Blogs
Tactics, patterns, and prep notes for coding rounds, system design, and behavioral interviews.
by Rohith Juluru
Apr 25, 2026
8 min read
Networking Scenario-Based Interview Guide for Software Roles
In-depth networking interview guide focused on networking scenario interview questions, real-world tradeoffs, and practical preparation strategy for software engineering interviews.
by Rohith Juluru
Apr 19, 2026
10 min read
Scalable Notification System Design for Interviews
In-depth system design interview guide focused on notification system design interview, real-world tradeoffs, and practical preparation strategy for software engineering interviews.
by Rohith Juluru
Apr 13, 2026
8 min read
Joins and Query Optimization Interview Questions You Must Master
In-depth dbms interview guide focused on sql joins query optimization interview, real-world tradeoffs, and practical preparation strategy for software engineering interviews.
by Rohith Juluru
Apr 7, 2026
10 min read
Process vs Thread Interview Guide: What Interviewers Expect
In-depth operating systems interview guide focused on process vs thread interview questions, real-world tradeoffs, and practical preparation strategy for software engineering interviews.
by Rohith Juluru
Apr 1, 2026
8 min read
DSA Patterns for Coding Interviews: The 80/20 Playbook
In-depth dsa interview guide focused on dsa interview questions, coding interview patterns, real-world tradeoffs, and practical preparation strategy for software engineering interviews.
by Rohith Juluru
Mar 20, 2026
11 min read
Production AI Systems: RAG, Evaluations, and Guardrails That Interviewers Respect
A practical framework for building and explaining production AI features in interviews. Covers retrieval-augmented generation, evaluation pipelines, guardrails, monitoring, and the tradeoffs hiring teams expect you to discuss.
by Rohith Juluru
Mar 5, 2026
10 min read
AI Coding Interviews in 2026: What Hiring Teams Actually Test
A deep guide to modern coding interviews in the age of GitHub Copilot, Claude Code, and agentic tools. Learn what interviewers now evaluate, how to answer AI project questions, and how to show strong engineering judgment.
by Rohith Juluru
Feb 18, 2026
9 min read
AI Impact Summit India 2026: Where Innovation Meets Real-World Scale
The AI Impact Summit India 2026 emerged as one of the most significant technology gatherings in the country’s recent history, positioning India at the forefront of global artificial intelligence conversations. Hosted in New Delhi, the summit brought together an influential mix of policymakers, global technology executives, startup founders, researchers, investors, and students — all united by a shared focus: transforming artificial intelligence from theoretical innovation into measurable, real-world impact. The event was not merely a technology conference; it functioned as a strategic platform aligning government vision, enterprise investment, and grassroots innovation. From keynote addresses by senior government officials to panel discussions featuring global AI leaders, the summit reflected India’s growing ambition to build a self-reliant, scalable, and globally competitive AI ecosystem. A major highlight of the summit was the emphasis on practical AI adoption across critical sectors. Rather than limiting discussions to large language models and generative AI hype, the sessions focused on tangible use cases in healthcare, agriculture, fintech, manufacturing, logistics, and public governance. Experts demonstrated how AI-powered diagnostics are accelerating early disease detection, how predictive analytics is supporting farmers with crop insights, and how intelligent automation is enhancing financial inclusion across rural and urban India. Infrastructure and compute capacity were central themes throughout the summit. Industry leaders discussed large-scale investments in AI-ready data centers, advanced GPU infrastructure, and domestic semiconductor partnerships to reduce reliance on external supply chains. Conversations revolved around building sovereign AI capabilities while maintaining interoperability with global platforms. The focus on infrastructure signaled a shift from experimentation to serious industrial deployment. The startup ecosystem also played a prominent role. Hundreds of AI-first startups showcased products ranging from conversational AI assistants to enterprise automation tools and robotics solutions. Government-backed initiatives were announced to map, support, and fund emerging deep-tech companies. Dedicated startup pavilions created opportunities for founders to connect directly with venture capitalists, enterprise buyers, and policymakers. The message was clear: India’s AI growth story will be driven not just by multinational corporations, but by domestic innovators solving contextual, region-specific challenges. Policy and governance discussions formed another critical layer of the summit. Panels explored ethical AI frameworks, data privacy concerns, algorithmic transparency, and the need for responsible deployment. Policymakers emphasized balancing innovation with safeguards, ensuring AI systems remain inclusive, secure, and unbiased. International delegates participated in dialogues about cross-border collaboration, standards alignment, and the future of global AI governance. These conversations reflected India’s intent to be an active contributor to global regulatory frameworks rather than a passive adopter. However, the summit was not without scrutiny. Media coverage highlighted operational challenges and isolated controversies that sparked debates about verification standards and representation in high-visibility expos. While such incidents drew attention, they also reinforced the importance of authenticity, accountability, and credibility in a rapidly expanding AI ecosystem. Beyond announcements and panels, the summit symbolized momentum. Public engagement was significant, with extended event hours due to overwhelming participation. Students, developers, and early-stage entrepreneurs gained exposure to cutting-edge research and real-world enterprise deployments. Workshops and technical sessions bridged the gap between theory and practice, equipping attendees with actionable insights. One recurring theme throughout the event was the transition from "AI experimentation" to "AI integration." Enterprises shared case studies demonstrating measurable ROI, productivity gains, and operational efficiency improvements achieved through AI adoption. The focus shifted from building isolated proofs-of-concept to embedding AI into core business processes. Another important dimension was talent development. Discussions addressed the urgent need to upskill India’s workforce in machine learning engineering, data science, AI ethics, and model deployment. Academic institutions announced collaborative programs with industry partners aimed at strengthening research pipelines and accelerating applied innovation. Ultimately, the AI Impact Summit India 2026 served as both a milestone and a signal. It marked India’s evolution from being a services-driven technology economy to aspiring toward leadership in AI product development, infrastructure ownership, and policy influence. The convergence of government backing, enterprise investment, startup innovation, and academic research demonstrated a coordinated push toward sustainable AI growth. For developers, the takeaway was clear: focus on building scalable, domain-specific AI solutions rather than chasing hype. For founders, the opportunity lies in solving real Indian problems with globally competitive technology. For policymakers, the challenge remains crafting regulations that encourage innovation while protecting public interest. In essence, the summit captured a defining moment — a shift from conversations about potential to conversations about implementation. It showcased India’s readiness to move beyond experimentation and into execution, shaping not only its own AI future but contributing meaningfully to the global artificial intelligence narrative.
by Neha
Jan 14, 2026
7 min read
The 30-30-30 Interview Prep Playbook
A structured 90-minute daily routine that balances fundamentals, practice, and review to build consistent momentum in interview preparation.