[ Blog ]
Notes from the workbench.
Long reads on building AI, software and security that hold up once real people start using them.
How to Build Your First AI Proof of Concept
Most AI PoCs fail not because the technology does not work, but because the problem was never scoped correctly. Here is a practical, step-by-step guide for technical leaders who want to get it right the first time.
14 min read →RAG Pipeline Architecture: A Complete Guide
A deep technical guide to building production RAG pipelines — from chunking strategies and embedding models to retrieval, reranking and the failure modes that will bite you if you do not plan for them.
15 min read →AI in Healthcare: 5 Real-World Applications That Are Actually Working
Not theoretical. Not in pilot. These five AI applications in healthcare are delivering measurable results in production today — and the engineering behind them is more practical than you might expect.
13 min read →LLM Security Checklist for Enterprise Deployments
A practical, actionable security checklist for enterprises deploying LLMs in production — covering prompt injection, data leakage, access controls, red teaming and more.
14 min read →Multi-Agent Systems: Architecture Patterns for Production
A technical deep-dive on building multi-agent systems that survive production — covering agent architectures, orchestration patterns, state management, failure handling and real-world lessons from SwarmScope.
15 min read →AI Automation ROI: A Decision Framework for Business Leaders
A practical framework for evaluating AI automation investments — covering candidate identification, true ROI calculation, hidden costs, build vs buy and phased rollout strategy.
14 min read →GraphRAG: Why Basic RAG Is Not Enough for Complex Data
Standard RAG retrieves chunks. GraphRAG understands relationships. Here is when you need it, how it works, and the engineering trade-offs involved.
10 min read →Shipping Three SaaS Products as a Solo Founder: What Actually Works
I shipped Inscrape, Nirvana and SwarmScope while studying CS full-time. Here is the system that made it possible — and the mistakes I made along the way.
9 min read →Why Your Engineering Team Ignores Alerts (And How to Fix It)
Alert fatigue is not a people problem — it is an engineering problem. Here is how we built Nirvana to cut alert noise by 90%.
8 min read →How We Built a 5,000-Agent Simulation Engine
SwarmScope turns unstructured data into living simulations. Here is the architecture behind running 5,000 autonomous agents with personalities, memory and social dynamics.
10 min read →What I Learned Shipping a Python SDK to PyPI
Building Inscrape taught me that the hard part of an SDK is not the code — it is the developer experience. Here is what I got right and what I would change.
7 min read →The Rise of AI-Powered Ransomware: What Defenders Need to Know
Ransomware operators are adopting AI to automate target selection, evade detection and accelerate encryption. Here is what your SOC needs to prepare for.
8 min read →Building Robust ML Pipelines: Lessons from Production Deployments
Hard-won lessons about what separates ML pipelines that thrive from those that quietly decay — from data quality to training-serving skew.
12 min read →Zero Trust Beyond the Buzzword: A Practical Implementation Guide
Zero trust has become one of the most overloaded terms in cybersecurity. Here is a practitioner's guide to what it actually means and how to implement it.
10 min read →Adversarial Attacks on LLMs: The Security Risks of Deploying Large Language Models
As organisations rush to deploy LLMs, a new attack surface is emerging. From prompt injection to training data extraction, here are the threats you need to understand.
11 min read →The Future of the Autonomous SOC: Human Judgement Meets Machine Speed
The fully autonomous SOC is not science fiction — it is an engineering problem being solved today. Here is how the role of the human analyst is evolving.
9 min read →Data Poisoning Attacks: How Adversaries Corrupt Your ML Models from the Inside
Data poisoning is one of the most insidious threats to machine learning systems. Learn how attackers manipulate training data and how to defend against it.
10 min read →Securing Kubernetes at Scale: A Practical Checklist for Production Clusters
Kubernetes is powerful but complex, and misconfigurations are the leading cause of cloud-native breaches. Here is a battle-tested checklist for production security.
13 min read →Multi-Agent AI Systems: Architecture Patterns for Production Deployments
Building AI systems where multiple agents collaborate is fundamentally different from building single-agent applications. Here are the architecture patterns that work.
11 min read →A Practitioner's Guide to Dark Web Intelligence Collection
Dark web monitoring has become essential for proactive security. Here is what actually works, what does not and how to operationalise dark web intelligence.
9 min read →Building a Responsible AI Framework That Actually Works
Most responsible AI frameworks gather dust in shared drives. Here is how to build one that is operationally embedded, measurable and genuinely effective.
10 min read →Software Supply Chain Attacks in 2026: The Expanding Threat Landscape
Supply chain attacks have evolved from targeting build systems to compromising AI model registries, open-source training data and inference APIs.
8 min read →Real-Time Feature Engineering: Patterns for Low-Latency ML Systems
When your model needs features computed in real time at sub-100ms latency, standard batch approaches collapse. Here are the patterns that scale.
12 min read →Swarm Intelligence in Cybersecurity: From Biology to Production Systems
How distributed agent architectures inspired by biological swarms are enabling a new paradigm of collective threat detection that no single sensor can achieve.
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