit (1 file) ......... near-instant
medium refactor (3–5 files) . a few seconds
large multi-file feature ... noticeably faster than heavier reasoning models, still worth watching output closely

Strong C# Backend Development

Grok 4.5 was reliably good at C# and ASP.NET Core. Dependency injection was wired correctly by default, async/await was used consistently instead of mixed with blocking calls, and generated services generally matched the patterns already in the surrounding codebase when given enough context.

public async Task<OrderResult> PlaceOrderAsync(OrderRequest request, CancellationToken ct)
{
    var customer = await _customers.GetByIdAsync(request.CustomerId, ct);
    if (customer is null)
        return OrderResult.Failure("Customer not found.");

    var order = Order.Create(customer, request.Items);
    await _orders.AddAsync(order, ct);
    await _unitOfWork.SaveChangesAsync(ct);

    return OrderResult.Success(order.Id);
}

public async Task<OrderResult> PlaceOrderAsync(OrderRequest request, CancellationToken ct)
{
    var customer = await _customers.GetByIdAsync(request.CustomerId, ct);
    if (customer is null)
        return OrderResult.Failure("Customer not found.");

    var order = Order.Create(customer, request.Items);
    await _orders.AddAsync(order, ct);
    await _unitOfWork.SaveChangesAsync(ct);

    return OrderResult.Success(order.Id);
}

This is close to what came back on the first try — no manual thread juggling, no swallowed exceptions, cancellation token passed through correctly.

Good React UI Generation

For common UI patterns — forms with validation, tables with sorting, state-driven components — React output was clean and used current hook patterns rather than outdated class-component habits. It respected existing component structure when I pointed it at a folder instead of asking it to generate from nothing.

Helpful for Refactoring Existing Code

This was one of the more pleasant surprises. Refactoring requires understanding intent, not just syntax, and Grok 4.5 was consistently good at preserving behavior while cleaning up structure — splitting an overloaded method, extracting an interface, simplifying nested conditionals — without silently changing what the code actually did.

Asked it to extract a 140-line controller action into a service method with the same external behavior. It correctly identified the side effects that had to move together (logging, a cache invalidation call) instead of leaving them behind — a mistake I’ve seen from other models on the same kind of task.

Works Well Across Different Types of Programming Tasks

The consistency across task types stood out more than any single strength. Bug fixing, refactoring, new feature work, and reviewing someone else’s pull request all felt like the same competent baseline, rather than the model being great at one thing and mediocre at everything else.

🐛 Where Grok 4.5 Still Needs Improvement

SQL Queries and Stored Procedures

This was the clearest weak spot. Simple SELECT statements and basic joins were fine, but anything involving multiple joins, correlated subqueries, or MS SQL Server–specific stored procedure logic needed correction more often than backend or frontend code did.

Asked for a stored procedure to return the latest status per order with a tiebreaker on timestamp. The first version used a plain GROUP BY without a tiebreak, which silently returned an arbitrary row on ties instead of the intended one — the kind of bug that passes casual testing and shows up weeks later.

-- what it produced first: no deterministic tiebreak
SELECT OrderId, MAX(StatusDate) AS LatestDate
FROM OrderStatusHistory
GROUP BY OrderId;

-- what it needed: ROW_NUMBER with an explicit tiebreak
SELECT OrderId, Status, StatusDate
FROM (
    SELECT *,
      ROW_NUMBER() OVER (
        PARTITION BY OrderId
        ORDER BY StatusDate DESC, StatusId DESC
      ) AS rn
    FROM OrderStatusHistory
) ranked
WHERE rn = 1;

-- what it produced first: no deterministic tiebreak
SELECT OrderId, MAX(StatusDate) AS LatestDate
FROM OrderStatusHistory
GROUP BY OrderId;

-- what it needed: ROW_NUMBER with an explicit tiebreak
SELECT OrderId, Status, StatusDate
FROM (
    SELECT *,
      ROW_NUMBER() OVER (
        PARTITION BY OrderId
        ORDER BY StatusDate DESC, StatusId DESC
      ) AS rn
    FROM OrderStatusHistory
) ranked
WHERE rn = 1;

None of this makes SQL unusable — it’s a reasonable starting point most of the time — but it’s the one area where I stopped trusting first-pass output and started expecting a second look every time.

Small Bugs Hidden Inside Good Code

The more concerning pattern wasn’t obviously broken code — that’s easy to catch. It was code that looked completely correct, followed good structure and naming, and still had a small logic error buried in it: an off-by-one in a loop boundary, a condition using || where && was intended, a date comparison that didn’t account for time zones.

A discount calculation looked right at a glance — clean method, clear variable names, sensible flow. The bug was a single comparison operator: >= instead of > on a threshold check, which meant customers exactly at the minimum spend got double-counted for a bonus discount. It took a targeted test case to catch, not a read-through.

Why Every AI Response Still Needs Review

Put those two points together and the takeaway is simple: fast, confident, well-structured output is not the same as correct output. Grok 4.5’s code reads well, which is exactly why it needs deliberate review rather than a skim — readable code earns trust faster than it’s earned it.

🛠️ 4 Tips for Getting Better Results with Grok 4.5

1. Break Large Tasks into Smaller Steps

   Large, vague asks (“add a full checkout flow”) produced weaker results than the same work split into stages: data model, then service layer, then endpoint, then UI. Smaller steps meant smaller, easier-to-verify diffs.

2. Provide More Project Context

   Pointing Grok 4.5 at the actual files, existing patterns, and naming conventions in the project produced noticeably better output than asking it to write something from a blank prompt. Context did more for accuracy here than clever prompt wording.

3. Ask Grok to Review Its Own Code

   A simple follow-up — “review this for edge cases and bugs before I accept it” — caught a meaningful number of issues on its own, including a couple of the hidden logic bugs mentioned above. It’s not a substitute for a human pass, but it’s a cheap first filter.

4. Never Skip Manual Code Review

   This is the one that matters most. No matter how clean the output looked or how much I trusted the model on a given task type, every change went through the same review it would if a teammate had written it.

💸 Is Grok 4.5 Worth the Price?

Using It During the Discount

I ran this entire test during a promotional pricing window, which matters for any honest verdict — the cost-per-task math looks very different at full price than it did during testing. Judged purely on capability-per-dollar during the discount, Grok 4.5 was an easy pick for day-to-day work.

My Planned AI Workflow After the Discount Ends

Once the promotional pricing ends, the plan is to keep Grok 4.5 as the default for fast, routine work — bug fixes, refactors, boilerplate, first-pass code review — and reserve slower, more expensive reasoning models for the tasks where getting it right matters more than getting it fast: tricky SQL, security-sensitive logic, and architecture decisions.

🔁 Will I Continue Using Grok 4.5?

Yes, but selectively rather than as a single default for everything. Two weeks of daily use was enough to see where it earns trust and where it needs a backup plan.

👀 Looking Forward to Kimi K3

Kimi K3 is next on the list to test. Early signals around its reasoning and coding performance are promising enough to be worth a proper trial under the same conditions — real production work, not a benchmark run. If it holds up, a head-to-head comparison against Grok 4.5, covering the same C#, ASP.NET Core, React, and SQL Server workload, is already planned as a follow-up article and video.

🏁 Final Verdict

Biggest strengths: speed, consistently solid C# and ASP.NET Core output, dependable React generation, and genuine usefulness for refactoring — all held up across two weeks of real, varied work.

Biggest weaknesses: complex SQL and stored procedures need extra scrutiny, and clean-looking code can still hide small, easy-to-miss logic bugs.

Who should use Grok 4.5: developers who want a fast daily driver for bug fixes, refactors, routine features, and first-pass code review — especially at discount pricing.

Overall recommendation: worth switching to as a default for everyday work, paired with disciplined manual review and a stronger reasoning model kept on hand for the hard problems.

Prefer watching instead of reading?

In this video, I walk through my complete two-week experience using Grok 4.5 for real software development inside Cursor. You’ll see where it performed exceptionally well, where it struggled, how it compares to the models I previously used, and the practical workflow I’ll continue using after the current pricing changes. If you’re considering switching to Grok 4.5, this video should help you make a more informed decision.

❓ Frequently Asked Questions

What is Grok 4.5? Grok 4.5 is xAI’s coding-capable large language model, available inside Cursor as a model option for chat, inline edits, and agent-style multi-file tasks.

Is Grok 4.5 good for coding? Yes, for most day-to-day work. Across two weeks of real C#, ASP.NET Core, and React development, Grok 4.5 was fast and produced solid backend and UI code. SQL and stored procedures were the weakest area.

Is Grok 4.5 better than Claude for programming? It depends on the task. Grok 4.5 responded noticeably faster in everyday testing, which matters for quick edits and iteration speed. For deep reasoning on gnarly SQL or subtle logic bugs, more caution and review were still needed than with slower, more deliberate reasoning models.

Does Grok 4.5 work well with C# and React? Yes. C# and ASP.NET Core backend code came out clean and idiomatic most of the time, and React component generation was reliable for typical UI patterns like forms, tables, and state-driven components.

Can Grok 4.5 write SQL queries? It can write basic to moderate SQL, but it struggled with more complex queries and stored procedures against MS SQL Server, sometimes producing logic that looked correct but failed on edge cases.

How much does Grok 4.5 cost? Pricing depends on the platform and any active promotional period. During a discount window, Grok 4.5 can be significantly cheaper per task than premium reasoning models, which changes how it fits into a daily workflow.

Should developers switch to Grok 4.5? For fast, everyday coding tasks — refactors, bug fixes, boilerplate, code reviews — it’s a strong pick. For complex SQL work or high-stakes logic, pair it with careful manual review or a stronger reasoning model.

13 days · real production code · C# · ASP.NET Core · React · MS SQL Server · Cursor