Surya Prakash Jayanti

How a knowledge graph, two cron jobs, and an LLM replaced my morning routine Surya Jayanti · April 2026 I manage a platform with 400+ repositories across multiple GitHub orgs. Every morning used to mean: 30+ merged PRs releases I didn’t track wiki updates I missed 22 blogs worth of industry noise So I built three AI systems that read everything for me, analyze it against my codebase, and send a briefing before my first coffee. This is how it works. 1. The Knowledge Graph: Teaching an LLM Your Codebase LLMs are great generalists, but they don’t understand your platform. Ask them about your services and they’ll confidently hallucinate. I call this the hallucination gap . The fix: build a structured representation of your codebase. Why not just RAG? Chunk-and-embed gives you fragments. But real insights live between files : imports → dependencies Kafka producers → consumers service calls → system wiring So instead of dumping code, I extract relationships. 4-Layer Model ...

  🚨 Combating AI Slop: A Framework for Effective AI Use TL;DR:  AI-generated content is flooding our workflows with diminishing returns. This page defines AI Slop, identifies where it happens, and provides actionable tools to filter signal from noise. 1.   AI Slop is flooding orgs  — 95% aren't seeing ROI, 40% more content YoY, and 53% of recipients are annoyed by low-quality AI output that shifts work downstream 2.   Two main sources  — Confluence pages (published without review) and PRs (AI-generated code without self-review) 3.   Fix it with machine-first review  — Use AI agent review, to review content before publishing/requesting human reviewers 🎯 The Decision Adopt a "machine review before human review" workflow  — AI catches the obvious slop so humans can focus on substance. ✅ The Action Confluence Run pages through AI for summary before publishing. If it can't be summarized clearly → revise first.  PRs Require AI Agent review b...

Quotes from the book "Ultralearning". In theory, there is no difference between theory and practice. But in practice, there is. Maximize the effectiveness of Ultra learning:  MetaLearning : First Draw a map. Focus : Sharpen your knife Directness : Go straight ahead Drill : Attack your weakest point. Retrieval : Test to learn Feedback : Don't dodge the punches Retention : Don't fill a leaky bucket Intuition : Dig deep before building up.            Experimentation : Branch out  and try new approaches. If I have seen further, it is by standing on the shoulders of giants. A good rule of thumb is that you should invest approximately 10% of your total expected learning time into research prior to starting. Now I will have less distraction. Leonhard Euler, mathematician, upon losing the sight in his right eye. First step to overcoming procrastination: recognize when you are procrastinating. Emotions can hijack the mind and make the process of returning ...

Quotes from the book "System Error". There are decades when nothing happens—and weeks where decades happen. System Error explores what breaks when fast-moving technology outpaces slow-moving institutions. When metrics become goals, and optimization replaces wisdom, systems fail quietly at scale. Progress needs better rules—not just better leaders. “There are decades when nothing happens, and then there are weeks where decades happen.”  History doesn’t move linearly—it accelerates suddenly, often without warning. “If men were angels, no government would be necessary.” Governance exists not because humans are perfect, but precisely because we are not. “Not everything that counts can be counted, and not everything that can be counted counts.” The most meaningful outcomes often resist neat quantification. The metric becomes the goal, and the means justify the end. This is Goodhart’s Law : when a measure becomes a target, it ceases to be a good measure.  To optimize for scienc...