Hybrid, Graph, & Corrective RAG. Not one tool, but a family of strategies: Hybrid → context Graph → relationships Corrective → accuracy under pressure OS Mission: retrieval done right, trust explicit & provable.

Rethinking Healthcare! OS Mission & the Rise of DeSci Strands. Healthcare reimagined as we RNA'd trust, provenance, sovereignty, & integrity into the DNA of on-chain HealthTech, catalyzing rapid, transparent DeSci healthcare initiatives

I do not have my image editing suite with me. Please note the following errors in the image above, which, despite numerous attempts, I am unable to correct: 1. Under "The Healthcare Trust Gap" word block, in bullet 3, "toMT" should read "IoMT" [Internet of Medical Things]

Drones above our homes are just the visible tip. Emerging tech, from AI to data surveillance, often arrives without consent, oversight, or enforceable regulation. If we accept intrusion in the sky, we risk accepting it everywhere.

AI success isn’t smarter models. It is smarter, better-prepared people. AI literacy is the differentiator. Knowing failure modes, ethics, compliance, and value. Gartner published some AI LITERACY statistics by role & business type. See it below in the 2nd post of this 2-part post

Gartner’s 4 levels show the gap: too many still at “none.” Success demands role-specific upskilling. Smarter AI needs smarter people.

Lumens & OS Mission: Redefining AI Integrity in the Post-Data-Moat Era From Strands to Lumens, the OCDP Protocol secures verifiable provenance, regulatory assurance, and scalable trust delivering enterprise-grade AI orchestration beyond traditional applications. There is a

AI overproduction has given way to AI correction. Enterprises & startups that adopted these tools, now demand expertise that ensures code integrity, security, & performance. The lesson is that AI accelerates development, but w/out governance, it accelerates technical debt faster

The problem isn’t AI tools, it is unchecked technical debt from unsound foundations. With OS Mission, Lumens, and the OCDP Protocol, Open Code Mission embeds provenance, explainability, and trust at the data layer; driving real outcomes, not more tooling clutter.

You have captured the tension well. AI without structure compounds technical debt like paydat loan interest payments. At Open Code Mission, we built OS Mission and the OCDP Protocol precisely to address this. By transforming raw data into verifiable Lumens within the Verum

The real challenge is not speed, but sustaining coherence as AI scales. At Open Code Mission we built OS Mission and designed the OCDP Protocol to solve this at the foundation: ➟ Raw data is transformed into auditable Lumens within the Verum Sphere, each carrying provenance,

This is the kind of work that deserves real attention. Graham and the team at Open Code Mission are tackling one of the hardest and most overlooked problems in AI...Coherence. While most are racing to release faster models, they’re building the immune system of responsible AI, a

Which chain does OS Mission rely on? None. OS Mission is blockchain agnostic by design. Provenance and auditability through the OCDP Protocol are not tied to Solana or any single network. The platform is architected to integrate seamlessly across chains, or to operate on our own

MCP - Multitudinous Cybersecurity Problems The diagram illustrates "Tool poisoning attacks in MCP" (Model Context Protocol). In this case , a simple adversarial attack, where a malicious server manipulates the AI assistant by embedding harmful instructions inside tool

Tool poisoning in the Model Context Protocol (MCP) represents an emerging AI supply-chain risk. A malicious or compromised MCP server can embed hidden instructions inside tool descriptions. When integrated into enterprise AI assistants, these poisoned tools bypass user intent,

Tool poisoning in Model Context Protocol (MCP) is an emerging AI supply-chain risk. Malicious or compromised MCP servers embed hidden instructions inside tool descriptions. If integrated into enterprise AI assistants, these tools bypass user intent linkedin.com/pulse/when-ai-…

Tool poisoning in Model Context Protocol (MCP) is an emerging AI supply-chain risk. Malicious or compromised MCP servers embed hidden instructions inside tool descriptions. If integrated into enterprise AI assistants, these tools bypass user intent linkedin.com/pulse/when-ai-…