AI-native SDLC Platform
Built an enterprise AI-powered platform that automates and accelerates the full software development lifecycle using intelligent agents. The platform enables project teams to orchestrate specialized AI agents across SDLC phases - discovery, planning, UX, development, and quality assurance. At its core is an autonomous coding agent pipeline that ingests tickets from project management tools, classifies them via LLM-based triage, schedules multi-step workflows, and executes implementation using AI backends (OpenAI Codex, Anthropic Claude) inside hardened, rootless containers with supply-chain attestations. We developed a curated knowledge base and Model Context Protocol (MCP) server providing agents with discoverable, faceted SDLC guidance, and built a cross-product integration layer establishing unified project identity and deep-link navigation across multiple internal accelerator tools with event-driven artifact exchange and RBAC.
Project Details
Client
PwC
Industry
AI Engineering
Location
Prague, Czech Republic
Services
AI Engineering, Platform Architecture, Full-stack Development, DevOps, Developer Experience
Challenge
To build an enterprise-grade AI platform that doesn't just assist developers but autonomously drives the full SDLC - orchestrating specialized agents across discovery, planning, coding, QA, and delivery - while integrating with enterprise identity, security tooling, and existing accelerator products in a regulated corporate environment.
Solution
Designed and delivered a full-stack AI agent platform with an autonomous coding agent pipeline that ingests tickets, classifies them via LLM triage, and executes implementation in hardened containers. Built a curated MCP knowledge base for context-aware agent behavior, a cross-product integration layer with unified project identity, and a developer tooling stack orchestrating MCP servers for consistent local environments. Shipped MCP-native IDE integration and integrated Azure Entra ID, SharePoint, and static analysis tooling into unified agent workflows.
Results
- Full-stack AI agent platform orchestrating specialized agents across all SDLC phases
- Autonomous coding agent pipeline with LLM-based triage and multi-step workflow execution
- Hardened, rootless Podman containers with supply-chain attestations for secure code execution
- Curated MCP knowledge base providing discoverable SDLC guidance for context-aware agent behavior
- Cross-product integration layer with unified project identity, deep-link navigation, and event-driven artifact exchange
- Docker Compose-based developer tooling stack with MCP servers for source control, project management, static analysis, and browser automation
- MCP-native IDE integration exposing full platform API to AI coding assistants
- Enterprise system integrations: Azure Entra ID (SSO/RBAC), SharePoint, and application security tooling