Nikita Khandelwal

As a Sr Principal in Search at Amazon collaborating with product managers, marketers, finance teams and operations specialists across the company, I've witnessed how technical barriers sometimes limit what talented people can accomplish. For years, automation was reserved for "tech-y" people with coding skills. Even simple tasks like analyzing data, creating reports, or automating workflows required knowledge of programming languages, APIs, and system commands. SQL is just one notorious example - a dark art requiring intimate knowledge of database schemas and complex joins. These technical barriers have kept productivity tools locked away from the people who need them most. This is changing dramatically with AI tools (like Amazon Q CLI. and others) The profound shift? Natural languages, like English, are becoming programming languages. These new AI tools aren't just generating text like old-school chatbots and Large Language Models (LLMs). They're agentic systems that execute tasks, interact with systems and applications, and adapt when things fail. What is an AI script? It's a reusable prompt with parameters – a template where you define what you want done once, then change specific values each time. Example: monthly_business_review.qscript with content "Pull updates for OKRs owned by {team_name}, summarize wins/misses, highlight areas for leadership input, suggest questions for the team to prepare for." You can run this script monthly like this: q chat "Run script monthly_business_review.qscript with parameters with team name: Consumer Products" Another example - simplify data access: q chat "Show me conversion rates for landing page visitors last month by traffic source" Behind the scenes, the AI figures out what to do - whether generating SQL, writing and running Python code, pulling data from internal websites, using tools, or processing files. Through conversation, and without programming, marketing managers, product owners, and executives can directly automate tasks. These scripts are: reusable and shareable across team members, self-documenting in plain language, and easily movable across operating systems. To take full advantage of this shift, organizations need proper infrastructure: internal-tool integrations with AI (for example, via Model Context Protocol), SQL data connectors, and authentication frameworks. The AI-driven democratization of automation has profound implications. Domain expertise, not programming skill, becomes the limiting factor in improving productivity. What could your team accomplish if coding wasn't a barrier? What would you automate? The answer might reshape how we all work. #AI #Productivity #FutureOfWork

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A colleague told me they admire how I openly disagree with my manager. I hadn’t thought of it as rare. I just say what I believe is true, respectfully and directly. I’ve tried to practice that since I started as a junior engineer. At Amazon, there’s even a principle for it: Have Backbone; Disagree and Commit. But having a principle, on a topic like this, doesn’t always guarantee people feel safe using it. I’ve mostly been lucky. I’ve had leaders who made that possible. Backbone matters. But without safety, it will bend. If you’re in a position of power, create the space. If you don’t, people stop telling you the truth.

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My thoughts on why so many Tech Layoffs are happening now. We keep hearing that AI is automating jobs out of existence, but that’s only half the story. In reality, what we are seeing is the aftermath of massive capital investment. Over the past couple of years, tech giants have poured billions into AI infrastructure GPUs, data centers, training clusters, all of it. That’s serious capital. And when you spend that much, you still have to show growth and profitability every quarter. The result? A brutal round of internal reprioritization. Only “cash cow” products and high-ROI bets are being kept alive. The nice-to-have or long-horizon projects are being quietly shelved. And when those projects go, so do the teams behind them. These rounds of layoffs isn’t just about automation. The cost of chasing AI innovation has to come from somewhere.

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I am an able-bodied son of a general category middle-class family. So when people talk about the challenges some face due to reservations and gender diversity hiring, I lie on the sweet spot of that most disadvantaged intersection in the Venn diagram. But through the years studying and working, I understood why we need affirmative actions for education and the workplace. To the people who feel that movements like reservations and feminism are sham, I'd like to present two anecdotes to you: 1. A person whom I know closely was forced out of her job, citing poor performance, when the rest of the team was all male. The other female employee who joined the team after the former left was also treated badly and left the team soon after. There was no harassment or explicit mistreatment, but there were signs of subtle sexism when working with colleagues who often tended to ignore requests for help or the doubt on quality of work provided by female members. 2. In my college, a junior approached me for help as he was struggling in his studies. The situation was worsened by the fact that, as he was coming from a reserved category, his batchmates maintained a distance in interactions. They weren't discriminatory, but just uncomfortable interacting with the person and therefore avoided close ties. From these incidents, I learnt how it's necessary to promote people in places where the stereotype doesn't want them to be. It is important to push for breaking norms even if the general public is non-discriminatory. You might not care about the rights of minorities today, you're neither for nor against them, but your lack of empathy will be taken as tacit support for discrimination and persecution today and in the future. When I see people arguing over how the draconian laws ruin men's lives over divorce settlements, I agree with them, but just for a particular case. To think that all men are suffering is a laughable rhetoric, and we have enough statistical evidence to prove otherwise. And so is the case for every discussion on how some minorities are being given benefits in society. There are some cases of exploitation, but there are also cases where rules promoting the rights of minorities are needed to protect them from exploitation. This is my serving of "food for thought" for you. #education #workplace #justice #equality 

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✨ This week marks my last working week at Intuit ✨ As I wrap up a truly transformative chapter of my career, I find myself reflecting on all that I’ve learned. I’m deeply grateful for the opportunities, the people, and the growth. There’s so much I could share, but here are a few key lessons that will stay with me: 1. You own your career No one will care about your growth more than you. Managers and mentors can guide you, but you're in the driver's seat. Ask for what you want. Seek the teams and work that energize you. Build your own path. 2. Build your brand—champion others and have your champions Your work and reputation speak when you're not in the room. Invest in your professional brand. Lift others up and surround yourself with people who do the same for you. 3. If you want another team to do something, show how it helps them Collaboration thrives when goals align. Frame your ideas around what matters to others. Speak their language and solve their problems—it makes all the difference. 4. Have a mentor A great mentor can shift your trajectory. Whether it’s advice or advocacy, mentorship matters. (Bonus: be one too.) Some of the advice I received that changed my thinking: * Say thank you for any feedback—even if it’s negative—because they took the time to give it, and they care. * Listen more and speak up when necessary. * Don’t be arrogant, even if you know something well. 5. Do great work, then move on Celebrate wins, learn from them, and keep moving. Growth comes from delivering consistently and stepping into new challenges—even the uncomfortable ones. 6. Stay relevant—keep learning Tech moves fast. Business faster. Stay curious. Read, code, build, talk to smart people. Always be in learning mode. 7. Don’t be afraid to challenge—but do it with kindness Some of my most meaningful moments came from asking tough questions. But how you challenge matters—humility and empathy go a long way. 8. Appreciate others—recognize great work Spotlight (non-cash) awards are a beautiful Intuit tradition. I gave and received many, and each made an impact. Recognition builds culture and confidence. Use it. To everyone I’ve worked with, collaborated with, and learned from—thank you. Excited for what’s next. Let’s stay in touch! 🚀 #newbeginnings #careergrowth #farewell #techlife #Intuit #careerlessons #grateful

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