Coding agent
with methodology
TAO·CODER is not a chatbot that generates code on demand. It's a full-featured development tool with a built-in methodology. Bounded context, stage pipeline, managed memory — one developer can run multiple projects in parallel, faster, cheaper, and more reliably.
await coder.execute(task);
context: bounded
✅ All checks passed
TAO·CODER vs Cursor, Windsurf, Claude Code
Cursor, Windsurf, Claude Code, and TAO·CODER solve similar problems — accelerating development through AI agents. But the approach is fundamentally different.
| Feature | Cursor / Windsurf / Claude Code | TAO·CODER |
|---|---|---|
| Target audience | Mass market: experiments and simple scripts | Professional development: complex B2B systems, Enterprise |
| Context management | Linear dialog history — grows endlessly, model loses focus | Bounded context — external managed memory, prompt always fits |
| Process | Free mode "ask and get" | Stage pipeline — formal stages with tool locking, transparent control |
| Quality assurance | No mandatory checks | check_all.sh — typecheck, linter, tests, documentation. Nothing slips through |
| Subscription cost | $20/month + you still pay for tokens | Free extension + flash models at $1–5 per task |
| Project cost (100-150K lines) | ~$1,000–1,500 over 3 months | $150–200 (7-10× cheaper) |
| Telemetry | Collect logs, code, prompts | Zero telemetry — everything runs locally |
Cursor is great for prototyping and pet projects — modern, polished, with a beautiful UI. TAO·CODER is for production-grade development of complex systems: it gives you control, predictable costs, and quality you can ship with confidence. They're different tools for different jobs.
Methodology, not just prompts
Bounded context
Typical agents accumulate dialog history linearly — each step adds previous messages to the prompt. The context window fills up, the model loses focus, costs spike.
TAO·CODER externalizes task memory to a structured Task Context on disk. Only the current stage, task spec, relevant code snippets, and recent dialog turns enter the prompt. History stays bounded — the model stays focused.
Stage pipeline
Instead of a free-form "ask and get" mode, TAO·CODER runs each task through formal stages. Each stage has its own toolset. During data collection, write tools are locked — the agent cannot accidentally modify code while studying the project.
Update-cycle
Two complementary mechanisms transfer information from dialog to long-term memory: the agent consciously records findings through tools (taocoder_add_relevant_code_ref
and others), plus an automatic update-cycle periodically analyzes accumulated dialog and extracts additional facts.
check_all.sh — quality gate
A validation script that runs typecheck, linter, tests, and documentation checks. The task cannot be completed until check_all.sh passes.
Transparent economics — pay only for tokens
Do the math. Cursor/Windsurf: $20/month × 12 = $240 per year in subscription alone + you still pay for tokens. TAO·CODER: $0 for the extension + $150–200 for an entire medium project.
| Parameter | Value |
|---|---|
| Flash models for daily work | DeepSeek V4 Flash, Gemini Flash, Claude Haiku |
| Frontier models for complex tasks | DeepSeek V4 Pro, Qwen, GPT — only when needed |
| Telemetry | Zero — everything runs locally |
Install in 2 minutes
Open VS Code → Extensions (Cmd+Shift+X)
Search for TAO·CODER (with dot)
Click Install → Trust Developer
Add your API key (start with DeepSeek)
Start with Architect mode
Frequently asked questions
How much does TAO·CODER cost?
Does TAO·CODER collect my data?
Which models are supported?
Can I use TAO·CODER in Enterprise?
How is TAO·CODER different from Cursor?
Why the dot in the name?
TaoCoder.
Ready to try it?
Install TAO·CODER for free — it takes 2 minutes. See for yourself why professional developers choose the engineering approach.
Enterprise deployment
Need a private deployment on your own infrastructure? Use TAO·CODER with local LLMs and full data control.
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