Autocraft Documentation

1. Introduction

Autocraft is an AI-powered software engineering environment that transforms natural language instructions into fully structured, production-ready Next.js applications. Unlike traditional AI code tools, Autocraft behaves like a full engineering pipeline, interpreting requirements, generating code, validating correctness, repairing issues, running real previews, and deploying to production automatically.

The platform integrates a multi-agent GPT-5 architecture, a continuous self-healing system, code-aware RAG memory, and zero-configuration Vercel deployment. Together, these components create a deterministic and enterprise-ready development workflow where builds are stable, predictable, and safe across iterations.

Autocraft is engineered for reliability, scalability, and long-term maintainability, making it suitable for startups, teams, and enterprise environments requiring consistent code quality and automated DevOps pipelines.

• Clean, maintainable Next.js 15 codebases
  Generated outputs follow modern RSC patterns, App Router conventions, and strict TypeScript.
• Component-driven architecture
  UI/UX is decomposed into reusable, isolated components that match real engineering best practices.
• Secure sandbox preview runtime
  All builds run in isolated virtual machines, ensuring safe rendering and accurate runtime behavior.
• Persistent project memory
  Autocraft stores and retrieves project context using conversation memory and vector-indexed code RAG.
• One-click deployment
  Integrated Vercel deployments allow any project to go live globally in seconds, no GitHub or setup required.

2. Input Understanding, From Idea → Structured Specification

Autocraft is designed to understand user intent at multiple levels, natural language, visual inputs, contextual cues, and historical project memory. The system transforms ambiguous instructions into a structured engineering specification that the code agent can execute reliably and deterministically.

2.1 Natural Language Input

Autocraft accepts any high-level idea, from vague concepts to detailed technical requirements. The system interprets user intent and translates it into actionable engineering constraints.

“Build a SaaS landing page with pricing, authentication, dark mode, and a dashboard.”

Whether the user is a beginner or an experienced engineer, Autocraft automatically infers structure, component boundaries, and architectural patterns from natural language alone.

2.2 Prompt Clarity Engine

Before generating any code, Autocraft validates the clarity and completeness of the prompt. If essential details are missing, it automatically asks targeted clarification questions ensuring the build starts with an unambiguous, developer-grade specification.

• Detects vague or underspecified requirements
• Identifies missing sections, behaviors, or components
• Resolves unclear design decisions or layout preferences
• Prevents invalid or incomplete builds before they start

This creates a predictable development pipeline and eliminates guesswork for the AI system.

2.3 Prompt Enhancement System

For users who prefer minimal descriptions, Autocraft includes an AI-powered Prompt Enhancement System that automatically upgrades raw ideas into structured, production-ready engineering briefs.

• Expands vague ideas into detailed specs
• Defines UI/UX components and layout hierarchy
• Adds missing functional requirements
• Normalizes styling systems (spacing, color schemes, typography)
• Ensures the code agent receives clear, explicit instructions

This feature enables non-technical users to generate professional-grade applications without needing prior experience in prompt engineering or software design.

2.4 Image-Assisted Understanding

Autocraft supports image uploads to strengthen context comprehension. Users can upload:

• UI screenshots
• Wireframes or sketched layouts
• Figma exports
• Design references or inspirational UIs

Powered by GPT-5 Vision models, Autocraft extracts structural and visual semantics from the image including layout hierarchy, spacing, color palettes, typography, and component architecture. This context is fused with the user’s textual instructions to generate highly faithful UI implementations.

Image-assisted understanding makes Autocraft suitable for designers, founders, agencies, and anyone who wants pixel-aligned output based on visual references.

3. Memory Layer: Autocraft’s Dual-Engine Knowledge System

Autocraft maintains a persistent understanding of your project using two independent yet complementary memory systems. Together, they allow the platform to generate changes safely, avoid regressions, and behave like a real software engineer who remembers everything previously built.

3.1 Short-Term Contextual Memory

Autocraft maintains conversation-level memory across your recent messages. This enables natural, incremental development where you can iteratively refine or extend the project without repeating previous instructions.

• Understands ongoing edits to the current session
• Tracks stylistic preferences and recent changes
• Allows incremental updates (“make the hero section larger”)
• Supports conversational refinement without losing context

This short-term layer behaves like a product engineer following your real-time feedback, enabling smooth, iterative build cycles.

3.2 Long-Term RAG Code Memory (Vectorized Project Understanding)

Beyond conversational awareness, Autocraft maintains a deep, persistent understanding of your entire project using a Retrieval-Augmented Generation (RAG) pipeline. Every file generated across all build iterations is tokenized, vector-embedded, and indexed for long-term retrieval.

• Each file is embedded into a high-dimensional vector space
• Autocraft retrieves the most relevant files on every new instruction
• Prevents overwriting or corrupting unrelated parts of the project
• Ensures continuity across days, weeks, or months of development
• Maintains architectural consistency as the project grows

This long-term memory layer eliminates the most common failures of traditional AI code generators such as missing imports, lost components, accidental rewrites, or structural inconsistencies.

Combined, Autocraft’s short-term and long-term memory systems create a development environment where the AI truly understands your project, making it capable of maintaining large, evolving codebases with stability and precision.

4. Code Generation Engine GPT-5 Multi-Agent Orchestration

Autocraft’s core generation pipeline is powered by a hardened GPT-5 multi-agent system architected specifically for stable, incremental Next.js development. The engine operates under strict constraints to ensure predictable, maintainable, and production-ready output avoiding the instability common in generic AI code generators.

Instead of generating an entire app in a single pass, Autocraft usestask-scoped agents with file-level isolation, enabling precise modifications without affecting unrelated parts of the codebase.

4.1 Framework-Native Code Generation

The engine is fully aligned with modern web engineering standards and generates code that adheres to best practices across:

• Next.js 15 App Router (app/ directory architecture)
• React Server & Client Component boundaries
• Tailwind CSS utility-driven styling
• shadcn/ui component patterns
• TypeScript strict mode with predictable types

4.2 Deterministic Output Constraints

Every agent in the system operates under strict guardrails, ensuring that Autocraft does not produce ambiguous, unstable, or incomplete code. These enforced rules include:

• No full-project rewrites: only targeted file updates
• Strict TSX validity: ensured before preview builds
• “use client” directive enforced at correct boundaries
• Deterministic folder structure: no random file placement
• Imports aligned with real file paths
• Zero duplicated React imports or unused variables

These constraints make Autocraft’s output predictable and production-safe, even as project complexity grows.

4.3 Multi-Agent Coordination

Multiple lightweight GPT-5 agents collaborate behind the scenes, each specializing in a specific action:

• Planning Agent: interprets intent and identifies required files
• Code Agent: generates and updates TSX/TS code
• Validation Agent: checks structural and semantic correctness
• Response Agent: summarizes changes in human-readable form

This division of responsibility reduces hallucination rates and ensures high-fidelity code generation aligned with actual engineering workflows.

4.4 Built-In Hardening Pipeline

Before any preview is rendered, all generated code passes through Autocraft’s multi-layer hardening system:

• TypeScript compiler simulation
• Import graph validation
• React hydration error simulation
• Symbol integrity scanning
• Forbidden pattern detection (e.g., invalid Next.js API usage)

These layers ensure that every build is structurally sound, reducing runtime failures and improving reliability during rapid iteration.

4.5 Safety & Reliability Guarantees

• No deletion of unrelated files
• No regeneration of the entire project unless explicitly requested
• No unsafe file mutations
• No overwriting of user-created structures
• All changes scoped and reversible through project history

Together, these constraints ensure Autocraft behaves like a senior engineer making deliberate, controlled changes with full awareness of the existing system.

5. Preflight Validation Layer

Before any generated code is merged into a user’s project, Autocraft executes an extensive preflight validation sequence. This layer acts as the first line of defense against malformed output, ensuring that only structurally correct and build-safe code proceeds to the sandbox stage.

5.1 What the Preflight Layer Validates

Preflight evaluates both the project structureand the latest AI-generated changes, detecting any conditions that could cause compile-time or runtime failure.

• Required Next.js files: Ensuresapp/layout.tsxand app/page.tsx exist.
• Missing imports: Detects undefined components or modules and flags them for auto-creation.
• Invalid JSX/TSX patterns:Unclosed tags, incorrect return statements, or invalid syntax.
• Alias inconsistencies:Ensures @/ imports resolve to valid POSIX file paths.
• Config presence:Validates Tailwind, PostCSS, TSConfig, and Next.js config files to prevent build-time failures.

5.2 Advanced Structural Validation

Beyond simple file checks, Autocraft performs deeper project-wide validation to ensure the generated code integrates safely with the existing architecture.

• Import Graph Consistency: Ensures that every referenced file exists and maps to a real component.
• Reserved Next.js conventions:Detects invalid usage of server/client boundary APIs.
• Duplicate file detection:Prevents unexpected overrides or name collisions.
• Symbol existence:Warns when imports reference missing exports or invalid identifiers.
• Invalid folder patterns:Protects against incorrectly placed pages, components, or route handlers.

5.3 Preventing Build-Time Failure

Any detected issues are transformed into explicit instructions for the GPT-5 agent to fix before attempting a sandbox build. This ensures the system preemptively resolves problems instead of allowing broken code to propagate into the preview runtime.

• Rewrite invalid imports or file paths
• Auto-create missing components or stubs
• Insert missing layout/page files
• Repair malformed TSX/JSX
• Normalize directory structures

5.4 Result: A Verified, Build-Safe Codebase

Only after a project fully passes the preflight validation layer does Autocraft proceed to:

• Merge changes into the persistent codebase
• Initiate self-healing routines
• Spin up the sandbox preview environment

This guarantees that nearly all avoidable errors are resolved long before the application reaches the preview or deployment stage.

6. Auto-Healing Engine

Autocraft includes a fully autonomous self-repair system that continuously analyzes and corrects AI-generated code. This engine operates before, during, and after the sandbox build, ensuring that unstable or incomplete output never compromises the project.

The Auto-Healing Engine is designed to eliminate the most common sources of AI-generated runtime or compile-time failures by repairing structural, syntactic, and dependency-level inconsistencies automatically.

6.1 What the Auto-Healing Engine Fixes

• Missing “use client” directives:Ensures correct client/server boundaries in Next.js 15.
• Broken or incomplete JSX/TSX:Unclosed tags, invalid fragments, malformed return blocks, improper component signatures.
• Missing imports or missing components:Automatically generates minimal placeholder components to preserve application stability.
• Invalid React boundaries:Detects and corrects hydration issues, forbidden API usage, or incorrect component structure.
• Auto-placeholder generation:If a referenced component does not exist, Autocraft synthesizes a safe stub component.
• Missing NPM modules:Automatically detected and installed inside the sandbox environment.
• Corrupted file outputs:Fixes cases where outputs appear as [object Object] or other malformed objects.
• Invalid alias imports:Resolves @/ paths into safe POSIX-resolved paths.
• Duplicate React imports or wrong imports:Normalizes import blocks to prevent runtime crashes.

6.2 Static + Dynamic Healing Pipeline

Autocraft’s healing system runs across multiple layers, each responsible for catching and repairing a different class of error.

• Static Syntax Repair:Fixes JSX, TSX, imports, React component signatures, and structural directives.
• TypeScript Compiler Simulation:Runs a lightweight TS compiler pass to detect missing exports, wrong types, or unresolved imports.
• Symbol Scanner:Ensures that referenced identifiers actually exist in their target modules.
• Hydration Simulation:Detects common client-side hydration issues before the browser does.
• Output Policy Enforcement:Prevents forbidden patterns such as invalid Dialog primitives or unsafe external image usage.

6.3 Intelligent Placeholder Component Generation

When Autocraft detects that an imported component does not exist, it automatically generates a safe placeholder including named exports when required ensuring uninterrupted rendering and avoiding runtime crashes.

These placeholders remain visible in preview until replaced by a proper implementation, providing clear feedback without breaking the build.

6.4 Dependency-Level Healing

During sandbox execution, Autocraft monitors for missing NPM packages. When detected, it installs them automatically and retries the build without requiring user intervention.

• UI libraries (e.g., shadcn/ui primitives)
• Utility packages
• Third-party integrations

This ensures the preview environment always has the dependencies needed to run the generated application.

6.5 Result: A Self-Stabilizing Development Workflow

The Auto-Healing Engine prevents more than 95% of typical AI coding errors from ever reaching end users. Instead of breaking previews, the system continuously repairs the project until a valid, stable, build-ready codebase is produced.

This makes Autocraft uniquely reliable compared to traditional AI code generators, which tend to degrade project stability over time.

7. Hardening Pipeline

Before code reaches the sandbox or deployment stage, Autocraft passes every generated file through a multi-stage Hardening Pipeline. This pipeline simulates how a real engineering team would validate a codebase catching structural, syntactic, and runtime issues early while enforcing Next.js architectural correctness.

7.1 Multi-Layer Validation System

The Hardening Pipeline ensures code quality through layered checks that detect and repair potential issues before the preview build runs.

• Simulated TypeScript checks:Ensures all components, exports, imports, and types are structurally valid even without running a full compiler inside the sandbox.
• Hydration boundary scanning:Detects potential server/client component mismatches, invalid hooks usage, and improper “use client” placement that would otherwise cause hydration failures in Next.js.
• Symbol-level validation:Identifies missing exports, incorrect identifiers, invalid module references, and non-existent component imports before runtime.
• Alias and path normalization:Rewrites brittle or incorrect imports (e.g., @/src/…) into safe, resolved POSIX paths.
• API usage enforcement:Removes or patches unsupported patterns such as Dialog.Overlay, unsafe next/image usage, or deprecated primitives.

7.2 Inference-Based Structural Repairs

The Hardening Pipeline uses semantic inference and contextual analysis to guess developer intent and repair code automatically before it causes failures.

• Auto-detection of missing React imports or Next.js primitives
• Automatic insertion of safe default exports when a file structure is incomplete
• Correction of malformed JSX return blocks using tree reconstruction heuristics
• Smart rewriting of incorrectly nested components
• Patch suggestion engine that rewrites only the broken portions of a file

7.3 Preview Stability Guards

Before code is passed to the sandbox, the hardening layer applies several safety guards to ensure the preview always loads even if the generated code contains severe structural issues.

• Detection of missing root layouts, pages, or routing hierarchy
• Automatic fallback component injection to prevent blank-screen failures
• Static HTML wrapper checks for structural HTML errors
• Enforcement of Next.js project shape (e.g., app/layout.tsx and app/page.tsx)

7.4 Result: Enterprise-Grade Resilience

This Hardening Pipeline ensures that Autocraft never produces fragile, unstructured, or non-functional Next.js code. Combined with the Auto-Healing Engine, it forms a dual-layer stability system that dramatically reduces the chance of runtime failures, undefined components, or invalid imports.

The result is a build process that is predictable, safe, and engineered for production matching the expectations of professional teams and enterprise workflows.

8. Deterministic File Governance & Normalization

Autocraft enforces a deterministic, stable, and fully normalized file system to ensure that projects remain predictable across builds, updates, and multi-step conversations. This governance layer prevents structural drift, inconsistent imports, brittle paths, and malformed file contents ensuring that the project’s integrity is preserved at all times.

8.1 Canonical Path & Structure Normalization

Autocraft rewrites and standardizes every file path before saving or executing code. This ensures consistency across Windows, Mac, Linux, and the sandbox VM runtime.

• POSIX path enforcement:Converts all paths to forward-slash, canonical POSIX format for universal compatibility.
• Automatic directory creation:Missing parent folders are created deterministically to prevent partial file writes or failures.
• Alias resolution:Rewrites brittle imports such as @/src/… into proper stable paths (e.g., app/…), avoiding broken imports in Next.js.
• Flattened normalization:Removes double slashes, trailing slashes, and inconsistent casing.

8.2 File Content Sanitization

To protect the project from invalid or corrupted values generated by the model, Autocraft enforces multiple sanitization layers on all TSX/JSX, JSON, and text files.

• Removal of [object Object] corruption
• Detection of non-code blobs that resemble JSON or plain text
• Safe fallback replacement for invalid TSX
• Whitespace and formatting normalization
• Strip accidental BOM characters and control sequences

Invalid TSX or orphaned components are replaced with a stable, sandbox-safe placeholder component to preserve build integrity.

8.3 Deterministic Safe-Merge System

When Autocraft modifies existing files, it uses a deterministic merge strategy that ensures only the intended sections are updated never the entire file.

• Change locality preservation, updates are isolated to the diffed region.
• No destructive overrides, unrelated code is never removed.
• Safe insertions, new sections are added without breaking existing logic.
• Merge conflict prevention, structural heuristics avoid ambiguous edits.
• Guaranteed idempotence, applying the same update twice yields the same output.

8.4 Missing Component & Placeholder Generation

If the generated code references a component, layout, or hook that does not exist, Autocraft automatically generates a safe placeholder file. This prevents runtime crashes and allows the preview to continue functioning while the agent resolves the missing piece in the next cycle.

• Auto-created component stubs
• Stable default exports
• Minimal JSX ensuring hydration safety
• Clear developer-facing placeholder messaging

8.5 Result: Predictable, Enterprise-Grade Stability

This deterministic file governance system ensures that Autocraft behaves like a disciplined engineering team, maintaining consistent structure, predictable patterns, and clean project organization across the entire development lifecycle.

The result is a codebase that remains stable across multiple builds, messages, and iterations, a requirement for enterprise environments where reproducibility and consistency are critical.

9. Sandbox Runtime (Secure Virtual Machine)

Once Autocraft completes preflight validation, healing, and structural normalization, the project is executed inside a secure, isolated virtual machine. This sandbox environment runs a real Next.js development server with full runtime simulation enabling accurate previews, reliable error detection, and predictable deployment behavior.

9.1 What the Sandbox Does

The sandbox mirrors a real-world Next.js runtime. It is not a mock, preview renderer, or partial compiler. It is a fully functional environment capable of reproducing actual production behavior.

• Automatic dependency installation:Any missing NPM modules are detected and installed on the fly before server startup.
• Real Next.js dev server execution:Ensures hydration behavior, routing, layouts, and metadata work as expected.
• Hydration boundary validation:Autocraft monitors React hydration logs to detect mismatches and structural defects.
• Automatic asset bundling:Images, fonts, and static assets are processed as they would be in a real project.
• Live error streaming:Build logs and runtime errors are streamed back to Autocraft for self-healing analysis.
• Fully isolated execution:Code runs in a containment sandbox, never touching real user files or servers.
• 30-minute VM lifespan:Each sandbox persists for 30 minutes, after which it automatically shuts down.

9.2 Safe Fallback Runtime

If the sandbox fails to compile due to missing components, invalid imports, or unexpected runtime errors. Autocraft injects a Safe Fallback Page.

This fallback guarantees that your preview interface always loads, even when the underlying Next.js build does not. You will never see a broken preview, white screen, or framework crash.

• Displays stable diagnostics instead of failing silently
• Ensures UI visibility regardless of build status
• Allows live iteration even when errors exist
• Integrates with the Auto-Healing Engine for next-pass repair

9.3 Sandbox Session Lifecycle

• VM is initialized
• Files are normalized & written into the filesystem
• Missing dependencies are automatically installed
• Next.js dev server is launched
• Sandbox-host URL is returned to the UI
• Live rebuild & error streaming continue for 30 minutes

After expiration, all state is destroyed but your project remains permanently saved in Autocraft’s storage. You can reopen the project and generate a fresh sandbox at any time.

The sandbox runtime provides Autocraft with a production-accurate execution environment, enabling reliable previews, real-time debugging, and confident deployment with complete isolation and zero risk to your underlying project files.

10. Project Persistence, History & Versioning

Autocraft preserves every step of your build process using a combination of fragment storage, full-project snapshots, and long-term vector embeddings. This creates a reliable, versioned development timeline that can be restored, analyzed, or continued at any time.

10.1 Full Project Snapshots

After each build cycle, Autocraft saves a complete snapshot of your project’s file system. This ensures that no work is lost and every version remains recoverable.

• All TSX, TS, layout, and component files
• Configs (tailwind, tsconfig, next.config)
• Public assets and generated directories
• Sanitized + normalized file contents

Snapshots allow Autocraft to behave like a persistent development workspace rather than a stateless code generator.

10.2 Project Fragments (Build Records)

Every build request produces a fragment a timestamped record containing:

• The AI response summary
• Generated or updated files
• The sandbox preview URL
• A human-readable fragment title
• Differential file changes

Fragments form a chronological history of the project, similar to commits in a Git repository but automatically created.

10.3 Past Preview Storage

Even after a sandbox expires, Autocraft stores metadata about your past previews: component state, structure, and code relationships. This enables:

• Re-opening old versions
• Inspecting how the UI evolved
• Understanding incremental changes

Previews are ephemeral, but their structure is permanently recorded.

10.4 RAG Code Embeddings (Long-Term Memory)

Each generated file is converted into a vector embedding and indexed in Autocraft’s Retrieval-Augmented Generation (RAG) system. On every new instruction, Autocraft retrieves the most semantically relevant files without relying on guesswork.

• Prevents overwriting existing components
• Ensures correct imports & relationships
• Restores architectural consistency
• Maintains project identity over time

This gives Autocraft long-term project awareness and something no traditional AI coding system offers.

10.5 Permanent Versioned Storage

Your entire project timeline is stored persistently. You can:

• Return to any previous state
• Download any version
• Continue development from any fragment
• Maintain long-running, multi-week projects

Autocraft behaves like a continuously versioned IDE but with AI-native tooling designed for collaborative, incremental code generation.

Together, snapshots, fragments, preview metadata, and RAG embeddings form acomplete, enterprise-grade project history systemthat guarantees stability and continuity throughout the entire development lifecycle.

11. Deployment Pipeline, Zero-Config, Production-Grade

Autocraft provides a fully automated deployment pipeline powered by the Vercel Deployments API. No GitHub repositories, no manual builds, and no command-line steps are required. Autocraft handles everything from packaging to global delivery.

11.1 End-to-End Automated Deployment

When you click Deploy, Autocraft performs a complete CI/CD workflow behind the scenes:

• Prepares and bundles your full Next.js project
• Uploads files to Vercel using a secure API channel
• Triggers a cloud build using Vercel’s native infrastructure
• Optimizes assets, routes, and static files
• Rolls out your application to the global CDN

The entire process is seamless and requires no external tooling.

11.2 Framework Auto-Detection & Build Orchestration

Vercel automatically detects that your project is a Next.js 15 application and applies the correct build settings. This includes:

• Next.js server and client routing configuration
• Turbopack / SWC-based compilation
• Static file optimization
• Edge runtime assignment (where applicable)
• Environment awareness and output verification

No manual configuration files or build commands are required on your side.

11.3 Deployment Safety & Validation Guarantees

Autocraft ensures that only validated and hardened code is deployed. Your deployment is blocked if the project fails:

• Static structure validation
• TypeScript simulation checks
• Hydration compatibility checks
• File sanitation & placeholder resolution
• Missing dependency and import validation

This guarantee prevents broken deployments and preserves production stability.

11.4 Deployment Output & Environment

Once deployment succeeds, Autocraft returns a full set of production artifacts:

• Public production URL
• Preview deployment links
• Deployment metadata (build logs, status)
• Automatic CDN caching for global delivery

Applications deploy globally within seconds and remain available regardless of sandbox session expiration.

11.5 Domain Management & Custom URLs

Autocraft and Vercel work together to support multiple domain workflows:

• Auto-generated project subdomains
• Optional custom domain linking
• HTTPS certificate provisioning (handled by Vercel)
• Instant redeployments via incremental builds

11.6 Zero-Config CI/CD Philosophy

Unlike traditional pipelines, Autocraft does not require:

• GitHub repositories
• Dockerfiles
• Manual environment setup
• Local builds
• CLI commands

Everything is managed inside Autocraft’s infrastructure and deployed directly to Vercel’s global edge network.

Together, these systems create a frictionless, production-ready deployment pipeline that allows startups, designers, and engineers to ship applications in seconds without touching DevOps tooling.

12. Credit System: Transparent, Predictable & Team-Ready

Autocraft uses a simple and deterministic billing model designed for both individuals and engineering teams. Instead of unpredictable token usage, Autocraft charges per action, ensuring clear cost expectations and zero hidden consumption.

12.1 Core Billing Model

The billing unit is intentionally simple:

✔ 1 message = 1 credit

A “message” includes:

• Build requests
• Feature modifications
• Bug-fix instructions (e.g., “Fix the issues”)
• Prompt enhancement requests
• Image-assisted instructions
• Iterative refinement messages

Credits are consumed only when the Autocraft agent processes your request.

12.2 Actions That Do Not Consume Credits

Autocraft does not charge for administrative or non-generative actions:

• Deployment to Vercel
• Downloading your project
• Opening or loading a project
• Viewing sandbox previews
• Browsing the file explorer
• Renaming or deleting projects

Credits are used exclusively for AI-driven operations.

12.3 Monthly Reset Policy

• Credits reset on your monthly billing date
• Unused credits do not roll over to the next month
• Your active subscription tier determines available monthly credits

This reset model ensures stable usage patterns and prevents credit hoarding or long-term imbalances.

12.4 Enterprise & Team Credit Allocation

For organizations, Autocraft supports tier-based account limits and shared credit pools. Features include:

• Unified team billing
• Shared or segmented credit pools
• Usage analytics & reporting
• Role-based permissions
• Optional monthly overage protection

12.5 Why Autocraft Uses a Credit System

Token-based billing is unpredictable. Costs grow with:

• Longer prompts
• Larger project context
• Model complexity
• RAG expansion
• Image inputs

The credit model shields users from this unpredictability, offering:

• Predictable monthly costs
• Stable budgeting for companies
• No surprise token spikes
• Simple and intuitive usage measurement

In short, Autocraft’s credit system is designed to be transparent, scalable, and enterprise-aligned, allowing users and teams to focus on building not on managing complex billing mechanics.

13. Error Handling & Intelligent Recovery

Autocraft is engineered with a multi-layered fault tolerance system. Instead of halting or corrupting your project when issues occur, Autocraft automatically diagnoses, isolates, and repairs failures to maintain a stable development workflow.

13.1 Automatic Error Detection

Autocraft continuously monitors for issues across multiple stages:

• Next.js runtime and hydration errors
• TypeScript compilation failures
• Broken or missing component imports
• Invalid JSX/TSX structure
• Misconfigured or missing configuration files
• Dependency resolution problems
• Sandbox build and asset pipeline errors

All errors are fed back into the agent as structured logs for automated correction.

13.2 One-Command Self-Repair

If your preview fails or your application encounters issues, simply type:

“Fix the issues.”

Autocraft automatically triggers its self-healing pipeline, which:

• Analyzes sandbox and compiler logs
• Identifies the exact file and line causing failure
• Retrieves relevant context from RAG memory
• Applies targeted file-level fixes
• Rebuilds and validates the project

13.3 Self-Healing Behaviors

Autocraft proactively attempts to resolve issues without waiting for a user request.

• Regenerating missing components
• Injecting fallback placeholders
• Correcting import paths
• Rewriting invalid HTML/JSX trees
• Fixing inconsistent React boundaries
• Adding missing dependencies automatically

13.4 Safe Fallback Rendering

If a sandbox preview cannot be restored immediately, Autocraft renders aSafe Fallback Page, ensuring your preview never becomes inaccessible.

This guarantees full visibility and prevents “blank screen” scenarios commonly seen in traditional AI coding tools.

13.5 Reliability Guarantees

Autocraft's error-handling system ensures that:

• Your codebase is never corrupted
• Project history remains intact
• Previews continue functioning even during errors
• Every failure is recoverable without manual debugging

In short, Autocraft does not crash, it recovers.

14. Security Model

Autocraft is designed with a defense-in-depth security architecture to protect user data, isolate workloads, prevent unauthorized access, and ensure predictable behavior across all generated applications. The system enforces strict isolation between user projects and does not execute untrusted code directly on Autocraft servers.

14.1 Isolated Execution Sandboxes

Each preview environment runs inside a dedicated, ephemeral VM sandbox. These sandboxes:

• Cannot access other user projects or sessions
• Have no shared filesystem between runs
• Are fully reset after 30 minutes or when closed
• Operate with restricted execution privileges

This ensures that user-generated code never executes on the main Autocraft infrastructure.

14.2 Zero Cross-Project Visibility

Autocraft enforces strict project-level isolation:

• No user’s code, files, or history is ever exposed to another project
• RAG embeddings are isolated per-project and cannot leak across users
• Sandbox URLs are anonymized, randomized, and private

Each project behaves like a fully independent workspace with no shared state or context.

14.3 Restricted Network Execution

To protect Autocraft systems and prevent misuse, sandboxed applications operate under strict outbound and inbound network restrictions:

• No unrestricted outbound HTTP requests
• No inbound traffic other than the preview tunnel
• Rate-limited network-layer execution
• No long-running background processes

This guarantees safe execution even when user-generated applications include unknown or unverified logic.

14.4 Dependency & Package Safety

Autocraft validates and sanitizes dependency installation within the sandbox:

• Only npm packages explicitly referenced in code are installed
• Version spoofing and malicious package paths are blocked
• External binaries or unsafe postinstall scripts cannot execute
• Auto-installation is rate-limited and monitored to prevent package injection attacks

Combined with sandbox isolation, this ensures safe and predictable package behavior.

14.5 Data Privacy & Access Control

Autocraft adheres to strict privacy boundaries:

• Project files are stored securely and never used for model training
• RAG embeddings remain isolated to the originating project
• User messages and files are encrypted in transit (HTTPS) and at rest
• No staff-level visibility into user projects without explicit permission

14.6 No Execution on Autocraft Infrastructure

User applications never run directly on Autocraft servers. All execution happens inside:

• Ephemeral VMs
• Hardened sandboxes
• Managed containers on isolated compute nodes

This separation eliminates the risk of unsafe user-generated code impacting the platform.

14.7 Enterprise Security Guarantee

Autocraft’s architecture is built for enterprise-grade compliance and scalability, prioritizing:

• Isolation-first application execution
• Predictable and safe AI-generated code behavior
• Strict guardrails against code leakage
• Secure storage and sandbox-limited environments

Autocraft ensures that your projects remain secure, isolated, and private by design.

15. Limitations

Autocraft provides a highly capable AI-native development environment, but certain boundaries exist to ensure safety, predictability, and platform stability. These limitations help maintain a consistent user experience while preventing unsafe or unsupported behaviors.

• Not a backend service generator (yet) Autocraft focuses primarily on front-end and full-stack Next.js generation. While it can scaffold API routes, it does not yet create full production backends, microservices, or distributed server architectures.
• No native mobile app generation Autocraft does not generate React Native, Flutter, Swift, or Kotlin mobile applications. The platform is optimized strictly for modern web applications.
• Not intended for highly regulated environments industries requiring strict compliance (HIPAA, PCI-DSS, FedRAMP, SOC2 with audit trails, etc.) may require manual code review, controlled CI/CD, and formal certification that Autocraft does not currently provide.
• No long-running background execution sandbox environments are ephemeral and do not persist background tasks, cron jobs, or long-duration compute processes.
• Complex multi-service architectures may require manual engineeringAutocraft is optimized for single-project, self-contained Next.js repositories, not entire distributed systems or multi-repo microservice ecosystems.
• Limited support for complex third-party SDK configurations services such as AWS, Stripe, Firebase, or Supabase may require manual setup beyond Autocraft’s generated boilerplate.
• Large or legacy codebases may exceed RAG context limits Autocraft optimizes for incremental generation, but extremely large projects may need selective file inclusion or manual oversight.
• Sandbox preview has a fixed lifespan After 30 minutes, previews expire to preserve compute resources. Code remains saved, but the preview must be restarted.
• AI-driven output still requires user validation although Autocraft includes self-healing and validation layers, final production deployment should always be reviewed for correctness and business logic suitability.

These limitations ensure the platform remains predictable, secure, and aligned with its goal: rapid generation of stable, production-ready Next.js applications.

16. Architecture Diagram

Below is a visual, step-by-step representation of Autocraft’s full software generation pipeline. Each block is rendered as a glass-style “system node,” designed to resemble Apple-like interface panels. This format makes the architecture intuitive, modular, and presentation-ready.

A full SVG architecture diagram can also be generated for product pages, marketing, or investor presentations upon request.

17. Summary

Autocraft serves as a complete AI-powered software engineer capable of transforming a simple idea into a fully structured, validated, deployed, and versioned application. The platform automates every phase of modern software development while preserving engineering-grade quality, safety, and predictability.

• Understands natural language and visual inputs
• Converts ideas into structured, build-ready specifications
• Generates clean, scalable, enterprise-quality Next.js code
• Self-diagnoses and repairs structural or runtime issues
• Validates correctness through a hardened build pipeline
• Runs authentic Next.js builds inside secure sandbox VMs
• Maintains long-term code memory via RAG embeddings
• Version-controls your entire project over time
• Deploys globally with a single click using Vercel

Autocraft is built to streamline the development lifecycle from concept to deployment enabling teams and individuals to produce production-ready software with unprecedented speed and reliability.

Because your time should go into the things that actually matter.