01 · Business & Product Intent
Intent
Are we solving the right problem?
Defines
Artifacts
- Intent Brief
- Process Map
- Outcome Definition
- Acceptance Criteria
Cian-OS™ · AI-Native Software Delivery System Asking AI is easy.
Asking AI is easy.
Knowing what to ask isn’t.
Cian-OS is Ciancoders’ engineering operating system: it defines how people and AI agents turn business problems into software that is verifiable, maintainable and operable.
- What is Cian-OS?
- Cian-OS™ is Ciancoders’ accumulated knowledge from 400+ projects since 2015, turned into rules, artifacts, controls, quality gates, responsibilities and verification practices. It is organized into five systems — Intent, Foundation, Build, Verify and Operate — with eight cross-cutting controls, and governs every Build, Rescue, Scale and Operate engagement.
The thesis
AI lowers the cost of execution. It raises the value of judgment.
Artificial intelligence is dramatically reducing the effort needed to produce code. But generating code is not the same as building software.
As execution gets cheaper and faster, the importance of understanding the right problem, providing context, defining architecture, making trade-offs, designing security, verifying results, operating systems and taking accountability grows in proportion.
Cian-OS exists to organize exactly that work: the part that doesn’t get automated.
Five systems
Each system answers a question AI can’t answer for you.
01
Intent
Business & Product IntentAre we solving the right problem?
02
Foundation
Product & Engineering FoundationAre we making the right decisions before we accelerate?
03
Build
Human + AI EngineeringAre humans and AI agents working with the right context and boundaries?
04
Verify
Continuous VerificationCan we prove that what was built satisfies the original intent?
05
Operate
Production & Continuous ImprovementCan the system stay reliable, understandable and economically sustainable?
02 · Product & Engineering Foundation
Foundation
Are we making the right decisions before we accelerate?
Defines
Artifacts
- Architecture Blueprint
- Data Model
- UX Prototype
- Threat Model
- Engineering Backlog
03 · Human + AI Engineering
Build
Are humans and AI agents working with the right context and boundaries?
AI executes. Humans remain accountable.
Defines
Artifacts
- Repository context
- Bounded tasks
- Review of every change
04 · Continuous Verification
Verify
Can we prove that what was built satisfies the original intent?
Faster generation requires stronger verification.
Defines
Artifacts
- Test suite
- Security report
- Production checklist
05 · Production & Continuous Improvement
Operate
Can the system stay reliable, understandable and economically sustainable?
Defines
Artifacts
- Operations runbook
- Observability dashboard
- Improvement backlog
Control model
Eight controls that run through all five systems.
A control is a question asked in every system, not a document signed at the end. That’s why business value, security, AI governance, documentation and human accountability are present from start to finish.
| Control | Intent | Foundation | Build | Verify | Operate |
|---|---|---|---|---|---|
| Business value | Active | Active | Active | Active | Active |
| Architecture | Not applicable | Active | Active | Active | Active |
| Security | Active | Active | Active | Active | Active |
| Quality | Not applicable | Active | Active | Active | Active |
| AI governance | Active | Active | Active | Active | Active |
| Cost | Active | Active | Active | Not applicable | Active |
| Documentation | Active | Active | Active | Active | Active |
| Human accountability | Active | Active | Active | Active | Active |
- Business value Intent: activeFoundation: activeBuild: activeVerify: activeOperate: active
- Architecture Intent: not applicableFoundation: activeBuild: activeVerify: activeOperate: active
- Security Intent: activeFoundation: activeBuild: activeVerify: activeOperate: active
- Quality Intent: not applicableFoundation: activeBuild: activeVerify: activeOperate: active
- AI governance Intent: activeFoundation: activeBuild: activeVerify: activeOperate: active
- Cost Intent: activeFoundation: activeBuild: activeVerify: not applicableOperate: active
- Documentation Intent: activeFoundation: activeBuild: activeVerify: activeOperate: active
- Human accountability Intent: activeFoundation: activeBuild: activeVerify: activeOperate: active
Human + AI
AI executes. Humans remain accountable.
What AI accelerates
- Analysis of existing code and documentation
- Code generation on bounded tasks
- Guided refactoring
- Tests and edge cases
- Documentation and migrations
- Repetitive implementation
What stays human
- Intent and problem definition
- Architecture and trade-offs
- Security and sensitive data handling
- Review of every change
- Acceptance against the original intent
- Accountability for the outcome in production
Principles
Seven engineering principles.
- 01
Intent before execution.
AI never replaces understanding the problem.
- 02
Context is infrastructure.
The context people and agents receive is treated as an engineering asset: written, versioned and reviewed.
- 03
Architecture before acceleration.
We don't accelerate decisions that shouldn't have been made yet.
- 04
AI executes. Humans remain accountable.
AI can execute work. Accountability for the outcome stays human.
- 05
Verification scales with generation.
The faster we produce, the more systematic validation has to be.
- 06
Production is the definition of done.
A working demo is not finished software.
- 07
Every system must remain understandable.
Code, architecture and decisions must stay maintainable regardless of who — person or agent — produced them.
Where it applies
One system. Four capabilities.
Build I have a process
I know what my business needs to improve, but not how to turn it into software.
Custom Software Engineering Rescue I already built somethingMy app works, but I'm not sure I should keep building on it.
Production Readiness Scale I have a roadmapI have a product and priorities. I lack engineering capacity.
Dedicated AI Engineering Operate I'm already in productionI need someone to own operations and evolution.
Software CareQuestions about Cian-OS
Is Cian-OS an agile methodology?+
It’s compatible with Scrum, Kanban or whatever rhythm your team uses. Cian-OS doesn’t define ceremonies: it defines what has to be settled before accelerating, how people and AI agents work, and how what gets built is verified and operated.
Which AI tools do you use?+
Professional AI-assisted engineering tools, with versioned context in the client’s repository. The tool can change; the system of controls and verification doesn’t.
What does Cian-OS measure?+
We don’t measure how much code AI produces. We measure how much verified software reaches production and keeps running.
Can I adopt Cian-OS with my own team?+
Dedicated pods work with Cian-OS inside your team, and its artifacts — context, controls, checklists — stay in your repository. In practice, that is adopting it.
A system, not a promise.
See it applied to your project.
Tell us what you're trying to solve. We'll help you decide whether to build, rescue, extend your team — or take a different path.
30 minutes · No commitment · English or Spanish