What is the Agentic SDLC?
A software lifecycle where specialised AI agents execute the work and people govern the decisions, with every step traceable from business intent to production. It is the method behind every Stack18 engagement.
- Intent-driven
- AI-executed
- Human-governed
- Fully traceable
Used on every Stack18 engagement. Free 30-minute consultation.
- Intent-drivenStart from business goals, not tickets
- AI-executedAgents do the repetitive engineering work
- Human-governedPeople approve what reaches production
- Fully traceableEvery artifact traces back to intent
What is the Agentic SDLC?
The Agentic SDLC is Stack18’s AI-native software development lifecycle and management platform. It connects intent, requirements, design, code, testing, deployment and operations into one lifecycle. Specialised AI agents execute the work, and people approve critical decisions at governance gates, so every artifact is traceable and nothing reaches production without sign-off. It is not an AI coding tool: coding is one stage of seven.
Traditional delivery vs the Agentic SDLC.
AI coding tools help in one stage, writing code, and stop at the editor. Agencies deliver project by project with manual handoffs. The Agentic SDLC connects the whole lifecycle in one traceable system with governance built in.
| Traditional delivery | Agentic SDLC | |
|---|---|---|
| Handoffs | Manual, so intent gets diluted at every step | Context moves with the work; nothing is re-explained |
| Requirements and design | Requirements live in documents, and design and code drift apart | Requirements, design, code and tests stay linked to the intent that justified them |
| Who does the work | People across separate tools | Specialised AI agents execute; people govern |
| Governance | Speed without control: no shared oversight of AI or of stages | Approval gates, permissions and policies at every stage |
| Audit trail | Reconstructed after the fact | Recorded as the work happens |
| Documentation | Falls behind the code | Living documentation that updates as the system changes |
| Knowledge | Leaves when people do | Captured in a connected software graph |
| Pricing model | Time and materials, open-ended | Fixed-price first step, then fixed scope or a monthly team |
Seven stages, from discover to operate.
Each stage takes structured input, executes with AI, passes a governance gate and hands a traceable artifact to the next.
| Stage | Purpose | AI executes | Humans govern | Output |
|---|---|---|---|---|
| 1. Discover | Capture what the business actually needs. | Synthesizes inputs, maps stakeholders, risks and open questions | Confirms intent, scope and success measures | Intent brief |
| 2. Define | Turn intent into precise, testable requirements. | Drafts the PRD, user stories and acceptance criteria; flags conflicts and gaps | Approves requirements | Requirements set |
| 3. Design | Shape the system before a line of code exists. | Proposes architecture, data model, API contracts and UI/UX flows | Approves architecture and design decisions | Architecture and design specs |
| 4. Build | Generate production code that matches the spec. | Generates code, APIs and integrations, with tests and documentation | Reviews critical changes and sets standards | Working code with tests |
| 5. Test | Verify against intent, not just against code. | Runs functional, regression and security checks and triages failures | Signs off on release readiness | Quality report |
| 6. Deploy | Ship through pipelines you can trust. | Builds pipelines, provisions environments and stages releases | Approves promotion to production | Live release |
| 7. Operate | Close the loop with what production teaches. | Monitors health, flags regressions and suggests fixes | Prioritizes what improves next | Insights for the next cycle |
Ten specialised agents, each with a job.
AI agents are the execution layer. Every one of them is visible and managed in the command center, with its permissions, current task and output.
| Agent | Capability | Lifecycle stage |
|---|---|---|
| Compass | Discovery | Discover |
| Draft | Requirements | Define |
| Blueprint | Architecture | Design |
| Frame | Experience design | Design |
| Grid | Data and APIs | Design, Build |
| Weld | Engineering | Build |
| Watch | Quality | Test |
| Ledger | Documentation | All stages |
| Launch | Release | Deploy |
| Pulse | Monitoring | Operate |
AI executes. Humans govern.
Gates are configurable per project, team and risk level, and every decision is recorded to the audit trail. Human approval is required for production releases, architecture changes and data access. Read more on our security and AI governance page.
Intent gate
Scope, goals and constraints confirmed
Requirements gate
Acceptance criteria approved
Architecture gate
Design and data decisions signed off
Release gate
Quality and security evidence reviewed
Production gate
Promotion approved by the right owner
One lifecycle, many kinds of work.
The same lifecycle adapts to very different kinds of delivery. See SaaS product development, legacy modernization and AI product development.
New products
Go from a business idea to specs, working code, tests and pipelines in one traceable flow.
Modernization
Map what exists into the software graph, then rebuild incrementally with requirements and tests to prove parity.
AI in production
Build AI-powered capabilities with approvals, evaluation and audit trails from the first commit.
Regulated delivery
Approvals, permissions and audit trails are produced as the work happens, ready when reviewers ask.
Managed services
Track scope, milestones and service levels next to the software and agents delivering them.
AI workforce
See what every agent is doing, approve what matters and measure what it produces.
Key terms, defined.
Agentic SDLC
Stack18’s AI-native software development lifecycle and management platform, where AI executes and humans govern.
AI agent
A specialised AI capability that executes work at one or more lifecycle stages, such as Compass for discovery or Weld for engineering.
Governance gate
A point in the lifecycle where a person must approve before work moves on. There are five: intent, requirements, architecture, release and production.
Governed autonomy
Approval gates, permissions and policies decide what AI may do alone and what needs a human sign-off.
Living documentation
Specs, diagrams and tests that update as the system changes, so documentation never drifts behind the code.
Transformation Pod
A dedicated team of senior architects, engineers, AI and data specialists, powered by the Agentic SDLC, on a 12 to 36 month annual contract.
Two ways to use the platform.
Enterprise Transformation Pod
- What you get
- The platform delivered with pre-built solutions and Stack18 engineers, from strategy to production.
Self-serve Agentic SDLC
- Who it is for
- Product teams, service providers and engineering organizations. Join the waitlist for early access to the command center.
Agentic SDLC questions.
What is the Agentic SDLC?
The Agentic SDLC is Stack18’s AI-native software development lifecycle and management platform. It connects intent, requirements, design, code, testing, deployment and operations into one traceable lifecycle in which AI agents execute the work and people govern the decisions.
Is the Agentic SDLC an AI coding tool?
No. Coding is one stage. The platform covers intent, requirements, architecture, design, code, testing, deployment and operations, with governance across all of them.
How many AI agents are there, and what do they do?
There are ten specialised agents: Compass, Draft, Blueprint, Frame, Grid, Weld, Watch, Ledger, Launch and Pulse. Together they cover discovery, requirements, architecture, experience design, data and APIs, engineering, quality, documentation, release and monitoring.
Where do humans stay in control?
Teams define intent and constraints, and approve critical decisions at five governance gates. Nothing reaches production without the approvals you configure.
How is it different from a traditional agency or an AI coding tool?
Agencies deliver project by project with manual handoffs, and coding tools stop at the editor. The Agentic SDLC connects the whole lifecycle in one traceable system with governance built in.
Can it work with our existing repositories and pipelines?
Yes. The infrastructure layer is designed to connect to your Git, cloud, CI/CD, identity and observability tools, and the platform can be deployed on your own infrastructure.
Is the self-serve platform available?
Not yet. It is coming soon, with a waitlist. Enterprise engagements through the Enterprise Transformation Pod are available today.
Can we start with one project?
Yes. Many teams begin with a single product or modernization effort, then extend the approach as confidence grows.
Where to next.
Agentic SDLC
The command center for services, software and agents.
Explore →TrustSecurity & AI governance
How approvals, access and audit trails work in practice.
Read →EnterpriseTransformation Pod
The platform plus a senior team on a 12 to 36 month contract.
Explore →PricingHow we price
Fixed-price first steps and one-time solution prices in rupees.
See pricing →See it on your project.
Tell us where you are and where you want to be. A senior specialist will reply within one business day with next steps.
- Free 30-minute consultation
- Indicative estimate after the call
- NDA available on request