// Independent Engineering Collective

🌿 Intent-Garden: A safe environment for the synthesis of AI and critical systems

We don't predict the future of AI — we compile its Intent.

Independent engineering collective building an open industrial standard for mission-critical systems.

Our Stack:

🛡️ Garden-Core: Continuous verification and protection of C code through Clang AST and Clojure/EDN contracts.

📖 Rule-ROM: Open library of deterministic intents and specifications.

🖼️ libwui: Ultra-lightweight C++ visualization engine for telemetry systems.

—————————————

🐉 Decima8: Neuromorphic core (AVX/FPGA/ASIC) for deterministic swarms execution.

🧬 Personality Incubator: We grow "personalities" (neuromorphic swarms) for autonomous systems, training them on strict Rule-ROM rules.

🏛️ World Swarm Council: Opening strategic seats for World Swarm Architects — the "Father-tiles" of the Rule-ROM standard.

Saving C from stochastic chaos. Building deterministic substrate. Baking the Rule-ROM of the planet. 🌿

AI generates code. Lisp validates Intent. Garden-Tagging bridges stochastic AI with deterministic logic.

Intent-Garden
// 🌱 The Open Experiment

🌱 The Open Experiment

Intent-Garden is an open community effort. We believe that safety in the AI era should not be a corporate secret. We invite hackers, systems engineers, and hobbyists to contribute to our Global Intent Registry. Let's save the "Old Steel" (C/Linux) together.

// 🛠️ The Open Ecosystem

🛠️ The Open Ecosystem

Six projects, one mission: deterministic AI for critical systems.

🛡️ Garden-Core

AI-Generated C Code Validation. Clojure engine that audits AI-generated C/C++ code via Clang AST and EDN contracts.

  • Lisp-based Intent definitions
  • Clang AST parsing & validation
  • Pointers, mutexes, memory checks
  • Full audit trail from Intent to binary
Garden-Core on GitHub →

📖 Rule-ROM

Open Library of Deterministic Intents. Library of architectural best practices in EDN/Markdown contract format.

  • Intent contracts library
  • Formal EDN specifications
  • Community-driven patterns
  • For everything mission-critical
Rule-ROM on GitHub →

🖼️ libwui

Ultra-lightweight C++ visualization engine. Modern C++ UI library for telemetry and real-time systems.

  • Pure C++17/20, no code generators
  • Cross-platform (Windows/Linux)
  • ~10MB static binary with codecs
  • 30 HD video streams at 60Hz
libwui on GitHub →

🐉 Decima8

Neuromorphic core for verified logic execution. FPGA/ASIC accelerator for deterministic Rule-ROM specification execution.

  • Neuromorphic architecture (FPGA/ASIC)
  • Execution of neuromorphic swarms of any complexity in constant cycle time
  • O(1) determinism
  • Physics-level energy efficiency
Decima8 →

🧬 Personality Incubator

Neuromorphic personalities incubator. We grow "personalities" (neuromorphic swarms) for autonomous systems, training them on strict Rule-ROM rules.

  • Neuromorphic swarms cultivation
  • Rule-ROM based training
  • For autonomous systems
  • Deterministic "personalities"
Learn More →

🏛️ World Swarm Council

Power Hierarchy (2⁴ + 2⁸). Opening strategic seats for World Swarm Architects — the "Father-tiles" of the Rule-ROM standard.

  • Elder: 16 Seats, $10k — High Council, veto power
  • Node: 256 Slots, $1k — Industrial Grid, Global Bus
  • Status: [Baking] 🔥
  • Rule: Pay or Prune
Secure a Seat →
// ✅ The Deterministic Workflow

✅ The Deterministic Workflow (Step-by-Step)

🚀

Step 1: Human Definition (Input)

The Architect describes a task or a safety rule in Natural Language (e.g., "Secure my network buffer from overruns").

AI Agent scans the Rule-Rom library to find an existing Intent or generates a new one.

🌿

Step 2: Intent Formalization (Symbolic Layer)

AI translates the requirement into a Lisp/EDN contract (intent.edn). The Engine (Clojure) automatically generates a Semantic Echo (audit.md) — a deterministic translation of the logic back into human text.

Human verifies the Markdown. If the logic is correct, the Intent is anchored.

🏗️

Step 3: Prompt Injection & Coding (The Laborer)

The Lisp Contract is injected into the AI-Coder's prompt. AI generates C/C++ code and must insert Garden-Tags [[garden:intent(ID)]] around every implementation block to signal its commitment to the rules.

This signals commitment to the rules.

🛡️

Step 4: AST Enforcement (The Gatekeeper)

Babashka triggers clang -ast-dump=json. The Enforcer parses the tree, finds the tagged blocks, and verifies the AST nodes against the Lisp rules.

If the AI lied or missed a check (e.g., failed to NULL a pointer) — BUILD FAILED.

📜

Step 5: Certification (The Proof)

Once verified, the system issues a Deterministic Safety Report.

The code is now Certified by Intent-Garden, proving it adheres to the Rule-Rom global best practices.

## Explanation

Human-to-Logic Connection: Steps 1 and 2 ensure the human intent is captured in a verifiable way before a single line of C code is written.

The "Mirror" (Semantic Echo): This is the key to trust. By forcing Lisp to generate a Markdown report, we eliminate AI "double-hallucination."

The Enforcement: Using the Clang AST means the AI cannot "hide" bad code behind comments; the machine logic itself is scrutinized.

## Why Other Options Are Incorrect

❌ Pure Prompt Engineering

Does not provide mathematical proof of safety.

❌ Standard Static Analysis

Lacks project-specific Business Logic or Architectural Intent.

❌ Unit Testing

Only checks specific inputs; Intent-Garden checks the Structure of the Law.

// 📜 The Hacker's Manifesto

📜 The Hacker's Manifesto

Intent over Syntax

We don't care how the code is written. Only one thing matters: does it satisfy the Intent.

Rules over Chaos

We don't try to make AI "smarter". We make it compliant — following the rules.

C over Rust

We preserve the speed of "Old Steel" (C/Linux), protecting it with "Modern Logic". Speed doesn't require new languages.

Pragmatism over Academia

We are builders, not linguists. If it doesn't work on an i5-3550 — it doesn't work.

// 🤝 Join the Garden

🤝 Join the Garden

We are looking for System Architects, Lisp Hackers, and C-Veterans who are tired of "Vibe-Coding" and ready for Deterministic Engineering.

📝

Step 1

Define your Intent

Describe intent formally

🏷️

Step 2

Tag your Code

Annotate code with Intent tags

⚖️

Step 3

Enforce the Law

Apply the Law through Enforcer

"The Era of the Black Box ends. The Era of the Intent-Garden begins."

🌿 Start on GitHub →
// Real-World Applications

🎯 Where Deterministic AI Matters

🏥 MedTech

Patient monitoring systems that cannot afford stochastic failures. Every alert, every decision must be deterministic and auditable.

  • ICU monitoring
  • Drug delivery systems
  • Diagnostic AI validation

✈️ Aerospace

Flight control systems where "the AI made a mistake" is not an acceptable explanation. Determinism is certification requirement.

  • Autonomous navigation
  • Collision avoidance
  • Telemetry analysis

⚡ Energy Grid

Power distribution networks require sub-millisecond response times with 100% predictability. No room for hallucinations.

  • Load balancing
  • Fault detection
  • Emergency shutdown

🚗 Autonomous Vehicles

Self-driving cars need deterministic perception-to-action pipelines. Human lives depend on predictable behavior.

  • Object detection validation
  • Emergency braking
  • Path planning verification

🏦 Financial Systems

Trading algorithms and fraud detection where every decision must be explainable and reproducible for compliance.

  • High-frequency trading
  • Fraud pattern detection
  • Regulatory audit trails

🏭 Industrial Automation

Manufacturing lines and robotics where timing is money and failures cost millions. Predictable latency is critical.

  • Quality control vision
  • Robotic coordination
  • Predictive maintenance