🎙️ Software Engineer at Microsoft | College, AI, Networking, Linkedin, CV & Hiring | Chandan Agrawal

Interview & DSA preparation: practice beats “guarantees”

• He strongly rejects the idea that a fixed number of DSA problems (e.g., “only 1000/1500”) can guarantee placement.
• Core belief: consistency + solving problems improves your odds, but no one can guarantee outcomes.
• He shares his own progress track (hundreds/thousands of LeetCode-style problems plus contest/test participation) to highlight that real improvement comes from sustained practice—not shortcuts.
• He cautions against planning to do only “X questions” without mastering underlying patterns/concepts.
  • He mentions structured sheets like Striver’s A-to-Z as a base, but stresses actually doing them properly rather than treating them as “just 300 questions”.

How to prepare while working (and why office work can hurt)

• He argues that working in-office after a shift can leave people too exhausted to prepare, reducing study progress compared to remote/WFH periods.
• He notes that during COVID and after (in his case at Microsoft / previously Infosys), WFH helped because he had more mental energy and time for study.
• Practical habits he recommends for working candidates:
  • Keep digital notes for quick revision.
  • Use short daily learning on mobile/apps (he specifically recommends GFG).
  • Break video lessons into small chunks (e.g., replaying short segments during commute).
  • Use weekends for longer focused blocks (e.g., roughly 5 hours per day, as an example).

Job switching & motivation: money matters, but plan the risk

• He discusses switching from companies like Infosys to Microsoft/Google/Amazon:
  • It’s possible, but you need planning, especially around notice periods and timing.
• Motivation: financial commitments (e.g., EMIs, loans, family responsibilities) often drive consistency and follow-through.
• Pragmatic view: even if a company offers a better package, they may not always match expectations—so choose opportunities based on reality, not hype.

LinkedIn referral strategy: polite, direct messaging, and follow-through

A major portion focuses on improving referral success on LinkedIn.

Why referrals often fail

• People receive many messages and may not notice yours.
• Even if they open it, only a small fraction will review resume details, and fewer will actually take action.

Recommended approach

• Contact many people, but do it properly and politely.
• Use point-to-point messaging:
  • Avoid overly casual “hi brother…” style chat.
  • Don’t pretend you already know them well.
• Include the essential details clearly:
  • Your background, relevant skills/experience, the role you want, and job ID/link context.
• Share resumes via Google Drive links (instead of downloading to someone’s phone).

Referral etiquette

• If someone already referred you:
  • Thank them and avoid repeatedly asking other people unnecessarily.
• If you asked for a referral and later learn another colleague already referred you:
  • Acknowledge it politely and avoid redundant follow-ups.

College preparation: CS fundamentals + communication

Don’t over-focus only on DSA

• He criticizes neglecting core CS fundamentals like:
  • Networks
  • DBMS
  • Operating Systems
  • Computer Architecture (and SQL)
  • Plus role-relevant subtopics (e.g., networking concepts for networking roles)

Improve corporate visibility

• He emphasizes presentation and group discussion skills.
• He claims many students become weak in corporate visibility because they skip presentations/bunk group discussions.
• Promotions and managerial perception can depend heavily on how visible and articulate you are, not just raw effort.

Face-to-face vs virtual interviews: trade-offs, and cheating affects difficulty

• Virtual interviews
  • More constrained and less visibility into body language.
  • Discussion still matters, but the setting changes.
• Face-to-face interviews
  • Less opportunity to cheat.
  • More direct observation of confidence and behavior.

He also argues:

• Companies may increase OA/online difficulty because cheating tools (e.g., GPT/automation) reduce fairness.
• Best preparation remains understanding approach/logic—not only memorizing solutions.

Language switching & transferable concepts

• DSA concepts are not tied to a single language:
  • Syntax differs across C++/Java/Python, but the underlying data structures and algorithms remain the same.
• He shares that he switched languages across roles (e.g., using C++ concepts in Java roles) and notes that IDE features/autocomplete reduce the need to memorize every syntax perfectly.
• Main message: learn fundamentals and problem-solving logic so you can adapt to whatever language is used in the interview.

AI tools (GPT/Gemini) for learning: useful depth, not a replacement

• He supports using AI to explain topics and clear doubts (a “zero-to-hero” style).
• But he warns against misuse:
  • Dependency on AI without learning basics.
  • Reduced practice of core coding/CS concepts.

Suggested AI workflow:

• Ask for explanations starting from basics.
• Request examples.
• Ask follow-up questions until you understand the full flow.
• Use AI to generate structured learning artifacts (notes, diagrams/flowcharts).

Interview performance mindset: practice to reduce nerves, and discuss your approach

• Interviewers care about more than just correct code:
  • reasoning, approach, clarity, and trade-offs.
• He notes many candidates get nervous in big-company interviews, so mock practice helps.
• He advises against messy “over-brainstorming,” and instead communicate clearly and logically.

Presenters / contributors

• Chandan Agrawal — Microsoft software engineer (main speaker)