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Mohammed Affan

Software Developer · Known online as Itachi

Professional profile

Software developer working across AI systems and the infrastructure around them. At Pollinations.ai, contributes agent interfaces, MCP tooling, retrieval, and isolated execution; at Myceli.ai, builds AI workflows and automation. Independent work spans model research, Rust systems, evaluation environments, and web, mobile, and 3D applications.

Professional experience

Pollinations.ai

Feb 2025 – Present

Myceli.ai

Feb 2025 – Present
  • Connect AI infrastructure through automations and workflows, connecting models, services, and agent modules across cloud and local environments.

Independent research & development

Ouroboros

  • Develop language-model research prototypes in PyTorch under local hardware constraints; retain unpublished architecture and implementation details privately.
  • Evaluate mechanisms independently against explicit baselines; document ablations, limitations, and negative findings in a public research notebook.
  • Public output is a research log. No published paper or public benchmark result is claimed.

Sylph

  • Develop a Rust-based AI runtime exploring local inference, task-driven learning, and peer-to-peer exchange of model adapters.
  • Separate model backends through an inference contract; implement adapter compatibility and payload-integrity checks in the exchange path.
  • Develop adapter-composition checks and adversarial tests, with local and Kubernetes/Helm deployment tooling. Public overview available; implementation remains private.
Mohammed AffanEngineering projects & technical background

Selected engineering projects

Memory-Arc

  • Built configurable memory infrastructure connecting recent conversation history to persistent vector retrieval, with AI, heuristic, hybrid, and disabled processing modes.
  • Separated configuration, JSON persistence, asynchronous memory interfaces, and model-provider adapters.

Repository intelligence

  • Develop local repository-analysis tooling using Rust, Tree-sitter, SQLite, and FTS5 for language structure, persistence, and evidence retrieval.
  • Build explicit validation context to distinguish stored results from evidence about the current source state.

Agent evaluation environments

  • Built simulation environments for evidence-based investigation, with procedural scenarios, MCP tools, state transitions, and reward components.
  • Added adversarial tests for reward shortcuts and evidence gathering; developed an adversary that advances during investigation and adapts to containment actions.

Application engineering

  • Built a Flutter records and reporting application with Supabase integration, insights screens, PDF tooling, and automated builds.
  • Developed a Next.js presentation builder with research, outline, image-generation routes, streamed results, and editing interfaces.
  • Built SceneForge with typed scene descriptions, incremental JSON parsing, and streamed updates to an interactive Three.js scene.

Technical skills

Languages: Python, TypeScript / JavaScript, Rust, Dart, SQL.

AI & MLOps: PyTorch, model fine-tuning, local inference, model deployment, MCP, agent orchestration, RAG.

Infrastructure: Cloudflare Workers, Vectorize, D1, Docker, Kubernetes, Helm, Linux, GitHub Actions.

Applications & data: FastAPI, React, Next.js, Flutter, Three.js, Qdrant, SQLite, Supabase.

Education

Diploma — AI/ML pathway

Pursuing · 5th semester

MS Ramaiah Polytechnic

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