50 free Raspberry Pi and Pico projects from the official sites, plus 8 bonus builds. Filter by level and parts, follow a learning path, and learn each idea with interactive diagrams.
OnDevice.ai is a private, local-first AI workspace — chat, projects, files and deterministic PPTX/XLSX/DOCX generation, running on your own hardware. The architecture, the design bet behind it, and an honest comparison with Claude and ChatGPT.
Why I built 'Forward Deployed Engineer: AI for the Infrastructure Estate' — course seven on AICademy. FDE method, infrastructure substance: embed with a client, assess the estate, then deliver and govern an AI change behind a human gate, across one accumulating 10-week engagement.
AICademy: six hands-on AI courses and 82 modules built for infrastructure support engineers at GSIs like TCS, HCL and Infosys. The philosophy, the stack, the courses, and why it's different from every AI course online today.
A rebuild log for AICademy: the six upgrades I shipped after a code review — scroll restoration, empty-state removal, lazy loading, a week's-path checklist, catalog wayfinding and worked examples — the two findings I declined, and the performance fix I deliberately left half-done.
A visual guide to AICademy's five hands-on paths — Service Desk, SysAdmin, IT Project Manager, RAG Engineering, and Agentic AI Leadership — and how to pick the one that matches the job you already do.
A technical deep-dive into my IIT Madras Agentic AI capstone: a framework-free customer-support resolution agent with deterministic pre-LLM safety, grounded RAG, guarded tool use, memory — and the live date-arithmetic failure that reshaped its architecture.
For thirty years, infrastructure outsourcing has competed on scale. AI is about to move the contest to who owns the best organisational knowledge. This is my case for Knowledge Agents — specialist AI experts sitting on a structured knowledge layer built from thousands of engagements. It separates industry consensus from my own hypothesis, answers the 'doesn't Copilot already do this?' question, puts numbers on the business case, gives a phased roadmap, and makes the case for the buyer as well as the provider. Companion to my two pieces on the MCP agent fabric.
Two real AI failures, two domain safeguard designs, and the responsible-AI thinking that connects them. My write-up from a mini project on agent risk, ethics, and governance.
