Remote-first AI coding startup Kilo doesn’t think software developers should have to pledge their undying allegiance to any one development environment — and certainly not any one model or harness.
This week, the startup — backed by GitLab co-founder Sid Sijbrandij — unveiled Kilo CLI 1.0, a complete rebuild of its command-line tool that offers support for more than 500 different underlying AI models from proprietary leaders and open source rivals like Alibaba’s Qwen.
It comes just weeks after Kilo launched a Slackbot allowing developers to ship code directly from Salesforce’s popular messaging service (Slack, which VentureBeat also uses) powered by the Chinese AI startup MiniMax.
The release marks a strategic pivot away from the IDE-centric “sidebar” model popularized by industry giants like Cursor and GitHub Copilot, or dedicated apps like the new OpenAI Codex, and even terminal-based rivals like Codex CLI and Claude Code, aiming instead to embed AI capabilities into every fragment of the professional software workflow.
By launching a model-agnostic CLI on the heels of its Slack bot, Kilo is making a calculated bet: the future of AI development isn’t about a single interface, but about tools that travel with the engineer between IDEs, terminals, remote servers, and team chat threads.
In a recent interview with VentureBeat, Kilo CEO and co-founder Scott Breitenother explained the necessity of this fluidity: “This experience just feels a little bit too fragmented right now… as an engineer, sometimes I’m going to use the CLI, sometimes I’m going to be in VS Code, and sometimes I’m going to be kicking off an agent from Slack, and folks shouldn’t have to be jumping around.”
He noted that Kilo CLI 1.0 is specifically “built for this world… for the developer who moves between their local IDE, a remote server via SSH, and a terminal session at 2 a.m. to fix a production bug.”
Technology: Rebuilding for ‘Kilo Speed’
Kilo CLI 1.0 is a fundamental architectural shift. While 2025 was the year senior engineers began to take AI vibe coding seriously, Kilo believes 2026 will be defined by the adoption of agents that can manage end-to-end tasks independently.
The new CLI is built on an MIT-licensed, open-source foundation, specifically designed to function in terminal sessions where developers often find themselves during critical production incidents or deep infrastructure work.
For Breitenother, building in the open is non-negotiable: “When you build in the open, you build better products. You get this great flywheel of contributors… your community is not just passive users. They’re actually part of your team that’s helping you develop your product… Honestly, some people might say open source is a weakness, but I think it’s our superpower.”
The core of this “agentic” experience is Kilo’s ability to move beyond simple autocompletion. The CLI supports multiple operational modes:
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Code Mode: For high-speed generation and multi-file refactors.
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Architect Mode: For high-level planning and technical strategy.
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Debug Mode: For systematic problem diagnosis and resolution.
Solving multi-session memory
To solve the persistent issue of “AI amnesia”—where an agent loses context between sessions—Kilo utilizes a “Memory Bank” feature.
This system maintains state by storing context in structured Markdown files within the repository, ensuring that an agent operating in the CLI has the same understanding of the codebase as the one working in a VS Code sidebar or a Slack thread.
The synergy between the new CLI and “Kilo for Slack” is central to the company’s “Agentic Anywhere” strategy. Launched in January, the Slack integration allows teams to fix bugs and push pull requests directly from a conversation.
Unlike competing integrations from Cursor or Claude Code —which Kilo claims are limited by single-repo configurations or a lack of persistent thread state — Kilo’s bot can ingest context from across multiple repositories simultaneously.
“Engineering teams don’t make decisions in IDE sidebars. They make them in Slack,” Breitenother emphasized.
Extensibility and the ‘superpower’ of open source
A critical component of Kilo’s technical depth is its support for the Model Context Protocol (MCP). This open standard allows Kilo to communicate with external servers, extending its capabilities beyond local file manipulation.
Through MCP, Kilo agents can integrate with custom tools and resources, such as internal documentation servers or third-party monitoring tools, effectively turning the agent into a specialized member of the engineering team.
This extensibility is part of Kilo’s broader commitment to model agnosticism. While MiniMax is the default for Slack, the CLI and extension support a massive array of over 500 models, including Anthropic, OpenAI, and Google Gemini.
Pricing: The economy of ‘AI output per dollar’
Kilo is also attempting to disrupt the economics of AI development with “Kilo Pass,” a subscription service designed for transparency.
The company charges exact provider API rates with zero commission—$1 of Kilo credits is equivalent to $1 of provider costs.
Breitenother is critical of the “black box” subscription models used by others in the space: “We’re selling infrastructure here… you hit some sort of arbitrary, unclear line, and then you start to get throttled. That’s not how the world’s going to work.”
The Kilo Pass tiers offer “momentum rewards,” providing bonus credits for active subscribers:
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Starter ($19/mo): Up to $26.60 in credits.
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Pro ($49/mo): Up to $68.60 in credits.
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Expert ($199/mo): Up to $278.60 in credits.
To incentivize early adoption, Kilo is currently offering a “Double Welcome Bonus” until February 6th, giving users 50% free credits for their first two months.
For power users like Sylvain, this flexibility is a major draw: “Kilo Pass is exactly what I’ve been waiting for. I can use my credits when I need them and save them when I don’t—it finally fits how I actually use AI.”
Community, security, and competition
The arrival of Kilo CLI 1.0 places it in direct conversation with terminal-native heavyweights: Anthropic’s Claude Code and Block’s Goose.
Outside of the terminal, in the more full featured IDE space, OpenAI recently launched a new Codex desktop app for macOS.
Claude Code offers a highly polished experience, but it comes with vendor lock-in and high costs—up to $200 per month for tiers that still include token-based usage caps and rate limits. Independent analysis suggests these limits are often exhausted within minutes of intensive work on large codebases.
OpenAI’s new Codex app similarly favors a platform-locked approach, functioning as a “command center for agents” that allows developers to supervise AI systems running independently for up to 30 minutes.
While Codex introduces powerful features like “Skills” to connect to tools like Figma and Linear, it is fundamentally designed to defend OpenAI’s ecosystem in a highly contested market.
Conversely, Kilo CLI 1.0 utilizes the MIT-licensed OpenCode foundation to deliver a production-ready Terminal User Interface (TUI) that allows engineers to swap between 500+ models.
This portability allows teams to select the best cost-to-performance ratio—perhaps using a lightweight model for documentation but swapping to a frontier model for complex debugging.
Regarding security, Kilo ensures that models are hosted on U.S.-compliant infrastructure like AWS Bedrock, allowing proprietary code to remain within trusted perimeters while leveraging the most efficient intelligence available.
Goose provides an open-source alternative that runs entirely on a user’s local machine for free, but seems more localized and experimental.
Kilo positions itself as the middle path: a production-hardened tool that maintains open-source transparency while providing the infrastructure to scale across an enterprise.
This contrasts with the broader market’s dual-use concerns; while OpenAI builds sandboxes to secure autonomous agents, Kilo’s open-core nature allows for a “superpower” level of community auditing and contribution.
The future: A ‘mech suit’ for the mind
With $8 million in seed funding and a “Right of First Refusal” agreement with GitLab lasting until August 2026, Kilo is positioning itself as the backbone of the next-generation developer stack.
Breitenother views these tools as “exoskeletons” or “mech suits” for the mind, rather than replacements for human engineers.
“We’ve actually moved our engineers to be product owners,” Breitenother reveals. “The time they freed up from writing code, they’re actually doing much more thinking. They’re setting the strategy for the product.”
By unbundling the engineering stack—separating the agentic interface from the model and the model from the IDE—Kilo provides a roadmap for a future where developers think architecturally while machines build the structure.
“It’s the closest thing to magic that I think we can encounter in our life,” Breitenother concludes. For those seeking “Kilo Speed,” the IDE sidebar is just the beginning.
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