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Capgemini Team 1 (Codex Morph)

Global Codex Hackathon: [London]
Both, Modernisation and MVP to production work often stalls before delivery begins because teams do not have a clear, shared view of what already exists. Legacy systems, internal tools, and early-stage prototypes are usually under-documented, inconsistently structured, and difficult to reason about at scale. Teams lose weeks reverse-engineering architecture, dependencies, risks, and migration options before they can even agree on a plan. This project removes that bottleneck. It uses Codex to analyse large codebases, maintain working context across multiple files and planning stages, and convert that analysis into a structured transformation blueprint. Instead of starting with scattered tribal knowledge and manual discovery, teams get an evidence-backed current state, target state, phased roadmap, risks, and next actions. For internal partner teams, that means faster discovery, clearer technical alignment, better handoffs, and a reusable accelerator for transformation engagements./…

Our Project - Codex Morph is a Codex-powered legacy/POC discovery and transformation planning workflow that turns a codebase into a structured, developer-ready modernisation plan in minutes. The product is built as a guided Next.js workspace with a multi-agent planning engine behind it. A user submits a codebase and transformation brief, Codex analyses the system, asks targeted clarification questions, orchestrates specialist section agents, and produces a reviewable transformation output covering architecture, migration strategy, security, CI/CD, testing, integration, product planning, and publish-ready documentation. What makes the approach strong is that Codex is not used as a one-off assistant. It is the workflow engine. It handles large codebase analysis, maintains context across multiple planning stages, and uses compaction patterns to preserve context for later iterations. Each run persists local Markdown artifacts such as shared run context, per-agent `context.md`, and `output.md` files so the system can rehydrate only the relevant context on reruns instead of starting from scratch. That makes the workflow more reliable, iterative, and reusable across delivery engagements. Key features: - Codebase intake from GitHub URL, ZIP upload, or local folder - Guided clarification flow before planning starts - Multi-agent planning orchestration using the Agents SDK - Specialist section agents for architecture, migration, infrastructure, security, testing, database, integrations, and product delivery - Local artifact generation for context persistence and future iteration - Human-in-the-loop review, section updates, and targeted reruns - Publish-ready outputs including hosted report views and structured export paths This is designed as a reusable accelerator, not a one-off demo. The workflow can be applied to different codebases, different transformation briefs, and different partner scenarios with the same structure: - Intake - Clarification - Multi-agent analysis - Review - Publish Because context persisted in local artifacts and outputs are modular by section, the system is well suited to repeated use across discovery engagements, internal accelerators, and future productisation. It can evolve into a partner-facing modernisation assessment tool, an internal engineering accelerator, or a pre-sales and delivery discovery workflow.

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