Knowledge Atlas
Focusing…
Neurofolio © 2026
Maker Culture & DIY
15 entries
Under tight contractual obligations and unclear vectors of work, conducted a set of experiments with 2 team members. We identified and prioritised/deprioritised streams of work. Result: we got a tool that wraps everything to an LLM — add-experimental-flag/SKILL.md.
Reframed an architecture stalemate into an organizational risk problem and got leadership alignment without formal authority. A legacy setup tightly coupled frontend and backend ownership. Frontend delivery depended on boundaries the backend controlled, creating unclear handoffs and a single point of failure. I'd proposed a known frontend architecture pattern, but it stalled because resistance centered on ownership, risk, and control rather than technical merit. I stopped pushing the pattern and
Leading the Neurofolio initiative, applying AI-driven agentic workflows to build adaptive knowledge portfolios and tooling.
Principal Engineer with a background in frontend and full-stack architecture, focusing on AI-driven agentic workflows that automate complex software systems.
Principal Engineer focused on AI-driven agentic workflows, evolving from frontend engineering into full-stack architecture.
Consolidate scattered taxonomy definitions into a single authoritative module (lib/taxonomy) to standardize types, color formats, and emoji mappings across multiple BCs.
Neurofolio targets the inefficiency of SaaS employees spending excessive time searching for internal knowledge. It uses a RAG-based assistant fine-tuned to company-specific data, providing accurate and secure responses that enhance productivity and decision-making.
Neurofolio is a vertical AI assistant for SaaS companies that transforms internal knowledge into an accessible resource using Retrieval-Augmented Generation (RAG). It answers employee questions using trusted internal documents and queues unanswered questions for the appropriate role. It integrates with Slack and starts as a standalone webapp, learning continuously to improve.
In the era of generative UI, traditional frontend complexity is becoming unnecessary for mini-tools and scoped interactions. The new approach focuses on prompt-driven, self-contained, design-system-aware development, using precision HTML and JS instead of bloated frameworks.
Transitioning from low-code platforms to custom-built applications can increase tech debt risk due to lack of mature software processes. This includes challenges in spotting tech debt, unmanaged architecture, reliance on team practices, and systemic risks affecting business-critical systems. The absence of dedicated DevOps and QA pipelines exacerbates these risks, making it crucial for companies to adopt software product discipline.