AI Research & Development Organization · Est. 2026

Overcoming the
Limits of AI

Dharmatech LLC investigates the fundamental limitations of artificial intelligence and develops novel architectural approaches to overcome them — producing open research outputs, working implementations, and reusable knowledge artifacts.

R&D
Focus
Open
Research Outputs
Novel
Architectural Approaches
Peer
Research Grounded
Areas of Investigation

Research Focus

Investigating where AI falls short and developing novel architectural responses to each failure mode.

01
Autonomous Knowledge Acquisition
Researching how AI systems can acquire, validate, and permanently retain mastery over technical domains without human intervention. Focus areas include continual learning architectures, cross-session episodic memory, and mastery scoring frameworks that compound over time.
02
Self-Improving AI Systems
Developing approaches for AI to reason about its own limitations, identify gaps in understanding, and autonomously improve its own capabilities. Grounded in Gödel Machine theory, STaR-style bootstrapping, and evolutionary program synthesis.
03
Multi-Agent Coordination
Researching emergent behaviors in multi-agent architectures — agent role decomposition, inter-agent knowledge transfer, and orchestration strategies that remain modular as system complexity scales.
04
AI Failure Mode Analysis & Remediation
Systematic investigation of where current AI approaches break down: cold-start amnesia, hallucination in code generation, reasoning degradation under long context, and context loss across sessions — and developing novel architectural responses to each.
Research Outputs

What We've Built

PUBLISHED · 2026
Self-Learning Multi-Agentic System
An AI that autonomously acquires, validates, and permanently retains mastery over any technical domain. Eight specialized agents, a six-phase adaptive learning loop, semantic cross-session memory, and an 11-phase implementation validation gauntlet.
Multi-Agent Continual Learning Knowledge Engineering Autonomous AI
IN DEVELOPMENT
AI-Native Code Intelligence Platform
A multi-agent platform for autonomous codebase understanding, incremental refactoring, and architecture-aware code generation — designed for large enterprise monorepos and CI-integrated workflows.
Code Intelligence Enterprise AI AST Analysis
Coming 2026
IN DEVELOPMENT
Research Assistant Application
An AI-native research assistant built on the self-learning architecture — capable of autonomously surveying literature, synthesizing findings across sources, identifying research gaps, and generating structured research reports. Designed to accelerate the R&D cycle by treating knowledge acquisition as a first-class engineering problem.
Research Automation Literature Synthesis Knowledge Engineering Autonomous AI
Coming 2026
About

Dharmatech LLC

Founded by Mark Wireman

Dharmatech LLC is a research and development organization dedicated to investigating the fundamental limitations of artificial intelligence and developing novel architectural approaches to overcome them. Our work spans autonomous learning, self-improvement, multi-agent coordination, and AI failure mode analysis — producing open research outputs, working implementations, and reusable knowledge artifacts.

We operate at the frontier of AI research and engineering, drawing from primary literature in continual learning, self-referential systems, and evolutionary program synthesis — translating theory into working implementations that demonstrate what is actually possible today.

Principal Mark Wireman
Organization Dharmatech LLC
Focus AI Limitations Research · Autonomous Learning · Self-Improving Systems
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