AI coding tools changed how developers work, but most organizations still struggle to turn personal AI gains into team-level impact. Tikal’s Agentic SDLC is a structured, outcome-driven solution for embedding AI into real software delivery. Operationalizing Tikal’s Twelve-Factor methodology and orchestrated by Harness,It enables engineering teams to move from scattered experimentation to a governed, repeatable, and measurable development system.
Agentic SDLC is Tikal’s end-to-end solution for operationalizing governed AI across engineering teams, based on Tikal’s Twelve-Factor Agentic SDLC methodology developed through hands-on work with engineering teams. It replaces ad-hoc prompting with a clear methodology, shared assets, and working habits that scale across teams. The journey typically starts with the Agentic SDLC Launchpad, a structured foundation phase that establishes shared workflows, governance, and core assets. As teams mature, the solution extends into the Agentic SDLC Subscription Program built on Harness, enabling continuous enterprise access, deeper pipeline orchestration, automated CI/CD quality gates, and organization-wide scale. For those interested in going deeper, the full Twelve-Factor Agentic SDLC methodology is available as a practical guide.
The Launchpad is built around a shared team-ai-directives repository, which is created during the engagement and serves as the single source of truth for how AI is used across the team. It captures rules, personas, examples, and shared context that guide consistent AI behavior and support the Agentic SDLC workflow inside developers’ existing IDEs. To operationalize this context inside daily workflows, we integrate Tikal’s open source agentic-sdlc-spec-kit CLI as an automated engineering harness. At scale, this framework seamlessly integrates into the enterprise Harness Platform, leveraging its powerful CI/CD pipelines, policy engines (OPA), and automated release gates to govern autonomous agents, LLM toolchains, and API gateways securely.
A governed, scalable AI development workflow embedded into real team delivery.
Developers remain accountable owners of architecture and quality, while AI acts as a fast, guided collaborator.
Every task starts with a clear, version-controlled Mission Brief instead of vague prompts.
Clear separation between sync collaboration for complex problems and async delegation for execution at scale.
Enforce code quality and security policies through automated Harness pipeline execution loops.
AI instructions become shared, versioned assets that evolve with the team.
Successful patterns are captured during delivery and fed back into the organization as reusable knowledge.
The Agentic SDLC Launchpad runs as a focused five-week process designed to establish a strong foundation for adopting Agentic SDLC across teams.
Adaptation (Week 1)
We assess current AI usage, friction points, and trust levels. Together we establish baseline metrics, adapt the methodology to your stack and create the initial team-ai-directives repository using real code scenarios.
(Week 2-3)
Three intensive hands-on sessions where teams practice the Agentic SDLC using customized exercises. Topics include Developer as Orchestrator, sync vs async execution, and Directives as Code.
(Weeks 4–5)
We work alongside your team during live sprints. Developers apply the methodology on real tasks while we mentor workflows and help capture successful solutions into shared assets.
(Week 6)
We measure improvement against the original baseline, validate adoption, and transfer ownership of the workflow, assets, and governance model to your internal AI lead, including a clear roadmap for scaling.
Once the Launchpad is complete, organizations can adopt Tikal's Harness-powered Agentic SDLC Platform to support deeper orchestration, governance, and scalable AI workflows across the organization.
Interested?
Let’s make sure AI is helping your teams move faster, not creating problems you’ll debug later. Schedule a consultation to build your Harness-powered Agentic SDLC foundation.
