DEV Community: saurabh tripathi

Unemployed for a year in software testing. Sliding into depression. Here's how talking about AI in interviews finally got me hired — as a lead.

saurabh tripathi — Mon, 20 Apr 2026 17:35:34 +0000

"Karthik has been in software testing since 2014. Java, automation, Python, Robot Framework. A decade of hands-on experience.

He lost his job during a restructuring.

For one full year, he applied for roles. Different positions. Different companies. Different approaches. Nothing worked. Not a single offer.

He described what happened to his confidence during that year: it became very low. He started to feel like the field had closed to him permanently. He was thinking about applying for a loan. Starting a business. Doing anything else. Because the thought of continuing to try and fail in testing was becoming unbearable.

He said he was starting to feel depression.

A person with a decade of professional experience — genuinely afraid that his career was over.

WHAT CHANGED:

He came across an AI and skills workshop online. Initially skeptical. But he had time and nothing to lose, so he attended.

The session showed him something he had not considered: how AI tools could be integrated directly into software testing workflows. Not as a replacement for testers — but as a force multiplier for them.

Test plan creation. Documentation. Report generation. Structured analysis. Things that take hours, done in minutes with the right prompts and tools.

He started learning. He rebuilt his confidence slowly as he saw what was possible.

THE INTERVIEW THAT CHANGED EVERYTHING:

When he finally got an interview for a test lead position at a major tech company, he approached it differently.

He did not just present his background. He walked the interviewer through exactly how he would use AI in the role — as a lead:

→ Using AI to write and refine test plans for complex features
→ Generating documentation that previously took days, in hours
→ Creating structured weekly reports automatically
→ Teaching junior team members to use these tools so the whole team becomes more efficient

He was interviewing for a leadership role. The interviewer was evaluating whether he could think at a systems level — not just execute tasks himself, but elevate an entire team.

Demonstrating a clear, specific vision for how AI would make his team better answered that question directly.

The interviewer was very impressed.

He got the offer. Lead position. A step UP from where he was before losing his job.

THE BIGGER PICTURE:

Karthik is 35. He described looking at the next 20 to 25 years of his career and feeling, for the first time in over a year, that it was navigable.

That shift — from fear and depression to genuine orientation — might be the most valuable thing he gained from the entire experience.

The tools are real. The results are real. And sometimes, what looks like a career crisis is actually the moment just before things turn around.

▶️ Watch Karthik's full story: https://youtu.be/A054oeWnDEw?si=_vKG6Yg0txTuWBrA"

My bank was about to lose a ₹252 crore government deposit bid. I had 10 minutes and an AI tool. Here's what happened.

saurabh tripathi — Sun, 19 Apr 2026 17:42:49 +0000

"There is a moment in competitive bidding when the room goes quiet. Usually it means someone has lost.

Deepak works in a public sector bank in Navi Mumbai. His bank was pitching for a government deposit worth ₹252 crore. A rival bank — Union Bank of India — suddenly quoted 17 paise more than them in the middle of the bidding.

Everyone in the room assumed it was over. Other banks conceded.

Deepak asked for 10 minutes.

WHAT HAPPENED IN THOSE 10 MINUTES:

Deepak had recently learned how to use AI tools properly — not just asking generic questions, but feeding real data and getting real analysis.

Here is exactly what he did:

Step 1: He pulled publicly available deposit rate data from peer bank websites. These websites are open to anyone. The data was always there. What Deepak now had was the ability to process it quickly.

Step 2: He fed that data into the AI tool and asked it to compare the rates, identify the structure of the rival bank's offer (non-callable deposits with cumulative quarterly reinvestment — which artificially inflates the headline rate), and generate a clear comparison chart.

Step 3: Ten minutes later, he had a visual analysis showing that his bank was offering 9 to 10 paise MORE than Union Bank on a genuine like-for-like basis.

He presented the chart to the panel.

His bank won the bid.

The difference in returns to the government of India: approximately ₹40 to ₹50 lakhs.

WHAT THE AI DID AND DID NOT DO:

The AI did not understand banking. It did not know what a non-callable deposit was. It did not know why cumulative reinvestment inflates a headline rate.

Deepak knew all of that. He is a banker with years of domain experience.

What he did not have before — was the ability to process and present that understanding fast enough to matter in a live, time-pressured bidding room.

The AI compressed what would have been two hours of manual spreadsheet work into ten minutes. Deepak's expertise directed what the analysis should look at and what the result meant.

That is the partnership. Domain knowledge tells the AI what to look for. The AI does the work at a speed human effort alone cannot match.

HOW DEEPAK LEARNED THIS:

He saw an ad on Instagram while scrolling. Registered for a ₹99 introductory session. Listened to classes on his phone during his daily commute on the Mumbai local train.

A public sector banker. Commuting through Mumbai. Learning on a phone. Applying that knowledge in a live bidding room. Winning ₹50 lakhs for the government.

The barrier to learning these tools is not high. The returns to learning them can be extraordinary.

You cannot beat that ROI.

▶️ Watch Deepak's full story: https://youtu.be/AEgotMPXQ-0?feature=shared"

I attended 15 interviews over 5 years and never made it past the first round. Here's what finally changed.

saurabh tripathi — Sat, 18 Apr 2026 16:52:15 +0000

"For 5 years, Ragendra — a mechanical engineer with 13 years of experience in product design and manufacturing — could not crack a single second round interview.

Not once. Out of 10 to 15 attempts.

Think about that for a moment. 13 years of real, hands-on experience. Product development from concept to customer. Design, manufacturing engineering, vendor coordination, process capability improvement. A bachelor's degree in mechanical engineering. A master's degree in progress.

And yet — rejection after rejection after rejection.

Here is the thing nobody tells you: the problem was never his experience. It was how that experience was being communicated.

WHAT HE CHANGED:

He started using AI tools — primarily ChatGPT and Gemini — to rebuild his resume from scratch. Not to fabricate anything. Not to exaggerate. But to translate his real experience into the language that hiring managers in his target roles were actually looking for.

The process was simple but powerful:
→ Take the actual job description
→ Feed his real responsibilities and achievements into the AI
→ Ask it to reframe and restructure the content to match

The result was a resume that felt targeted, current, and specific — rather than the same generic document he had been carrying around for years.

He did the same for his LinkedIn profile. Summary, headline, project descriptions — all rewritten with AI assistance to speak directly to the roles he wanted.

Within TWO MONTHS of applying this approach consistently, he got selected.

Same experience. Same qualifications. Completely different outcome.

WHAT MAKES THIS STORY POWERFUL:

Ragendra said something that stuck with me: he estimates he is using maybe 15 to 20 percent of what AI can actually do. That number represents his current ceiling — and yet that 15 to 20 percent was enough to end a five-year losing streak.

He also started using AI for his medical reports. It suggested a diet plan and morning walk routine. He changed his routine. He started waking up earlier. He has followed the plan for weeks.

Same tool. Completely different domain. Same principle: give it good context, ask a precise question, act on the output.

THE LESSON:

Most career advice focuses on what to do — update your resume, network more, practice interviews. All correct. None of it explains why smart, experienced people still fail to get through first rounds.

The real answer is simpler and harder to hear: the way you are describing yourself is not connecting with the people reading about you.

It is not a skills problem. It is a translation problem.

AI is very good at translation.

Five years is a long time to wait before discovering that.

▶️ Watch Ragendra's full story here: https://youtu.be/ntkF2tImt4Y?si=moe_IoXQW320zg8B"