Other tools re-read your repository and forget everything when you close the tab.
The coding agent that
knows your project
Arkoder knows your code, your product and the why of your business. Start every task with that context already injected, define the spec before coding and it updates with your approval. You configure 4 things. Nothing else.
Current agents make you
work for them.
You waste time explaining what your project already knows. And when they understand it, they forget it.
Re-reading the repository
The agent scans thousands of files each session and still does not understand the why of your decisions.
Re-explaining the context
Every new conversation means pasting the architecture, business rules and decisions again.
Endless configuration
Dozens of settings, providers and API keys before writing your first line with AI.
Data that goes far away
Your prompts and code train third-party models, with nothing you can do about it.
The context that
never forgets.
Configure each project once and the agent starts every task knowing your code, your rules and the why of your business. Everything separated in two layers.
Immutable information
Stack, architecture and decisions that must not change. Arkoder never alters them unless you decide to.
Adaptable knowledge
What does evolve with your work: APIs, flows and new details. It only changes when you approve the diff.
The why of your business
Add rules, product and business context: the "what for". The agent decides with the same judgment as you.
Active project
Only one active project at a time. Its context is injected at the start of every conversation: no repo re-reading.
Define the task well.
Then let it code.
The Spec Wizard turns an idea into a complete specification: it asks the right questions, leaves it ready to edit and only then starts development.
1 · Tell it what you want to achieve
Describe the goal in your own words, no format. The why also counts.
Uses the active project context2 · Answer its questions
It asks for clarifications on scope, decisions and edge cases to avoid misunderstandings.
3 · Review the specification
Read the document, edit it to your liking and approve or discard each proposal.
4 · Start coding
Only with the approved spec does the agent implement. Zero ambiguity, fewer surprises.
- Accept card tokenization and charging with idempotent retries.
- Handle duplicates at the payment gateway.
- The transaction state is persisted and queried from a single source.
- Confirmation webhook verified by signature.
- Retry after timeout does not duplicate the charge.
- Correct denied-payment response.
Learn from every task.
Only what is new.
When a task completes, the system reviews what you actually did. If you discovered or something changed, it proposes it as a diff. If there is nothing new, it does not bother you: most tasks generate no learnings.
You complete a task
The agent finishes the whole job: file changes, database, unit tests, everything.
The system compares
It analyzes the conversation against the project adaptable knowledge and detects what is really new.
Only if there is something, it proposes a diff
It shows you what comes in and what has become obsolete. Immutable information never changes here.
You decide
Accept, reject or tick checkboxes. Nothing is saved without your explicit approval.
All the power.
Just four settings.
While other agents overwhelm you with dozens of options, Arkoder is set up with four. And the LLM comes built in: there is nothing else to assemble.
Language
Your agent works in your language. No fuss, no friction.
Auto-approval
Decide how much autonomy you give it: from asking about everything to flowing with you.
MCP
Connect your tools and services. One setting, no complexity.
Projects
The heart of the system: memory, context and learning for each project.
No API keys, no providers, nothing to configure. Subscribe and start coding with your agent.
Your data does not train
a third-party model.
Your code and conversations are not used to train models nor handed to third-party companies. Three layers guarantee it.
Knowledge on your machine
Your projects memory and learnings are stored locally, inside the extension. You control them.
Own infrastructure
Compute runs on high-performance own infrastructure. Nothing is outsourced or resold.
Top models, no ownership
It relies on top-tier models that are not owned by a single provider. No lock-in, no training with your data.
Simple plans.
No surprises.
Plans for every pace: from individual use to teams and unlimited usage. The LLM included and all features. Pick the one that fits you.
For individual developers who want a memory-powered agent without hassle.
+ VAT · No commitment · Cancel anytime
- 10.000 Compute credits per month
- Standard service priority
- No connection limit
- LLM included in the extension
- Unlimited projects with context memory
- Spec Wizard: define the spec before coding
- Automatic learning with diff approval
- MCP and auto-approval
For those who code with AI every day and want more headroom and high priority.
+ VAT · No commitment · Cancel anytime
- 25.000 Compute credits per month
- High service priority
- No connection limit
- LLM included in the extension
- Unlimited projects with context memory
- Spec Wizard: define the spec before coding
- Automatic learning with diff approval
- MCP and auto-approval
For teams: one key per seat and per-developer usage control.
+ VAT · No commitment · Cancel anytime
- 25.000 Compute credits per seat and month
- High service priority
- No connection limit
- LLM included in the extension
- Unlimited projects with context memory
- Spec Wizard: define the spec before coding
- Automatic learning with diff approval
- MCP and auto-approval
For a single developer who does not want to think about limits, with top priority.
+ VAT · No commitment · Cancel anytime
- Unlimited Compute credits fair use
- High service priority
- One active connection at a time
- LLM included in the extension
- Unlimited projects with context memory
- Spec Wizard: define the spec before coding
- Automatic learning with diff approval
- MCP and auto-approval
Prices exclude VAT. All plans include the extension, the LLM, Projects and Learning. No commitment: change or cancel anytime.
Frequently
asked questions
No. The LLM is built into the extension and included in your subscription. No API keys, no providers, nothing to configure: subscribe, activate your project and start.
When a task is completed (not halfway), it evaluates the conversation against the stored project knowledge and generates a proposed change. Nothing is saved without your explicit approval, change by change.
Immutable information, adaptable knowledge and learnings are stored locally, inside the extension on your machine. Only the context needed for the current task travels.
The extension handles very large contexts and, when approaching the limit, automatically compacts the context and continues. You do not lose the thread in long tasks.
It means unlimited usage for real development work, with one active connection at a time to guarantee service quality for everyone. No token counters to watch.
Yes. MCP is built in and configured in one setting. And being a VS Code extension, it works with the stack you already use: TypeScript, Python, Go, Rust, Java and any other language in your repository.
Yes. No commitment: switch plans or cancel anytime from your subscription panel. Your project knowledge stays local, on your machine.
It is the way to plan before coding. You tell it what you want to achieve and, using your active project context, it asks a few questions and returns an editable specification (scope, requirements and tests) that you approve. Only then does it start developing on that base.
Not from all. Only when a task discovers something genuinely new —not already captured in your knowledge— does it propose it as a diff to the adaptable knowledge. If nothing is new, it does not bother you: most tasks generate no learnings.
No. Immutable information is yours and only you modify it, by hand. Task learning only affects adaptable knowledge and always requires your explicit approval, change by change. The immutable layer never changes here.
Agent Compute measures actual AI work rather than simply counting requests. Cached project context consumes less Compute than new context, generated code/reasoning, or image processing.
An agent that remembers,
plans and learns.
Define the spec before coding, rely on what your project already knows and approve only what truly adds value. Activate your first project and let Arkoder work with you from the first message.
LLM included · No API keys · Cancel anytime
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