Genrikh: Building a $0-Marginal-Cost Universal AI Problem Solver with Gemma 2, Sentry & ElevenLabs A developer known as torrua built Genrikh, an open-source AI problem solver that applies the TRIZ/ARIZ algorithmic methodology to engineering and business trade-offs using Google's Gemma 2 running locally via Ollama, with Sentry agent tracing and ElevenLabs audio debriefings. The project targets $0 marginal cost and full intellectual property privacy by keeping inference on local hardware, and structures reasoning through a dual-loop pipeline that sharpens physical contradictions before delivering layered outputs. Submission for the Hacktoberfest Open-Source AI Challenge: Week 2 — Side Hustle https://dev.to/challenges/hacktoberfest-week2-2026-10-12 . Repository: github.com/torrua/triz-universal https://github.com/torrua/triz-universal Author: @torrua https://dev.to/torrua Target Partner Tracks: Best Use of Gemma, Best Use of Sentry Agent Tracing, Best Use of Render, Best Use of ElevenLabs In 1946, Soviet inventor and patent examiner Genrikh Saulovich Altshuller 1926–1998 began reviewing thousands of breakthrough inventions to answer an audacious question: Is inventive genius a genetic lottery, or is it an exact algorithmic science? Altshuller discovered a recurring law across every field of human ingenuity: Real innovation is NOT compromise. Conventional thinking resolves conflicting requirements by meeting in the middle: buying more hardware to handle unoptimized code, crippling battery life for faster sensor reads, or raising prices to cover cloud overhead. Inventive thinking sharpens the conflict into an atomic Physical Contradiction and eliminates it completely using latent resources already present in the system. Altshuller formalized this into TRIZ Theory of Inventive Problem Solving and the rigorous ARIZ algorithm. When modern AI chatbots encounter tough trade-offs, they default to lazy, expensive platitudes: "In the real world, trade-offs are inevitable. You should purchase an enterprise Redis cluster or scale your cloud instances." I built Genrikh to change that. Genrikh is an autonomous, open-source AI problem solver that brings classical ARIZ algorithmic rigor to modern engineering, hardware, and business systems—with $0 marginal cost and 100% intellectual property privacy . When solo-founders, freelance developers, and small engineering teams build products, they hit crippling deadlocks: Hiring a human senior architect or patent attorney costs $250–$400/hour . With Genrikh , any freelance engineer or consultant can run an audit in 60 seconds and deliver: Large Language Models tend to hallucinate or invent post-hoc justifications if asked for an answer directly. To enforce scientific rigor, Genrikh implements a Dual-Loop Execution Pipeline : flowchart TD subgraph Loop1 "Loop 1: Deep Methodological Reasoning Internal State Lock " S0 "Step 0: Limit & Constraint Pre-Check