Codex CLI × PlanToCode

The architect builds blueprints. The construction crew executes.

PlanToCode completes Stages 1-4 (spec capture, file discovery, multi-model planning, human review). Codex CLI is Stage 5: taking the merged XML implementation plan and executing it with approval governance.

$5 free credits • Pay-as-you-go • Intelligence-Driven Development: Blueprint-first execution with monorepo-ready terminal workflows

Intelligence-Driven Development follows 5 stages: (1) Specification capture via voice/meetings/text, (2) Targeted file discovery using 4-stage FileFinderWorkflow, (3) Multi-model implementation planning across GPT-5.2/Claude Sonnet 4.5/Gemini, (4) Human review and plan merge with merge instructions, (5) Secure execution. Codex CLI is your Stage 5 construction crew—taking the merged implementation_plan XML blueprint and building it with approval governance.

What PlanToCode gives you here

Blueprint-first Codex runs

Stage 4 produces a merged implementation_plan XML with file-by-file edits, dependencies, and constraints. Stage 5 feeds this blueprint directly into Codex CLI for execution—no ambiguity, no surprises.

Approval modes as governance

Auto (workspace freedom, prompts outside scope), Read-Only (plan and chat only), Full Access (unrestricted). Choose the approval mode that matches your risk tolerance and team policy. The blueprint defines scope, Codex enforces boundaries.

File discovery ensures no-surprises changes

Stage 2 FileFinderWorkflow (root folder selection, regex file filter, AI relevance assessment, extended path finder) identifies every relevant file before planning. Stage 5 execution touches only what the blueprint declares—no stray edits.

Monorepo-ready terminal workflows

Run Codex CLI inside PlanToCode's integrated terminal. Navigate monorepo workspaces, execute build scripts, run migrations—all with persistent logs, health checks, and auto-reconnect. The terminal is Stage 5's execution environment.

Multi-model plan synthesis prevents blind spots

Stage 3 runs implementation_plan prompts across multiple models (GPT-5.2, Claude Sonnet 4.5, Gemini 3 Pro). Stage 4 merges their outputs with your merge instructions. Codex gets a comprehensive blueprint, not a single model's narrow perspective.

Skyscraper blueprint analogy

PlanToCode is the architect (Stages 1-4): capturing requirements, surveying the site (file discovery), drafting plans (multi-model), reviewing blueprints (merge). Codex CLI is the construction crew (Stage 5): building exactly what the blueprint specifies.

How it works with this tool

How to use Codex CLI with a merged implementation plan

Complete Stages 1-4 in PlanToCode: (1) Capture specification via voice/text using text_improvement and task_refinement prompts. (2) Run FileFinderWorkflow (root folder selection → regex file filter → AI relevance assessment → extended path finder) to discover all relevant files. (3) Generate multiple implementation plans using different models (GPT-5.2, Claude Sonnet 4.5, Gemini 3 Pro) via the implementation_plan prompt. (4) Review plans side-by-side, write merge instructions, run implementation_plan_merge to produce a single XML blueprint.

Stage 5: Feeding the blueprint to Codex CLI

Open PlanToCode's integrated terminal, navigate to your repo root, start Codex CLI. Paste the merged implementation_plan XML into Codex as context. The XML contains file-by-file edits (add/modify/delete), dependencies, rollback instructions, and constraints. Codex treats this as the execution specification—no improvisation, no scope creep.

Approval modes as risk governance

Auto (default): Codex can read/edit/run inside the working directory without prompting; asks before leaving workspace or using network. Read-Only: Plan and chat only—no edits or command execution. Full Access: Edits + commands (incl. network) without approval. Use only when policy allows. Configure via /approvals in Codex UI or CLI flags. The blueprint defines scope, approval mode enforces boundaries.

Real-world scenario: Database migration with schema changes

Stage 1: "Add user_preferences table with JSONB column, migrate existing settings from user_settings." Stage 2: FileFinderWorkflow discovers migrations folder, models, API routes, tests. Stage 3: Generate plans with GPT-5.2 and Gemini 3 Pro—each brings a different perspective. Stage 4: Merge with instruction "Prioritize GPT-5.2 rollback strategy, use Gemini data validation." Stage 5: Codex executes migration, updates models, runs tests—all from the merged blueprint.

Monorepo workflows and build orchestration

PlanToCode terminal supports WSL, persistent sessions, health checks. Run Codex in backend/, then switch to frontend/. The merged plan declares cross-package dependencies—Codex follows them. Terminal logs every step. If Codex crashes, terminal auto-reconnects; resume from last checkpoint.

Model selection and Windows compatibility

Codex CLI defaults to GPT-5.2; switch to GPT-5.2-Codex via /model or --model gpt-5-codex. Windows users: WSL recommended for best CLI compatibility. PlanToCode detects WSL environments and preserves paths across Windows/Linux boundaries.

Quick start

Stage 1-2: Capture spec and discover files
Stage 3: Generate multi-model plans
Stage 4: Merge with human guidance
Stage 5: Execute in Codex with approvals

Learn more:Codex CLI·Approval modes

Verified from official sources

Codex CLI is OpenAI's official command-line tool for AI-assisted coding.

Official docs

Codex CLI offers three approval modes: Auto (default - workspace freedom with approval outside), Read-Only (requires approval for all actions), and Full Access (no approvals).

Official docs

Windows users should run Codex CLI in WSL2 for correct sandboxing and performance.

Official docs

Codex CLI defaults to GPT-5.2. Users can switch to GPT-5.2-Codex via the /model command or --model flag.

Official docs

Approval modes can be configured using the /approvals command or CLI flags.

Official docs

Codex CLI supports multiple models and usage patterns.

Official docs

WSL getting started guide is available for Windows users.

Official docs

Frequently Asked Questions

Everything you need to know about PlanToCode

Yes. PlanToCode provides a human-in-the-loop workflow where team leads and stakeholders can review generated implementation plans, edit details, request modifications, and approve changes before they are executed by coding agents or developers. This ensures corporate governance and prevents regressions.

Upload Microsoft Teams meeting recordings or screen captures to PlanToCode. Advanced multimodal models analyze both audio transcripts (including speaker identification) and visual content (shared screens, documents) to extract specification requirements. You review the extracted insights - decisions, action items, discussion points - and incorporate them into implementation plans.

Yes. Implementation plans break down changes on a file-by-file basis with exact repository paths corresponding to your project structure. This granular approach ensures you know exactly what will be modified before execution, providing complete visibility and control.

PlanToCode is a desktop planning workspace. You run the file discovery workflow, review implementation plans in a Monaco editor, adjust prompts, and then launch the terminal from the same session. Chat tools hand you a single reply; here you stage the work before anything runs.

Yes. The app assumes you already work in large repositories and are comfortable with terminals, dependency graphs, and architecture trade-offs. The software keeps context organized so you can apply your judgment faster.

The default configuration ships with Gemini 3 Pro, GPT-5.2, Claude 4.5 Sonnet, o3, Grok 4, DeepSeek R1, and Kimi K2. You can switch models per task from the settings panel before submitting a job.

Project state, terminal logs, and plan drafts are stored locally in SQLite. Only the prompt you approve plus the files you select are sent through your configured server proxy. The Rust server in this repo can be self-hosted when you need to keep traffic on your own infrastructure.

The terminal boots the same shell you use on the host machine and auto-detects claude, cursor, codex, and gemini binaries. You can still run any other tooling manually - the PTY session is a regular shell with voice dictation available when you need hands-free input.

Start the file finder workflow to generate search patterns, relevance scoring, and prioritized file lists. Each stage runs as its own background job so you can inspect results before applying the selections to your session.

Absolutely. Plans open in a Monaco editor with syntax highlighting, diff-friendly formatting, and clipboard helpers. You can tweak the prompt, copy individual steps, and rerun generation without leaving the workspace.

Select two or more plans, write the merge guidance, and submit. The merged result is saved alongside the originals so you can compare drafts, keep notes, or rerun the merge with different instructions.

Token estimates, prompt previews, terminal health monitoring, and persistent sessions reduce rework. You decide when to run commands and which model to trust, while the app handles orchestration details.

Describe the task (typing or voice) → run the file finder workflow → generate one or more implementation plans → edit or merge plans in the Monaco editor → launch the built-in terminal to execute the plan and monitor logs. Sessions and logs stay available the next time you open the app.

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