- What changed in AI coding help
- Pick by how you like to work
- Nine assistants side by side
- The assistants in alphabetical order
- Privacy, data handling and the NIST framework
- Licences, open source and your legal team
- A sensible way to trial them
- My advice for picking a coding assistant
- Frequently asked questions
The best Tabnine alternative depends on how much you want the AI to do. If you want smarter autocomplete, pick a completion-focused tool. If you want it to write and fix whole features, pick an agent-based assistant. If your code can't leave your network, prioritise open-source or on-premise options first.
A few years ago an AI code assistant meant one thing: grey text appearing ahead of your cursor. Tabnine is one of the tools from that completion era, and plenty of developers still want exactly that. But the category has split. Some assistants now run agents that open pull requests, and some build entire apps from a sentence.
So the nine tools below cover the whole spread, in no particular order, A to Z. Each description is the vendor's own wording, rewritten plainly, so test how they'll behave on your own code before you trust them.
Do you make AI coding assistants? Tool makers can ask to be considered for a featured place on this list.
What changed in AI coding help
The shift is from suggesting to doing. Completion tools guess your next line. Agent tools take a task, plan it, edit several files and hand you the result to review. That's powerful, but it changes your job from typing to checking, and it means the assistant needs far more access to your codebase.
If you're weighing up how the big agent tools compare, my head-to-head of Claude Code and Kiro is a useful companion to this list.
Pick by how you like to work
- You like writing code yourself: stick to completion tools and keep agents for chores.
- You'd hand off whole tasks: try an agent-based assistant on a small, well-tested part of the codebase first.
- Your code can't leave the building: shortlist open-source and on-premise options before anything else.
- You're not a developer at all: an app builder that works from plain-language descriptions is the better fit.
- Your team uses one IDE family: check which assistants work natively there, so nobody has to switch editors.
Nine assistants side by side
| Tool | Kind | Good for |
|---|---|---|
| Amazon Q Developer | AI coding assistant | Writing, debugging and refactoring in the IDE |
| Blackbox AI | Model access for coding | Choosing and hosting your own model |
| GitHub Copilot | AI coding assistant | Help from issue to merged pull request |
| JetBrains AI | Agent system for JetBrains | Bringing your own agents into one system |
| Refact | Open-source coding agent | On-premise AI that knows your workflow |
| Replit | App builder | Describing an app instead of coding it |
| Supermaven | Code completion | Completions that see lots of context |
| Void | Open-source AI IDE | An AI editor with privacy built in |
| Windsurf | Agent command center | Running several agents at once |
The assistants in alphabetical order
Amazon Q Developer
Best for: builders already on AWS who want an assistant that writes, debugs and refactors code natively in their IDE.
Blackbox AI
Best for: privacy-minded teams that want a chosen open-weight model as a dedicated deployment, or many models through one endpoint.
GitHub Copilot
Best for: developers living on GitHub who want help at every step, from an open issue to a reviewed and merged pull request.
JetBrains AI
Best for: JetBrains users who'd like one system for building with agents, including ones they already use and ACP-compatible agents.
Refact
Best for: organisations that want an open-source coding agent with full context awareness that can be deployed on-premise.
Replit
Best for: non-developers and founders who want to describe what they need and get a working app or website back.
Supermaven
Best for: coders who mainly want fast inline completions backed by a 1 million token context window.
Void
Best for: developers who want an open-source AI code editor designed around full privacy.
Want AI doing the heavy lifting in your marketing?
I build the systems that handle the boring 80 percent, so you get your week back. Done properly, with the human kept in.
Windsurf
Best for: people who want to plan, review and ship with a team of agents, local or cloud, managed from one command center.
Privacy, data handling and the NIST framework
Here's the question I'd ask before any feature question: what happens to the code you send it? The NIST AI Risk Management Framework is intended for voluntary use to improve the ability to build trustworthiness into the design, development, use and evaluation of AI products, services and systems. You don't need to adopt the whole framework to borrow its thinking.
In plain terms, ask each vendor where prompts and code are processed, whether they're stored or used for training, and whether you can run the model somewhere you control. Then write the answers down. A tidy one-page note per tool makes the security conversation much shorter.
Licences, open source and your legal team
Open-source assistants and editors are attractive because you can see the code and run it where you like. But they come with their own homework: someone has to keep them updated, and someone has to check the licence fits how your company works. That isn't a reason to avoid them. It's a reason to give one person ownership of the tool from day one.
Hosted assistants shift that work to the vendor, which suits small teams with no spare engineer for upkeep. The trade is less control over where your code goes. Neither is wrong. Pick the side of that trade your business can live with.
A sensible way to trial them
- Choose two or three assistants from the group that matches how you work.
- Give each the same real tasks: a bug fix, a small feature, a refactor.
- Time how long you spend checking and correcting the output, not just how fast it appeared.
- Ask the people who'd use it daily which one they'd keep.
If your team's still learning to work with agents, structured learning helps more than random experiments. These Claude Code courses are a good starting point for the habits that carry across tools.
My advice for picking a coding assistant
Choose the least powerful tool that does the job you want. If you love writing code and just want fewer keystrokes, a completion tool will make you happier than an agent that rewrites files you didn't ask it to touch. If you're drowning in routine tickets, an agent may earn its keep. Whichever way you go, keep a human reviewing every change before it ships, and look at your choice again every few months, because this category moves faster than almost any other in software.
Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.
Frequently asked questions
What is the difference between code completion and an AI coding agent?
Code completion suggests the next line or block as you type. An AI coding agent takes a task, plans it and edits code across files, then asks you to review the result.
Can I use an AI coding assistant without sending code to the cloud?
Some options are open source or can be deployed on-premise, which keeps code inside your own systems. Check each vendor's documentation on where code is processed and stored.
Do non-developers need a coding assistant?
Usually not. App builders that work from plain-language descriptions suit non-developers better than assistants designed to sit inside a code editor.
Is this list ranked?
No. The assistants are listed A to Z, not in order of preference, and every description is based on the vendor's own website.


