What's Happening With AI Token Prices, and What It Means for Your Budget
A practical look at why AI token prices can feel both expensive and rapidly cheaper, and how falling inference costs change what customers should expect from AI products.
What's Happening With AI Token Prices, and What It Means for Your Budget
A practical look at why AI token prices can feel both expensive and rapidly cheaper, and how falling inference costs change what customers should expect from AI products.
Does your team use different AI agents? Here’s how to standardize your products.
If your team uses a mix of Cursor, Claude Code, and Copilot, things can get messy fast. In this article, we explain how to set up a system to standardize your products, keep your design system consistent, and ensure every AI agent plays by the exact same rules.
Everyone’s Talking About MCPs: Learn, Test, and Build Your First MCP Server
Learn what MCPs are, how AI tools interact with them, and how to build and test your own MCP server with a hands-on example.
Understanding AI Code Fast: A 60-Second Habit for Institutional Memory
Why teams using AI-generated code still need lightweight verification, and how a 60-second micro-review habit with git-lrc can build institutional memory without reading every line.
Locking Down Nomad: How to Implement ACLs and Secure Your Cluster
Nomad is a flexible workload orchestrator that enables an organization to easily deploy and manage any containerized or legacy application using a single, unified workflow. Nomad can run a diverse workload of Docker, non-containerized, microservice, and batch applications. With powerful features, it becomes very important to secure the Nomad cluster.
A New Method for Stable Software: Micro Code Reviews for the AI Era
Why AI-generated code needs lightweight verification, and how micro code reviews with git-lrc can improve software stability and developer comprehension.
How Python's GIL actually works (and when it bites you)
Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is free and source-available on Github. Star Us to help devs discover the project. Do give it a try and share your feedback for improving the product. I remember
The Subsidy Era Is Over: A Reality Check on AI-Powered Dev Tool Pricing
A reality check on AI-powered dev tool pricing, shrinking subsidies, workload-based costs, and predictable pricing for code review tooling.
Why Agentic Engineering Must Replace Vibe Coding
A critique of vibe coding and a case for agentic engineering built on verification, feedback loops, accountability, and engineering rigor for serious software systems.
Responsible Design: Shaping Large-Scale Consequences by Organizing Agents
A reflection on AI accountability, individual responsibility, and why careful design is the only viable way to shape outcomes in complex agentic systems.
Searching Billions in Seconds: How HNSW Solved the Scale Problem
Discover how HNSW solved the scale problem for Approximate Nearest Neighbor Search by creating a multi-layered graph system that can search through billions of items in milliseconds.
Recurrent Neural Networks (RNNs): 4 Ideas That Explain How They Actually Work
Understand the basics of RNNs, why they are needed, how they build memory, and their limitations.