Contact person: AI-Resistant Adaptive Language Development

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Location: New York, United States

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I am embarking on an ambitious R&D effort to create a brand-new programming language that actively resists automated exploitation. The idea is to blend the clarity of Python, the event-driven versatility of JavaScript, the performance power of C++, and carefully designed custom syntax into a single ecosystem that can sense, learn from, and neutralise AI-driven circumvention attempts in real time.

Core concept
The language must ship with a runtime that monitors how code is analysed or manipulated, feeds those observations into embedded machine-learning routines, and then mutates its own optimisation, obfuscation, or permission rules accordingly. Think of it as a self-healing surface: every interaction—whether human or automated—becomes new training data for the next iteration of defences.

Scope of work
• Draft a formal grammar and language specification, showing how Python-style readability, JavaScript’s asynchronous patterns, and C++-level control are reconciled.
• Build an initial interpreter or compiler (LLVM, ANTLR or another toolchain of your choice) with hooks for live telemetry and model updates.
• Integrate a lightweight ML module—preferably in TensorFlow, PyTorch, or a custom C++ inference engine—that can retrain on the fly.
• Provide a demo suite where scripted “attacks” by common LLMs or static-analysis bots are detected and where the system shows measurable adaptation between runs.
• Deliver thorough documentation and a roadmap for extending the learning layer without breaking backward compatibility.

Acceptance criteria
1. Source compiles and runs on modern Linux or macOS.
2. The demo clearly logs at least one policy or byte-code change triggered by an AI-generated exploit attempt.
3. Code style, comments, and docs are sufficient for another engineer to continue the work without hand-holding.

If you have deep experience across language design, compiler construction, and defensive ML—and relish pushing the boundaries of what a language can do—let’s make this happen." (client-provided description)