Personal Genomics Zone

Dr Manuel Corpas presents the HEIM framework and Bias Amplification Cascade at the Molecular Science Research Hub seminar (12 March 2026). The talk covers three dimensions of compounding neglect in biomedical research: discovery (70 biobanks, 38,595 publications), translation (563,725 clinical trials), and knowledge (13.1M PubMed abstracts). Key findings: no neglected tropical disease has generated a single biobank publication; 93.5% of biobank research comes from high-income countries; and structural metrics predict 66.6% of LLM performance variance across 175 diseases. Six frontier LLMs benchmarked on 10,500 standardised queries show identical blind spots, proving the bias originates in shared training data, not model architecture. The talk concludes with the HIV/AIDS case as proof that sustained investment can reverse semantic isolation.

Dr Manuel Corpas introduces Agentic Genomics — a framework for how AI agents are transforming bioinformatics. Covers the HEIM equity framework, bias amplification in genomic AI, ClawBio skill library, and why deep human intelligence remains the bottleneck. Recorded 9 March 2026.

Live demo of ClawBio, the first bioinformatics-native AI agent skill library, presented at DoraHacks Demo Day at Imperial College London on 7 March 2026. Covers pharmacogenomics, intelligent routing, multi-channel agents (Telegram and WhatsApp), and the Drug Photo feature. 21 skills, 14 production-ready, built on OpenClaw.

Peter Steinberger delivers the keynote at the UK AI Agent Hack at Imperial College London. He discusses building open-source AI agent tooling, setting up a foundation with David Morin to accept donations and hire full-time contributors, learning by building rather than reading, the exchange loop as the 'hello world' of AI agents, and why prompt injection remains an unsolved industry problem that should discourage one-click installations for non-technical users.

How I built a complete AI research infrastructure -- from personal knowledge base to automated pipelines -- without software engineering training. Practical lessons on vibe coding, the six-layer RAG architecture, and leveraging domain expertise to build tools that matter.

Seven actionable insights for researchers on using AI as a learning partner: pair-programming with LLMs, handoff documents, project organisation, autonomous agents, voice interfaces, AI-to-AI orchestration, and context-first prompting.

What separates casual AI users from the top 1%? Drawing on lessons from building a personal agentic AI system over six months and insights from Calvin French-Owen (co-founder of Segment, former OpenAI Codex team), this episode covers ten practical strategies: building persistent memory systems, mastering context management, test-driven AI workflows, moving from chatbots to agents, automating intelligence pipelines, clearing context aggressively, thinking like an engineering manager, keeping your workspace clean, shipping citable artifacts weekly, and building for sovereignty over your own AI.

A 71-minute lecture on how genomics is transforming medicine from trial-and-error to targeted, predictive care. Covers the paradigm shift from population averages to personalised treatment, variant interpretation using ACMG guidelines, the distinction between Mendelian and complex diseases, genome-wide association studies, and next-generation sequencing. Examines the critical equity gap: 86% of genomic research participants are of European ancestry yet Europeans represent only 16% of the global population. Introduces the HEIM framework for quantifying genomic data representativeness. Includes pharmacogenomics, liquid biopsy, direct-to-consumer testing, and ethics of genomic data. Delivered at the University of Westminster, 30 January 2026.

A practical walkthrough of building a personal agentic AI system that runs at production scale. Covering architecture (ChromaDB, Voyage AI, tiered Claude models), a nine-tool Telegram agent called RoboTerri, six automated daily jobs including ArXiv paper digests and podcast intelligence, cost engineering with three-tier model routing, and seven lessons learned from six weeks of autonomous operation.

Topics: ChromaDB vector database with 14 collections, Voyage AI embeddings, three-tier Claude model routing (Opus/Sonnet/Haiku), RoboTerri Telegram bot with 9 tools (memory query, calendar, audio generation, voice transcription, photo analysis), automated morning briefings, ArXiv research digests, podcast insight extraction with human-in-the-loop approval, PharmXD pharmacogenomic advisor, cost engineering from £1.50/day to 20p/day, and seven production lessons.

I spend many hours working with LLMs to help me support my academic writing. This post summarises what I have learned. If you are using LLMs to help write academic papers, grant applications, or technical reports, these observations might save you from some painful mistakes.