🚀 Tech Hiring in 2026 — What Recruiters Actually Want

📍 The Big Picture

Stat	What it tells you
AI skills now appear in 73% of U.S. tech job postings (May 2026), up from 29% a year earlier	AI fluency is no longer a bonus skill — it's the baseline
45% of companies have dropped degree requirements for key tech roles	Skills are beating brand names — but only if the skills are real
Applications per job posting: 32 (2023) → 56 (2025)	More competition per role, even with hiring rising
3,300+ active India job listings explicitly require strong DSA	DSA isn't dying — it's still the first gate at every product company
India's active tech openings fell ~24% YoY in early 2026 (Xpheno), while AI/ML hiring grew 40–50% in the same period	The market isn't shrinking — it's redistributing toward AI-fluent talent
India's AI talent demand is set to cross 1 million roles by 2026, against a 53% AI skill deficit	Genuine opportunity for anyone who closes that gap early

🧠 Why This Happened (in one line each)

The hiring frenzy ended. 2020–22 forgave weak interviews. 2025–26 doesn't.
AI rewired how code gets written. Google's Sundar Pichai confirmed (April 2026) that 75% of new code at Google is AI-generated, up from 50% just six months earlier.
AI then rewired how candidates get evaluated. Companies stopped asking "can you avoid using AI?" and started asking "can you use it well?"
Skills-based hiring tripled in 2 years — and skills-based hires are reportedly 30% more productive in their first 6 months (McKinsey).

1️⃣ DSA Didn't Die. It Changed Shape.

DSA is still the non-negotiable gate at every Indian product company — Flipkart, Razorpay, Swiggy, Zepto, Meesho, CRED. Skipping it to "go all-in on AI projects" caps you at service-company offers, not product roles.

Used to be tested (2021–23)	Tested now (2025–26)
Solve a fresh puzzle from scratch	Read and debug an existing, broken codebase
Optimize a clean algorithm	Extend a partial multi-file solution
Whiteboard from zero	Spot logic flaws in someone else's code
Speed of typing	Speed + understanding + explaining out loud

Do this:

150–200 well-chosen problems across 15–20 patterns beats 500 random ones
Practice explaining your solution out loud, not just solving it
Add "code reading" reps — read unfamiliar code and explain what it does
Pick one language and stay consistent: Python (cleanest), Java (Indian IT favorite), C++ (CP background)

Reality check: Karat's 2026 Engineering Interview Trends report found 80–90% coding-round failure rates are common across the industry right now. The bar moved — your prep needs to move with it.