Build•8 min read
The Coding Agent Revolution: Why History Is Repeating Itself
AI coding agents echo the 2006 cloud shift - 84% of developers now use AI tools, yet 46% distrust the output. A practitioner's take on Claude Code vs Gemini.
AI Guru Team
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Build
Technical deep dives into AI systems, algorithms, and hands-on engineering guides.
Build•5 min read
Introducing Plan — Strategic Analysis in Hours, Not Weeks
Plan turns weeks of strategic analysis into hours - 8 frameworks, 15+ AI agents, and live market data built to cut the busywork around real strategic thinking.
AI Guru Team
Build•4 min read
I Built an AI for People Who Hate Writing Emails
How a 7-day build produced DraftEmail, an AI tuned for professional email with a Chrome extension and templates - 500 beta users save 5+ hours a week.
AI Guru Team
Build•7 min read
Beyond the Paycheck: How Agentic AI Is Transforming Total Rewards
Fragmented data and one-size-fits-few programs leave Total Rewards underdelivering. How agentic AI unifies systems and personalizes rewards for HR leaders.
AI Guru Team
Build•2 min read
Rethinking Clinical Documentation with AI
Physicians spend 34-55% of their day on notes, costing $140B yearly. How ambient clinical documentation cuts that up to 70% and eases clinician burnout.
AI Guru Team
Build•22 min read
AI Agents Come of Age: How Enterprises Are Driving Real Value in 2025
Enterprise AI agents now deliver 30-40% efficiency gains via multi-agent setups like Moody's 35 specialized agents, defense-in-depth controls, and oversight.
AI Guru Team
Build•4 min read
AI in Action: The Evolution of Sales Analytics
Three waves of sales AI from basic automation to integrated intelligence, with results like Clay's 312% response lift and Klarna scaling 700 agents of work.
AI Guru Team
Build•6 min read
Fast Inference in Generative AI: A Game Changer
Generative AI inference feels slow due to sequential token generation and memory bandwidth limits - even an H100 3.3 TB/s falls short of 1,000 tokens/sec.
AI Guru Team
Build•5 min read
Revolutionizing Education Through Multisensory AI
How multisensory AI tailors learning to each student with video, audio, and interactive content, and grades work through speech, presentation, and feedback.
AI Guru Team
Build•4 min read
Meta's Llama 3.1: Democratizing AI
Meta's Llama 3.1 405B is the first open-source model rivaling GPT-4o and Claude 3.5, leading GSM8K math at 96.8, with 128K context across the upgraded family.
AI Guru Team
Build•4 min read
Prompt Engineering: The Key to Effective Generative AI
A prompt is the fundamental building block of generative AI - the context and instructions that guide a model's output. What prompts are and why they matter.
AI Guru Team
Build•3 min read•Beginner
Understanding Algorithms: Beginner Level
Learn what algorithms are through simple analogies and everyday examples that everyone can understand.
AI Guru Team
Build•3 min read•Intermediate
Understanding Algorithms: Intermediate Level
How algorithms drive business operations, including real industry applications and measurable ROI examples.
AI Guru Team
Build•4 min read•Beginner
Understanding Artificial Neural Networks: Beginner Level
A beginner-friendly introduction to neural networks using simple analogies and everyday examples.
AI Guru Team
Build•5 min read•Intermediate
Understanding Artificial Neural Networks: Intermediate Level
How businesses leverage neural networks for pattern recognition and complex predictions.
AI Guru Team
Build•6 min read•Technical
Understanding Artificial Neural Networks: Technical Level
Technical deep-dive into artificial neural networks, architecture design, and implementation best practices.
AI Guru Team
Build•4 min read•Beginner
Understanding Batch Learning: Beginner Level
Learn batch learning through simple analogies - how AI systems train on big groups of data at set times.
AI Guru Team
Build•6 min read•Intermediate
Understanding Batch Learning: Intermediate Level
How businesses use batch learning for scheduled model training and predictions.
AI Guru Team
Build•5 min read•Technical
Understanding Batch Learning: Technical Level
Technical guide to batch learning paradigm, implementation strategies, and performance considerations.
AI Guru Team
Build•4 min read•Beginner
Understanding Big Data: Beginner Level
A beginner's guide to understanding big data - the massive information powering modern AI.
AI Guru Team
Build•5 min read•Intermediate
Understanding Big Data: Intermediate Level
How enterprises leverage big data for business insights and competitive advantage.
AI Guru Team
Build•5 min read•Technical
Understanding Big Data: Technical Level
Technical guide to big data technologies, architecture, and processing strategies.
AI Guru Team
Build•3 min read•Beginner
Understanding Classification: Beginner Level
An easy introduction to classification in AI, with everyday examples and helpful analogies.
AI Guru Team
Build•3 min read•Technical
Understanding Classification: Technical Level
Technical guide to classification in machine learning, including system architecture, implementation, and best practices.
AI Guru Team
Build•4 min read•Beginner
Understanding Clustering: Beginner Level
Learn clustering through simple analogies - how AI naturally groups similar things together.
AI Guru Team
Build•4 min read•Intermediate
Understanding Clustering: Intermediate Level
How businesses use clustering to understand customers and markets, with real industry applications.
AI Guru Team
Build•4 min read•Technical
Understanding Clustering: Technical Level
Technical deep-dive into clustering algorithms, implementation strategies, and performance optimization.
AI Guru Team
Build•4 min read•Beginner
Understanding Computer Vision: Beginner Level
Learn how computers can see and understand images - a beginner-friendly introduction to computer vision.
AI Guru Team
Build•5 min read•Intermediate
Understanding Computer Vision: Intermediate Level
How businesses use computer vision to automate visual analysis and improve operations.
AI Guru Team
Build•4 min read•Technical
Understanding Computer Vision: Technical Level
Technical guide to computer vision algorithms, system architecture, and implementation best practices.
AI Guru Team
Build•4 min read•Intermediate
Understanding Datasets: Intermediate Level
How datasets power business decisions, with industry applications and measurable business benefits.
AI Guru Team
Build•5 min read•Beginner
Understanding Generative AI: Beginner Level
Learn what generative AI is through examples and analogies - the technology creating art, music, and text.
AI Guru Team
Build•6 min read•Intermediate
Understanding Generative AI: Intermediate Level
How businesses leverage generative AI for content creation, design, and product innovation.
AI Guru Team
Build•8 min read•Beginner
Introduction to Large Language Models
How LLMs work, what they can do, and how Indian enterprises are deploying them for real business impact.
Ritesh Vajariya
Build•5 min read•Beginner
Understanding Large Language Models: Beginner Level
A beginner-friendly introduction to large language models - the AI behind ChatGPT and similar tools.
AI Guru Team
Build•6 min read•Intermediate
Understanding Large Language Models: Intermediate Level
How businesses leverage large language models for content, automation, and business operations.
AI Guru Team
Build•5 min read•Technical
Understanding Large Language Models: Technical Level
Technical deep-dive into transformer architecture, training, and deployment of large language models.
AI Guru Team
Build•4 min read•Beginner
Understanding Machine Learning: Beginner Level
A beginner-friendly introduction to machine learning concepts through everyday analogies.
AI Guru Team
Build•5 min read•Technical
Understanding Machine Learning: Technical Level
Technical comprehensive guide to machine learning algorithms, techniques, and best practices.
AI Guru Team
Build•5 min read•Beginner
Prompt Engineering 101
Practical prompt engineering techniques that work across ChatGPT, Claude, and Gemini.
Ritesh Vajariya
Build•6 min read•Technical
RAG Architecture: Building AI Apps with Your Data
A technical guide to Retrieval Augmented Generation for enterprise applications.
Ritesh Vajariya
Build•3 min read•Beginner
Prompt Engineering 101 — How to Get Useful Results from AI
The beginner's guide to writing AI prompts that work — a four-element framework with before-and-after examples.
AI Guru Team
Build•3 min read•Beginner
Beyond the First Try — How to Refine AI Outputs Like a Pro
Why your first prompt is a starting point, not a final answer — three techniques for iterative refinement that save time.
AI Guru Team
Build•4 min read
Governing AI System Design — From Use Case to Architecture
A practitioner's guide to governing AI system design from use case to architecture, with feasibility, risk/benefit analysis, and knowing when not to build.
AI Guru Team
Build•5 min read
AI Data Governance — Training Data, Quality, Bias, and Documentation
Governing AI training data in practice - consent and legality, quality dimensions, sources of bias, and cross-border challenges, grounded in NIST and EU rules.
AI Guru Team
Build•4 min read
Model Cards, Datasheets, and AI Documentation — What You Need and Why
What model cards and dataset datasheets should document - intended use, limitations, metrics, ethics - and how to match documentation rigor to system risk.
AI Guru Team
Build•5 min read
AI Testing and Validation — Beyond Accuracy Metrics
A model can be 95% accurate overall yet 60% for one demographic - why testing needs the TEVV framework, disaggregated evaluation, and fairness analysis.
AI Guru Team
Build•4 min read
AI Release Readiness — From Lab to Production
A release readiness checklist for moving AI from lab to production - validated performance, bias and fairness testing, security, and stakeholder sign-off.
AI Guru Team
Build•4 min read
Continuous AI Monitoring — Drift, Degradation, and When to Retrain
Data drift, concept drift, and model drift all degrade AI in production. How teams catch decline early with segment metrics and decide when to retrain a model.
AI Guru Team
Build•4 min read
Evaluating AI for Deployment — Build vs. Buy, Cloud vs. Edge
Match build-vs-buy and cloud-vs-edge decisions to risk using NIST AI RMF, the EU AI Act, and OECD principles - practitioner guidance for governance teams.
AI Guru Team