Can you actually run a full AI software development company on free models?

Yes, for the majority of tasks. The company defaults to Nemotron 3 Ultra 550B A55B on the NVIDIA NIM free tier, and real sessions run on Nemotron 3 Super 120B, also free. The one caveat is heavyweight from-scratch cross-platform builds, which may need a paid frontier model such as DeepSeek V4 Pro (approximately $1.13 for a full desktop-game build). For audits, reviews, incremental implementation, and browser-scale web projects, free-tier Nemotron is enough.

How is this different from ChatDev, AutoGen, CrewAI, or MetaGPT?

Those are stand-alone Python multi-agent frameworks that orchestrate LLM calls from outside your editor. SANYALnet Labs runs inside a production coding CLI (a fork of Kimi Code) as native subagents that share one session, one conversation transcript, one workspace, and the same tool surface (file system, shell, git, MCP servers) that a solo developer would use. The result feels like six colleagues working in the same terminal, not six processes coordinating over a queue.

Do I need a paid API key to try it?

No. A free NVIDIA NIM key from build.nvidia.com is enough for the whole install, the Phase 1 project audit, and most day-to-day company work. Add a DeepSeek key later only if you want to run the DeepSeek V4 Pro adjudicated code-review workflow.

What operating systems and CPU architectures are supported?

Six: Linux x64, Linux ARM64, macOS Intel (x64), macOS Apple Silicon (ARM64), Windows x64, and Windows ARM64. Pre-built binaries for every combination ship under the kimi-code-sanyalnet-cli-vX.Y.Z release tag, and a GitHub Actions smoke workflow verifies the install path on all six on every push to main.

Will it modify my existing codebase without asking?

No. The SDLC directive halts after the automatic Phase 1 audit and refuses to proceed to blueprint, code, review, or test phases without an explicit operator instruction. You get an evidence-backed Project Status Briefing with file-and-line citations, a menu of candidate next steps, and a hard stop. Nothing gets written, refactored, or deleted until you approve a scope.

Is this a good fit for solo developers, or only teams?

Solo developers benefit the most, because the company gives one person the leverage of a five-person engineering team: a strategist, an architect, an implementer, a reviewer, and a QA engineer, without the coordination overhead. The operator-halt design means the human stays in the loop on every scope decision, which is exactly what a solo developer wants.

How does it compare to using a single AI coding assistant?

A single assistant conflates roles: the same context that just wrote the code is asked to review it, which produces predictably shallow audits. Splitting the work across six subagents with dedicated persona prompts, each with its own reasoning context and its own definition of done, catches classes of defects a monolithic assistant misses, especially concurrency bugs, silent fallbacks, and integration-test coverage gaps.

Supratim Sanyal's Computing Blog | Wandering Digital Wastelands as a Geek

Part 5 of the AI Agents series. A six-role software development company — CEO, CPO, CTO, programmer, reviewer, tester — running as native subagents inside a downstream fork of the Kimi Code CLI, powered by free NVIDIA NIM (Nemotron) models, verified on six platforms, and shipping a browser-playable Snakes and Ladders arena.

What this post covers:

How to build a multi-agent AI software development team that runs an end-to-end SDLC (inception, blueprint, code, review, test) inside a single coding CLI session.
Why forking a production coding CLI (Kimi Code) is a better fit than assembling a separate multi-agent framework (ChatDev, AutoGen, CrewAI) for real-world software delivery.
How to make an OpenAI-compatible NVIDIA NIM (Nemotron 3 Ultra 550B, Nemotron 3 Super 120B) endpoint work with a client that assumes Kimi/Anthropic API conventions.
A step-by-step install of pre-built binaries on Linux (x64 / ARM64), macOS (Intel / Apple Silicon), and Windows (x64 / ARM64).
Honest engineering post-mortems: the WaitFor timeout saga, a GitHub Actions YAML parse bisect, and provider-compatibility gotchas for OpenAI-compatible gateways.
A live browser deliverable — a four-player Indian Snakes & Ladders arena — produced end-to-end by the agent team.

Six subagents (ceo, explore, cto, programmer, reviewer, tester) active in a single kimi session on Nemotron 3 Super 120B via NVIDIA NIM, closing out a bad-regressions report against a snakes-and-ladders workspace. Sixty-two minutes in; four subagents already checkpointed and closed, tester still running the verification suite across 153 tool calls.

Six subagents on Nemotron 3 Super 120B via NVIDIA NIM, in one kimi session, closing out a bad-regressions report against a Snakes and Ladders workspace. Sixty-two minutes in; the tester is still running the verification suite across 153 tool calls.

For four posts now this blog has been running someone else's virtual software company — ChatDev 2.0, wired up to free NVIDIA NIM models, and put through progressively harder assignments: a smoke test on Linux, a live AI news debate wall, a cross-platform Ludo game, and finally a public GitHub release stress-tested on eleven runners. The framework held up. Along the way it also demonstrated, in Part 3, that a green build and a passing test suite can quietly ship a completely broken headline feature; and, in Part 4, that "it works on my machine" reliably hides four defects until the code lands on a machine that was not the author's.

This post moves the company one layer down. Instead of using someone else's multi-agent AI framework and someone else's models, SANYALnet Labs now owns the coding harness itself. The virtual software company is no longer a Python process orchestrated from outside; it lives inside a downstream fork of a production AI coding CLI, as six bindable subagents — autonomous coding agents that share a single session, a single model, and a single conversation transcript. This is agentic SDLC done as one continuous transcript, not a message bus between processes.

Supratim Sanyal's Computing Blog | Wandering Digital Wastelands as a Geek

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Friday, September 4, 2026

Build a Six-Role AI Software Company by Forking Kimi Code: Multi-Agent SDLC on NVIDIA NIM