The Most Powerful
Agentic IDE Ever Made

Greatcodestartswithgreatinformation.Methodturnsyourideasintotheexecutablesourceoftruthyourcodingagentdependson—nohallucinations,nodisconnectedcode.

Plan. Generate. Merge. Done.

IDE Mockup

OVERVIEW

Idea-to-Development Engine

The most important artifact is no longer the coding agent—it's the project specification. Write your intentions once, and watch as AI agents translate them into structured tasks, aligned code, and working features—with full traceability. Say what you want to build, Method makes it real.

Your specifications are the
source code.

AI Task Breakdown
Specification
Build AI-powered onboarding
35%
Detect user roles
In Progress
Parse user metadata
Match role patterns
Auto-draft flows
Pending
Generate step sequences
Create branching logic
Personalize CTA placement
Pending
Analyze user behavior
A/B test variations
Continuous Loop
Live
One Brain
Spec
Define intent
Code
Generate
Feedback
Learn & adapt
Context
Understand
Active Loops
247
+12 this hour
Learning Rate
3.2x
improvement/cycle

Defineonce,executeeverywhere

Writeyourproductspecificationswithclearsuccesscriteria.Methodunderstandsyourintentandautomaticallygeneratestheimplementationhierarchy—fromhigh-levelfeaturesdowntoatomictasks.

AIagentsmapintenttoarchitecture

OurAIagentsanalyzeyourcodebasestructureandtranslatespecificationsintoarchitecturally-alignedimplementations.Everylineofgeneratedcodetracesbacktoyouroriginalintent.

SPEC-DRIVEN AI

AI that builds with your intent

Properspecificationsletyoushipfasterandsafer.Ouragentsreasonoveryourspec,architecture,andcontext—generatingcodethataligns,adapts,andrespectsyoursystems.

Living Specification

Build AI-powered onboarding

35%

Detect user roles

In Progress

Auto-draft flows

Pending

Personalize CTA placement

Blocked: Needs Clarification

Implementation Flow
Request
→
AuthService
→
UserService
Personalize?
Yes ↓
Blocked
No ↓
Default CTA

AI Reasoning & Orchestration

Context Agent: Identified `Repository` pattern.

Trace: Seen in `user.service.ts`, `product.service.ts`.

Author: Last modified by `Sarah` (June 15).

Confidence: 95% - High

Routing Agent: Decided to use `Next.js` API routes.

Reasoning: Aligns with existing project structure in `/pages/api`.

Code Agent: Drafting `POST /api/onboarding/roles`

⚠️ Low confidence.

Spec-to-Code Trace:

Spec: "Detect User Roles"
 → Task: User Onboarding Flow
 → Decision: No conflicting endpoints
 → Code: POST /api/onboarding/roles

Orchestrator: Blocked on ambiguous logic.

Previously clarified to use **In-App Behavior** for CTA logic (June 21).

Orchestrator: Applying learned logic to unblock tasks.

One Brain, One Workspace

Planandbuildinthesameplace.PMsdefinespecswhiledevelopersseecodegenerateinreal-time.Oneunifiedbrainorchestrateseverything.

PM Specification
Define product intent
Live Code Generation
Real-time implementation
Developer Feedback
Continuous learning
Real-time Sync
All changes live

Continuous Feedback Loop

Everyinteractionimprovesthesystem.Codeadaptstochangingspecs,learnsfromfeedback,andevolveswithyourarchitecture—creatinganunstoppabledataflywheel.

Live Feedback Loop — Continuous Improvement

Active Feedback Loops

Spec changes triggering code regeneration
— 3 components updated based on new requirements
→ Auto-adapting to maintain spec alignment
Learning from developer feedback
— Patterns identified from 142 code reviews
→ Improving future generation accuracy

Data Flywheel Status

Unified Workspace Activity
Live: PM and 3 devs collaborating in real-time
Model Performance Improvement
97% spec-to-code accuracy (up 12% this week)

Fromplanningcalltoproductioncode.

Pattern Recognition → Code Generation → Feedback → Learning
Continuous Learning Cycle
1
Pattern Recognition
Analyzes codebase patterns and developer preferences
2
Code Generation
Creates code following team's established patterns
3
Developer Feedback
Captures edits and improvements made by developers
4
System Update
Integrates learnings to improve future generations
↻ Continuous: Each cycle improves accuracy by ~3%
Learning MetricsLive
Patterns Learned
1,247+142
Accuracy
97%↑12%
Recent Learnings
Auth patterns: Team prefers OAuth2 with JWT
Applied to 12 new implementations
API design: REST preferred for CRUD operations
98% accuracy in suggestions
Error handling: Consistent try-catch patterns
Reduced bugs by 34%

Continuous Learning Loop

Everyspecification,codegeneration,anddeveloperfeedbackimprovesthesystem.Yourteam'spatternsbecometheAI'sexpertise.

Unified Data Flow

Specsflowintocode,codegeneratesfeedback,feedbackrefinesspecs.Onecontinuousloopthatkeepseverythinginsync.

Compound Value Growth

Eachcyclestrengthenstheflywheel.Betterspecsleadtobettercode,whichcreatesbetterpatterns,whichgenerateevenbetterspecs.

One workspace. One brain. Everyone aligned.

PMs write specs while developers see code generate in real-time. Everyone works in the same place, with the same context, creating an unstoppable feedback loop.

PM Workspace

Write specs that instantly become code

Dev Workspace

See code generate as specs evolve

Real-time Sync

All changes instantly reflected everywhere

Feedback Loop

Every interaction improves the system

Team Alignment

Everyone sees the same truth

Data Flywheel

Each cycle makes the next better

Built for engineering teams

Enterprise security meets developer velocity. SOC 2 certified, self-hosted options, and your code never leaves your control.

Code-Aware AI

Understands your codebase and architecture patterns

Human-in-the-Loop

Engineers approve every PR before it ships

Self-Hosted Option

Run Method entirely within your infrastructure

The most intuitive single-loop way to build software.

Therealpowerliesinexpressingwhattobuildandwhy.