Shuru » Large Language Model

Rails Authentication with OmniAuth: A Practical Guide (GreyMonk)

OmniAuth, Agentic AI, AI, AI tools, Authorisation, OAuthSeptember 12, 2025219Views 1Like 0Comments

Developers work with many tools nowadays, from git hosting providers like GitHub/Bitbucket to task management tools like Jira/ClickUp to communication platforms like Slack/Teams to AI IDEs/Agents like Cursor/Claude Code/GitHub Copilot etc and countless other development tools. With work spread across so many tools, analytics, reporting & insights are also fragmented, making it hard for engineering…

How to Measure Engineering Team Performance – Introducing GreyMonk

AI, AI tools, Analysis, Large Language Models, Software EngineeringSeptember 11, 2025376Views 0Likes 0Comments

Objective engineering analytics that leaders and teams actually use Start line and Current Position Two years ago we pivoted. We stopped running a B2C product and doubled down on what we do best: building technology products. From day one we solved client problems from first principles. Early on we noticed the industry talks in boxes…

OpenRouter experiment Phase 1: Power Users – How Our Top AI Developers Really Work

Agentic AI, AI tools, Claude Code, Claude Opus, Claude Sonnet, CLine, Cohort Analysis, Context Engineering, Gemini 2.5, GitHub CoPilot, Large Language Models, OpenRouter, OpenRouter, Prompt Engineering, Research and Development, Roo Code, Software EngineeringJuly 8, 20254KViews 0Likes 3Comments

What happens when engineers get total freedom to pick and choose their own tools from a credits-based, model-agnostic AI stack? In Project Reboot’s latest experiment, we allocated OpenRouter credits – matching the value of a monthly Copilot seat – to a randomly selected group of participants, with Copilot left in place as a safety net.…

Mapping the AI Terrain: A Deeper Dive with Cohort-based Developer AI usage analysis

Agentic AI, AI, Analysis, Cohort Analysis, Large Language Models, Research and DevelopmentJune 23, 2025797Views 0Likes 2Comments

In our first post, we shared high-level insights from our AI usage survey across the engineering department at Shuru. But averages can be misleading. To truly understand how AI is impacting developer workflows, we’re diving deeper — by slicing the data into cohorts. This post outlines our approach to cohort-based analysis, how we plan to…

Project reboot – A new default

AI, Agentic AI, AI tools, Analysis, Creative, Generative AI, Large Language Models, Research and Development, Software EngineeringJune 16, 20252KViews 0Likes 3Comments

Project Reboot – A new default is Shuru’s internal initiative to reshape how teams engage with AI in software development. As AI tools become ubiquitous, their adoption across teams remains uneven. With this series, we’re not just trying to change that – we’re committing to doing it in public. From tool usage data across our…

Intro to Transformer Models: The Future of Natural Language Processing

Generative AIJune 20, 20232KViews 1Like 5Comments

The accomplishments of large language models are attributed to the architecture that they follow – Transformer Models

Simple and Effective LangChain Guide to Get Started

Generative AIJune 19, 20237KViews 2Likes 1Comment

At the core of LangChain lies the concept of chaining different components together to tackle complex problems using LLMs. These chains can consist of multiple components sourced from various modules within Langchain.