The Services-to-Product Transition Kit (7-in-1)

You're technically good. Product companies keep rejecting you anyway. You don't know why.

Maybe you're a Data Engineer at TCS, Infosys, Wipro, or Capgemini. Maybe you're an SDE trying to move into DE or MLE. Maybe you're at a startup where you own everything but your resume shows nothing. Different starting points, same wall: you apply to Flipkart, Razorpay, or a FAANG GCC, and you get silence or "not the right fit."

Here's what's actually happening: your resume isn't reaching a human, your positioning doesn't read the way the room needs it to, and you have no idea what actually got said about you behind closed doors. This kit fixes all of it, whichever door you're walking in from.

What's inside:

1. DE Resume Template, India Edition. A resume structure built for Indian product companies, with fill-in guidance so you're not staring at a blank page. GET IT

2. Services-to-Product Translation Playbook. The language shift from "I was assigned to build X" to "I decided we needed X, here's what it enabled." The single biggest signal that separates services DEs who get offers from services DEs who don't. GET IT

3. The DE Debrief Phrasebook. A decoder for the 30 most common rejection phrases in DE interview loops, what the interviewer meant, what triggered it, and the fix. GET IT

4. The DE→MLE Pivot Guide. If your last few loops point to a structural mismatch, not a one-round fix, this maps whether staying in DE or pivoting to MLE gets you to an offer faster. GET IT

5. The "Too Technical" Fix Guide. For SDEs specifically: decodes the feedback that sounds like a compliment ("too technical," "too in the weeds") and shows the exact reframe that fixes it. GET IT

6. The Startup-to-FAANG Resume Translator. For startup DEs specifically: turns real, high-ownership work that was never formally measured into numbers a Big Tech screener can actually judge, without inflating anything. GET IT

7. AI/ML Engineer Positioning Guide. For engineers who've already shipped real production ML systems: the translation framework, vocabulary swap, and interview signals for candidates whose resume sounds like a research paper instead of a product engineer's. GET IT

Who this is for:

• Data Engineer at a services company (TCS/Infosys/Wipro/Capgemini), 3-7 YOE, targeting product companies
• SDE moving into DE/MLE, getting "too technical" or similar feedback
• Startup DE targeting Big Tech or a FAANG GCC, resume undersells real ownership
• Technically solid in all three cases, the gap is positioning and signal, not skill

Who it's not for:

• You already know exactly what's wrong and have a fix in progress
• You want coding/SQL interview prep specifically, that's the Active Looper Kit
• You're targeting services companies, not product companies

Why this, not free advice: every phrase in the Debrief Phrasebook comes from being inside debrief rooms. The positioning shifts across all seven guides come from reviewing 10,000+ resumes and watching which ones get an offer, across every background this kit covers. This is the view from the other side of the table, not a guess from outside it.