Google Antigravity Review: Why I Think More Developers Should Try It

I try a lot of tools.

Some are genuinely useful. Some look impressive for five minutes, then start feeling repetitive. Some promise speed, but in reality they just add another layer between me and the work. You still end up jumping between your editor, the terminal, the browser, docs, prompts, screenshots, and endless little checks that break your focus.

That is why Google Antigravity stood out to me.

When I first looked at it, I expected another AI coding tool with a polished interface and the usual promises about moving faster. But the more I explored it, the more it felt like something a bit more thoughtful. It did not seem designed only to help me write code quicker. It seemed designed to help me move through actual development work in a smoother and more enjoyable way.

That difference matters a lot.

Most people talk about AI coding tools as if the only thing that matters is generation. Can it write a function. Can it scaffold a component. Can it explain an error. Can it autocomplete faster than the next tool.

Those things matter, but they are not the whole job.

Real development work is messier than that. It is planning a change, deciding where to implement it, checking the browser, running commands, reviewing what happened, making adjustments, then checking everything again. A tool becomes much more interesting when it understands that coding is not just typing. It is a workflow.

That is the main reason I enjoyed learning about Google Antigravity. It feels closer to how people actually build.

And honestly, it also feels more fun.

This article is my detailed take on Google Antigravity, what I like about it, why I think more developers should try it, the features that stood out to me, practical tips if you want to use it well, hidden gems people may overlook, and a few honest notes about where I think the real value is.

What Google Antigravity actually is

The simplest way I would explain Google Antigravity is this.

It is a Google built agent first development platform that tries to move beyond the old idea of AI as a small helper sitting inside your editor.

Instead of only assisting with lines of code, it is built around the idea that AI agents can help plan, execute, verify, and refine broader engineering tasks. That includes work across the editor, the terminal, and the browser. Google also presents it with two distinct parts: an Editor View for direct hands on work, and a Manager Surface for creating, observing, and coordinating agents.

That structure immediately makes it feel different.

A lot of tools want to be a smarter autocomplete layer. Antigravity feels more like it wants to be a proper workspace for modern development where agents are part of the operating model, not just a side feature.

I think that is why the product name has stuck in people’s minds. It feels like Google is trying to lift some of the weight that usually drags development down. Not by replacing the developer, but by changing how the work is organised.

My first impression

My first impression was simple.

This feels less cramped than most AI coding tools.

With many tools, the interaction pattern becomes very repetitive very quickly:

1. You ask for help.
2. The tool answers.
3. You copy or accept something.
4. You test it elsewhere.
5. You come back and explain what happened.
6. You repeat the cycle.

That loop can still be useful, but it is also tiring. It forces you to do a lot of the glue work yourself.

What attracted me to Antigravity is that it seems designed around reducing that glue work. If a tool can help plan a task, run commands, inspect the browser, and show me proof of what it did through artifacts like task lists, implementation plans, screenshots, and recordings, that makes the whole process feel more coherent.

And that is where the product started to feel interesting to me.

Not because it looked futuristic.

Because it looked practical.

Why I think Google Antigravity feels different

I think the biggest difference is not one feature. It is the operating model.

Most AI coding products still revolve around this idea:

I am doing the work, and the AI occasionally helps.

Google Antigravity feels more like this:

I am directing the work, reviewing the work, and stepping into the work when needed, while agents can carry parts of the load in parallel.

That is a very different mindset.

It shifts the developer’s role from constantly handling every small action to spending more time on judgement, review, priorities, and refinement.

That does not mean the developer becomes passive. Quite the opposite. It means your role becomes more editorial and strategic in the moments where that matters, while the platform helps with execution and verification.

For me, that is much more compelling than yet another assistant that waits for one tiny prompt at a time.

What I liked most about Google Antigravity

There are a few things I found especially appealing.

1. It seems built for real workflows

This may be the biggest reason I rate it so highly.

A lot of AI demos look amazing because they are showing ideal tasks in ideal conditions. That tells me very little about how a product behaves once the work becomes messy.

Antigravity feels aimed at the messy middle.

That includes things like:

1. longer task flows
2. browser based verification
3. task planning before execution
4. multiple agents working in parallel
5. reviewing what happened without digging through endless raw logs

That makes the whole product feel far more grounded.

2. The split between Editor View and Manager Surface is smart

I genuinely like this design choice.

Sometimes I want to work directly in the code.

Sometimes I want to assign work, review progress, and manage higher level tasks without losing sight of the details.

Those are two different modes of thinking, and I think Antigravity recognises that properly. The separation between the editor side and the agent management side is one of the clearest signs that this was designed around real development behaviour rather than a flashy feature checklist.

3. Artifacts are a brilliant idea

This is one of the strongest parts of the whole concept.

Trust is always the issue with AI development tools.

It is not enough for a tool to claim it completed a task. I need to know what it did, how it approached the job, and whether the result actually matches what I asked for.

Google Antigravity addresses that with artifacts such as task lists, implementation plans, screenshots, browser recordings, code diffs, and other review friendly outputs.

That is exactly the kind of detail that reduces the trust gap.

Instead of reading a wall of logs, I can review something tangible.

That makes the tool feel more serious and much more usable.

4. It seems strong for front end work

As someone who cares a lot about how things look and behave, this part matters to me.

Front end work is not just code correctness. It is visual correctness, spacing, interaction, responsiveness, state behaviour, and whether the thing actually works when a human uses it.

That is where browser interaction becomes a huge advantage.

If an agent can help open pages, inspect behaviour, capture screenshots, read console logs, and support browser based validation, then this becomes far more interesting than an AI tool that only stops at code generation.

For UI work, that is a very big deal.

5. Model choice is a real advantage

I also like that Google is not treating one model as the only path.

At the moment, Antigravity offers multiple model options, including Gemini variants and support for Claude and GPT OSS models. I like this because different jobs need different strengths. Sometimes I care more about depth. Sometimes I care more about speed. Sometimes I want a different style of reasoning.

Model optionality makes the platform feel more flexible and more mature.

6. Skills could become one of the best parts

I think this is one of the quieter but more powerful features.

Antigravity supports Skills through a SKILL.md based approach, which means you can define reusable instructions and workflows for the agent.

That may sound small at first, but it is actually huge.

It means the platform is not only about one off prompting. It means you can start turning repeated tasks into reliable patterns. If you work with certain conventions, frameworks, formatting standards, or team rules, Skills give you a way to make that repeatable.

That is where these kinds of tools become much more valuable over time.

7. Planning mode makes a lot of sense

I appreciate that Antigravity distinguishes between deeper work and faster work.

The official guidance describes Planning mode for more complex tasks where the agent first organises the work, produces task groups, and creates richer artifacts. There is also a Fast mode for more localised and lightweight tasks.

That is exactly how a sensible product should behave.

Not every task needs the same level of analysis. Not every task should be rushed either.

Giving users both options is smart.

Why I enjoyed it conceptually even before going deep

Some tools feel technically impressive but emotionally flat.

They may be capable, but they do not make the work feel better.

Google Antigravity gave me the opposite feeling.

What I liked is that it seems built to make development feel lighter.

That is important because a lot of the frustration in development does not come from the hardest problem on the page. It comes from friction.

Friction when you have to test something manually again.

Friction when you lose focus switching between tools.

Friction when a task becomes more annoying than difficult.

Friction when you need to verify changes but the proof is scattered everywhere.

A good tool reduces that drag.

That is the promise I find most compelling here.

Not magic.

Not replacement.

Not unrealistic autonomy.

Just a better flow.

Who I think should try Google Antigravity

I do not think this is only for one narrow kind of developer.

1. Front end developers

Absolutely yes.

If your work depends on actual browser behaviour, UI polish, layout adjustments, interaction testing, and fast feedback loops, Antigravity looks especially relevant.

The browser side alone gives it a clear advantage for front end workflows.

2. Full stack developers

Also yes.

If you are constantly moving between routes, components, APIs, state, terminal commands, and browser checks, a more agent centred workflow can be a very natural fit.

3. Solo builders

I think solo builders may get a lot from this.

When you are building alone, every piece of friction lands directly on you. There is no handoff. There is no extra pair of eyes. There is no second person doing the boring bits.

A tool that helps structure tasks, reduce switching, and make validation easier can feel especially useful when you are carrying everything yourself.

4. Curious beginners

I would not tell beginners to expect magic, but I do think curious beginners can benefit.

Google’s own getting started material explicitly says the codelab is designed for users and developers of all levels, including beginners. That makes sense to me because a tool like this can make learning more interactive and more connected to real workflows, as long as the user still thinks critically.

5. Developers who enjoy trying new tools early

If you like spotting where development workflows are going, this is exactly the sort of product worth exploring early.

Even if you do not adopt it heavily right away, it gives you a sense of where AI enabled development is moving beyond plain chat inside an editor.

My practical tips and tricks for using Google Antigravity well

If I were recommending this to someone seriously, these are the tips I would give.

1. Start with a real task, not a throwaway demo

Do not waste your first impression on something meaningless.

Give it a task you actually care about.

Examples:

1. refine a landing page section
2. fix a layout bug
3. improve a form flow
4. scaffold a useful component
5. verify a UI change in the browser
6. troubleshoot a broken interaction

The more real the task, the faster you will understand whether the tool suits your workflow.

2. Use Planning mode for anything with moving parts

If a task has multiple steps, dependencies, unknowns, or trade offs, use Planning mode.

That gives the agent space to think through the task properly, organise its work, and produce reviewable artifacts. In my view, that is exactly where Antigravity’s strengths start to show.

Use Fast mode for lighter tasks.

Use Planning mode when the job actually matters.

3. Review the artifacts properly

Do not just read the final claim and assume everything is correct.

Look at the screenshots.

Read the implementation plan.

Check the code diffs.

Watch the browser recording if the task involved UI work.

Artifacts are not decorative. They are one of the best parts of the platform. Use them as intended.

4. Be sensible with permissions at the start

Google’s guidance around terminal execution, review policy, JavaScript execution, and browser allowlists is there for a reason.

Start cautiously.

Let the tool earn more freedom as you get comfortable.

That is the most sensible way to use any system that can execute actions across your environment.

5. Use Skills for repeated workflows

This is one of my biggest practical recommendations.

If you keep doing the same category of task, do not rely on fresh prompting every time.

Build Skills.

That is how you start turning the tool from “occasionally useful” into “part of how I work”.

6. Use it for the messy middle of projects

This is where I think people will get the best value.

The start of a project is often exciting. The end is often clear. The middle is where everything gets awkward.

Half done components.

Ugly edge cases.

Testing loops.

Verification.

Refinement.

Small but annoying fixes.

That is exactly where Antigravity seems strongest.

7. Think of it as a momentum tool

This might sound unusual, but I think it matters.

Sometimes the hardest part of development is not the logic. It is the resistance.

You know what needs doing, but it feels annoying to start because the work is scattered.

If a tool helps reduce that resistance, it does more than save time. It protects momentum.

That is a very real benefit.

Hidden gems I think people may overlook

This is the part I wish more reviews focused on.

Not just the headline features, but the quieter details that actually shape the experience.

1. The review model is part of the product’s value

Many AI tools obsess over creation.

Antigravity also seems to care about review, feedback, and verification.

That is important. The product is not just trying to generate things. It is trying to make the generated work easier to understand and supervise.

That changes the whole feel of the platform.

2. Browser support makes it much more interesting than it first appears

A lot of people may underestimate this.

Browser integration is not just a neat bonus. It is one of the things that turns Antigravity from a coding assistant into a more complete workflow tool.

For front end work in particular, this could be one of the strongest advantages.

3. Skills may quietly become the most important feature for serious users

The more I think about it, the more I believe this.

Reusable skills are how a platform becomes personalised, repeatable, and genuinely integrated into daily work.

That is often where long term value is created.

4. It may help solo work feel less heavy

This is a more human observation than a technical one, but I think it matters.

Building alone can become mentally heavy because every responsibility stays with you. Planning, implementation, testing, review, refinement, rechecking.

A system that helps carry some of that workflow weight can make solo development feel much less draining.

5. The Workspace and MCP direction is worth watching

Antigravity’s support for MCP makes the product more interesting for the future too. If it can securely connect to tools, data sources, and services you already use, then the value goes beyond coding alone.

That is one of the reasons I think this is more than a novelty tool. It has room to become a broader development environment rather than just a smarter editor.

A few honest notes before anyone treats it like magic

I really like the direction of Google Antigravity, but I do not think any review is useful if it sounds blindly impressed.

So here is the honest part.

1. It still needs judgement

No serious developer should use a tool like this with their brain switched off.

The value is not in surrendering judgement. The value is in shifting your effort toward better judgement, better review, and better decisions.

You still need taste.

You still need reasoning.

You still need context.

2. Public preview means evolving product

Google has positioned Antigravity as a public preview product, which means it is still maturing.

That is not necessarily a negative. In many cases it is exciting. But users should still approach it as something actively evolving rather than a completely settled environment.

3. Good controls matter

Any tool that can browse, run commands, and work more autonomously should be used thoughtfully.

Google’s own guidance clearly reflects that, and I think users should take the review policies and safety controls seriously.

That is just sensible practice.

My final verdict

I think Google Antigravity is one of the more interesting AI coding tools I have looked at in quite a while.

Not because it is loud.

Not because it is trying to impress with gimmicks.

Not because it promises impossible things.

I like it because it seems to be asking a better question.

Instead of only asking, “How can AI help me write code faster?” it asks, “How can AI help me move an actual development task forward in a way that is structured, reviewable, and practical?”

That is a much stronger question.

And it leads to a much stronger product direction.

The combination of Editor View, Manager Surface, artifacts, browser support, planning options, Skills, model choice, and MCP support makes Antigravity feel broader and more thoughtful than a standard AI assistant inside an editor.

Most importantly, it sounds like the kind of tool that could make development feel lighter.

And that is the part I care about most.

The tools I keep coming back to are not only the ones that save time. They are the ones that make the work feel better.

Google Antigravity feels like that kind of tool.

So yes, I do think more developers should try it.

Not because it will do everything for them.

But because it looks like one of the clearer signs of where modern development workflows are going, and because it genuinely seems built to make the process more enjoyable.

Tips I would give before your first session

If you are planning to try it, here is the short version of what I would do:

1. install it on a machine where you can test freely
2. start with a real project task, not a toy example
3. use Planning mode for anything meaningful
4. review the artifacts carefully
5. keep permissions conservative at first
6. test browser workflows early if you do front end work
7. create Skills once you notice a repeated pattern
8. use it to reduce friction, not to avoid thinking

If you approach it like that, I think you will get a much clearer sense of why it is interesting.

FAQ

What is Google Antigravity?

Google Antigravity is an agent first development platform from Google. It is designed to let AI agents help with broader engineering tasks across the editor, terminal, and browser instead of only acting as a small autocomplete or chat layer inside an IDE.

Is Google Antigravity free?

At the moment, Google has introduced Antigravity in public preview at no cost for individuals. Availability may still depend on account type, geography, and preview access conditions.

Who should use Google Antigravity?

It looks especially useful for front end developers, full stack developers, solo builders, and developers who enjoy exploring new workflows early. Beginners can also learn from it, as long as they still review outputs carefully and do not treat the tool like magic.

What makes Google Antigravity different from other AI coding tools?

The biggest difference is that it is built around an agent workflow rather than only inline assistance. It combines direct editing with agent management, planning, browser support, terminal execution, and reviewable artifacts such as screenshots, plans, and recordings.

Does Google Antigravity work for front end development?

Yes, and that is one of the reasons I find it especially interesting. Browser interaction, console reading, screenshots, and recordings make it far more relevant for UI work than tools that stop at code generation.

What are Google Antigravity Skills?

Skills are reusable instructions and workflows defined through a SKILL.md based format. They help agents follow repeatable patterns, rules, and task structures more reliably.

Is Google Antigravity good for beginners?

It can be, especially for people who learn best by building and exploring. But beginners still need to review outputs, understand what the tool is doing, and use it as a support system rather than a substitute for learning.

Is Google Antigravity worth trying?

Yes, I think it is worth trying if you care about development workflows, AI coding tools, or reducing friction between planning, coding, testing, and review. What makes it compelling is not just speed. It is the broader workflow design.

My takeaway

If I had to sum it up simply, I would say this:

Google Antigravity feels less like a novelty and more like a serious attempt to rethink how AI fits into development work.

That is why I enjoyed it.

That is why I think it is fun.

And that is why I think more people should give it a proper try.