How Productive AI Is Rewiring Competitive Analysis for Smarter Building

Summary

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Podcast Summary: Lead With AI

Episode: How Productive AI Is Rewiring Competitive Analysis for Smarter Building

Host: Dr. Tamara Nall
Guest: Adithya Sharma (Founder, Productive AI)
Date: March 24, 2026

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Episode Overview

In this episode, Dr. Tamara Nall welcomes Adithya Sharma, the founder of Productive AI, to discuss how AI-driven tools are changing the landscape of competitive analysis for developers and founders. They explore the origin story of Productive AI, how it accelerates and deepens competitive research, ethical considerations in AI-powered development, and what the future holds for builders leveraging AI. The episode maintains a conversational and enthusiastic tone, spotlighting practical insights and real-world use cases.

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Key Discussion Points and Insights

1. The Origin and Purpose of Productive AI

• Adithya’s Background and Motivation
  • Adithya describes himself as a “problem solver,” whose experience as a founder revealed the inefficiencies of traditional competitive analysis—days lost to manual searches, spreadsheets, and bookmarks.
    • Quote (02:25):

      “Founders spend days doing competitive analysis. They were googling alternatives, bookmarking tools and making spreadsheets. I thought what if AI could do that thinking for you in seconds.” — Adithya Sharma

  • Productive AI was built to automate this process—streamlining research while empowering founders to focus on building rather than tedious hunting.

2. How Productive AI Works

• Functionality for Builders
  • Users input a product description and relevant tags. The platform searches across open-source projects (particularly on GitHub) to find similar initiatives, providing:
    • Feature-level comparisons
    • Details on competitors’ features vs. your own
    • Links to open repositories for code and inspiration
  • Quote (03:24):

    “You can just insert the description of your product and tell the tags that your product has...it will go and do AI based searching...and show you the similar projects that are available on GitHub...you can just use them in your projects.” — Adithya Sharma

Key Segment: How Productive AI Surfaces Useful Insights

• Timestamp (04:32):

  “It will do a competitive analysis and it will give you the level of correctness or the similarity that your product has and that the GitHub project has...It will also tell you that the features that your product has but that project doesn't have and vice versa.” — Adithya Sharma

3. Intellectual Property & Ethical Considerations

• Productive AI focuses solely on open-source code, sidestepping copyright or IP issues.
  • Quote (05:22):

    “Just because you are using GitHub, so the projects are open source, so I think that saves you a lot. So there will be no problem using the open source projects.” — Adithya Sharma

• Emphasizes that AI should “augment thinking and not replace it.” The tool avoids training on private user data without consent, and maintains human control at each decision point.
  • Quote (10:28):

    “AI should augment thinking and not replace it… We don't train on private user data without consent and we design the product to teach users how to think better, not blindly follow suggestion.” — Adithya Sharma

  • Dr. Nall responds with appreciation for this principle:
    • Quote (11:09):

      “Oh, I love that. I absolutely love that.” — Dr. Tamara Nall

4. Real-World Impact and User Stories

• The “Jaw-Dropping” Value Propositions

  • Founders using Productive AI are amazed by the speed—going from days to seconds for competitive analysis, surfacing not only known competitors but “hidden” ones they’d likely never discover manually.
    • Quote (06:22):

      "The founder expected a list of tools. Instead they get open source alternatives, feature level comparison and hidden competitors that they have never heard of, all in seconds.” — Adithya Sharma

• Adithya’s Own Experience Using Productive AI

  • Adithya used his own product to research competitors for Productive AI, discovering similar projects and features he then built into his own tool.
    • Quote (08:37):

      “To my surprise, I got N numbers of exactly same open source project, which was similar to Productive AI, and I used their components and features in Productive AI. So that was really a game changer for me.” — Adithya Sharma

5. The “Brain” Behind Productive AI

• Productive AI relies on semantic understanding to perceive similarities between projects, even if they use different terminology, allowing for more meaningful matches.
  • Quote (07:41):

    “It’s all about semantic understanding. Knowing two products might solve the same problem even if they use totally different words.” — Adithya Sharma

  • Dr. Nall reflects:
    • Quote (08:02):

      “Wow, wow. And you’re saying that it’s all about semantic coding, right? Awesome. Awesome.” — Dr. Tamara Nall

6. The Future of AI-Assisted Competitive Analysis (Looking to 2030)

• Adithya’s Vision:
  • Competitive analysis will be instant and open-source will be central, not hidden. Decisions will feel “lighter” and “calmer,” with AI as an unobtrusive assistant.
    • Quote (11:31):

      “For founders, the competitive analysis will be instant. Open source will be first class, not hidden. And their decision will be faster, calmer and smarter. The future won't feel automated, it will feel lighter.” — Adithya Sharma

    • Dr. Nall remarks:

      “It just becomes a way of life. Like breathing.” — Dr. Tamara Nall (11:51)

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Notable Quotes and Memorable Moments

• On AI as a Co-Builder (Overrated and Underrated Tech Trends)

  • Overrated:

    “Most people believe in that AI will do everything for you...AI is just your friend that can help you do your work and be your companion.” — Adithya Sharma (13:55)

  • Underrated:

    “People still want to use the primitive way of software development in today’s era. But I think they should adapt the newer method that AI gives and they should adopt the strategy.” — Adithya Sharma (14:25)

• Book Recommendation

  “The book that I would probably suggest is the Almanac of Naval Ravikant that clarity beats complexity.” — Adithya Sharma (14:56)

• Bold Prediction for the Future

  “AI won’t replace developers, but developers who use AI will replace those who don’t.” — Adithya Sharma (15:23)

• Lighthearted Olympic Metaphor

  • When asked which Winter Olympics sport he’d choose:

    “I’d choose curling...it is mostly about strategy, precision and long term thinking.” — Adithya Sharma (13:10)

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Timestamps for Important Segments

• 00:00–02:25 – Introduction, guest welcome, and Adithya’s backstory
• 02:25–03:24 – Origin of Productive AI
• 03:24–04:32 – How Productive AI works and what users receive
• 05:09–05:39 – Intellectual property and open-source discussion
• 06:22–06:40 – Real-world impact for founders: speed and thoroughness
• 07:41–08:02 – Semantic search and technical design
• 08:37–09:15 – Adithya using his own product for development
• 10:01–11:09 – Ethics and human intelligence in the loop
• 11:31–11:51 – 2030 vision for AI and product development
• 12:13–12:49 – How to try Productive AI
• 13:10–13:38 – Olympic sports analogy (curling and strategy)
• 13:55–15:34 – Rapid-fire Q&A: trends, book, bold predictions
• 15:48–16:03 – Connecting with Productive AI and Adithya

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How to Access Productive AI

• Website: productiveai.netlify.app
• Social Media: Adithya Sharma is available on LinkedIn, Twitter, and Instagram

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Takeaways

• AI-Driven Research: Productive AI transforms days of competitive analysis into seconds, focusing on open-source code to inspire and accelerate innovation.
• Augmentation, Not Automation: AI is positioned as a partner, helping founders build better—without removing their agency or decision-making.
• Emphasis on Ethics: Transparent recommendations, consent-based data use, and the goal of enabling user learning are central.
• The Future Is Lighter: As AI tools like Productive AI mature, the competitive landscape becomes more navigable, democratized, and user-friendly.

Dr. Nall’s energetic and insightful hosting ensures the conversation delivers actionable insights and genuinely celebrates the possibilities of AI-enabled creation.

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Transcript

[A]

On today's episode of Lead with AI, we're asking a critical question. How well do you really understand your competition in the AI race? Building fast isn't enough. You have to build strategically. What used to take days of research can now happen in seconds. I'm joined by Adithya Sharma, founder of Productive AI, a platform that helps developers run competitive analysis instantly so they can refine their AI tools and ship with an edge. Let's get into it. Welcome to lead with AI. I'm Dr. Tamara Nall. In each episode, we will take you behind the scenes with visionary leaders shaping the future of AI across public and private sectors. Join us as we explore groundbreaking projects and innovations that are transforming industries and making a real impact on people's lives. Let's dive in. Hi everyone. Welcome back to lead with AI. I'm your host, Dr. T. And we are so excited this year we've had some amazing guests and you're not going to be disappointed by our guests today. But first I just wanted to say thank you to all of you who listen in every week or actually more than once a week to find out all of the latest AI powered tools that are shaping the world today. Because of that, as you know, we hit number one in technology on Apple podcast last year as well as being a W3 award winning podcast. So we are excited and you will find out today why we have won awards. So we want to welcome Aditya Sharma who is the founder of Productive AI. Welcome Aditya. How are you?

[B]

I'm doing good. It's been a long. So let's discuss today more about AI. I'm pretty excited.

[A]

Absolutely. I am too. So before we get into Productive AI and what it is, tell us about you. Who are you at your core, what are you passionate about and how did you come up with the idea that productive AI was needed?

[B]

Okay. At my core I am a problem solver. So the idea of productive AI came from a different but equally painful place where building startups, I realized founders spend days doing competitive analysis. They were googling alternatives, bookmarking tools and making spreadsheets. I thought what if AI could do that thinking for you in seconds. Not to replace the founders but to free them from focusing on the building part. So what I think that AI shouldn't be make you feel magical, it should feel helpful.

[A]

Got it. That's amazing. Now tell us a little bit about what productive AI is.

[B]

Okay, so the productive AI is a place where you can come and if you are building something, so you can just insert the description of your product and tell the tags that your product has. So what it will do, it will go and do AI based searching. It will search the whole lot of open source projects that are available on GitHub and show you the similar projects that are available on GitHub that you can go through. And if you like some parts or some features of that product, you can just use them in your projects. That's where AI helps you in making, building a great product.

[A]

Wow. So if I go, so if I'm building something and I want to see what other projects are going on or tools are going on, I can go and then does productive AI, then send me that code that I can then use myself. Or if I need this one specific component, how do I get that component to make my tool better?

[B]

Okay, so based on your inputs, so it will do a competitive analysis and it will give you the level of correctness or the similarity that your product has and that the GitHub project has. It will also tell you that the features that your product has but that project doesn't have and vice versa. This will help you, this will help you to know the product that what you are looking for and you can just go to that GitHub repository and just use that.

[A]

Oh, okay. How clever is that? Now I know I gotta ask this, you know, does that kind of get into like intellectual property issues at all? Like how have you thought about that?

[B]

Yeah, I surely thought of that. Just because you are using GitHub, so the projects are open source, so I think that saves you a lot. So there will be no problem using the open source projects.

[A]

You're right. Oh my God, that is genius. You're right. Because that's the whole purpose of GitHub is that it's open source and you're supposed to share code and help each other. Oh my goodness, that is amazing. Oh my goodness. See this is what I was telling people. This is why we're award winning because there's like all these products that are just so phenomenal that can help build better. That is absolutely amazing. So I've already had kind of a holy smokes moment, but give us an example of where someone used productive AI and it changed everything for them. See we like examples, we like illustrations so that we can actually take it from conceptual than actually have something that we can nub.

[B]

So for productive AI, the job jaw dropping moment was speed. The founder expected a list of tools. Instead they get open source alternatives, feature level comparison and hidden competitors that they have never heard of, all in seconds.

[A]

Oh my Goodness, that is amazing. That is absolutely awesome. To be able within seconds to know what other competition is out there. Because I feel like as founders, sometimes we feel like we have the best and the latest and the greatest when there are, you know, hundreds if not thousands of people who are actually working on the same thing or something similar. And what better way than to use productive AI to make yours even better?

[B]

Correct.

[A]

Oh, my gosh, that is amazing. We're also very curious people and we like to know how things work. So if we were to open up the hood of productive AI and really look at the brain of how it works and how it's so accurate and how it can happen within seconds and be able to find these competitive components that we can use to better ours and walk us through that. How does it work?

[B]

Yes, sure. So for productive AI, it's all about semantic understanding. Knowing two products might solve the same problem even if they use totally different words. So emotionally it feels like, oh, wow, this gets me.

[A]

Wow, wow. And you're saying that it's all about semantic coding, right? Awesome. Awesome. That is great. Now give us another example of where you were testing it, developing it, and your mind was blown with how productive, no pun intended, it was, and the results where you're like, oh my gosh, should I really create this? Did I really build this? Or walk us through that scenario where you were wowed by what you had built.

[B]

Okay, so when I was building productive AI itself, so I was using AI for that, and after building the productive AI, I just tried to find my project itself. So productive AI, it's open source. So I just gave the description and the feature that productive AI automatically already had. So to my surprise, I got N numbers of exactly same open source project, which was similar to productive AI, and I used their components and features in productive AI. So that was really a game changer for me.

[A]

Oh, wow, that's amazing. So do you feel that without finding that other tech, that productive AI would not be as good as it is today, or do you think it would still be just as great had you not found it?

[B]

I guess making productive AI was a bit challenge at first, but after making it evolving into what we have today, it was a bit of iteration work. But we finally are, we are getting the similar product. We are having less time inputs in making competitive analysis for the founders. So here we are.

[A]

All right. Okay, that's actually amazing. So how do you think about ethics? I mean, obviously GitHub is there because it's open source, you can share, but as developers and founders use productive AI. What are some of the ethical considerations that you thought as you were building it? And things that if you could give advice to other founders, how they should think about ethics.

[B]

So I would say the line is dependency AI should augment thinking and not replace it. So we are very intentional about not promising guaranteed outcomes, showing why a recommendation exists, keeping the human in control of decision. We don't train on private user data without consent and we design the product to teach users how to think better, not blindly follow suggestion. So if user grow without understanding that it means we have failed.

[A]

Right? Oh, I love that. I absolutely love that. So tell us about like the big Future, you know 2030, which is four years from now. Time is moving fast. If you had to, if you had a crystal ball in your mind, how will productive AI change the world and how will it impact the big future?

[B]

So for founders, the competitive analysis will be instant. Open source will be first class, not hidden. And their decision will be faster, calmer and smarter. The future won't feel automated, it will feel lighter.

[A]

Awesome. I love that. It won't feel automated. It just becomes a way of life. Light breathing. That is great. So we like to get our hands dirty and to try out all these different apps that we're learning about. If we want to try out productive AI, tell us how we can do that. Where do we go?

[B]

You can just go to Productive AI's website and just. It is very easy to use. You can just give your inputs in the section and you can tell us about the description of your product and you can just hit search. It will do all the jobs for you in an instant.

[A]

Got it. Okay, so what is the website? Give us the website so that we can know how to get there.

[B]

Yeah, surely it is productiveai netlify app. Okay, you can just go there and use that.

[A]

That's amazing. Well, I have a question that I call from one genius to another. So from one guest to another. And the question for you is, and it's so timely given the fact that we're in the middle of the Winter Olympics now. So if you had to compete in the Winter Olympics, which sport would you choose and why?

[B]

That is really a very good question indeed. So if I were to participate in Winter Olympics, so I'd choose curling and not just because it looked calm compared to downhill skiing. Culling is fascinating because it is not about brute strength or speed. It is mostly about strategy, precision and long term thinking.

[A]

Awesome. I love that. And so fitting. That is so fitting. Well, let's move now to our bonus Rapid Fire. That is where I will quickly ask you four questions and then you quickly give me the answer. Starting with what is the most overrated tech trend?

[B]

I think most people believe in that AI will do everything for you and they give the command in the hand of AI. I think that is the most overrated because it is not. So AI is just your friend that can help you do your work and be your companion. So that's what I think.

[A]

Awesome. What's the most underrated tech trend?

[B]

I think that people believe that AI is not that much useful in building technology. People still want to use the primitive way of software development in today's era. But I think they should adapt the newer method that AI gives and they should adopt the strategy.

[A]

Got it. Amazing. What's a book we should all read?

[B]

Yeah. The book that I would probably suggest is the Almanac of Neville Ravican that clarity beats complexity. I would suggest them to their users to go through it once. It is pretty amazing.

[A]

Oh, that is great. That is absolutely amazing. Now scare us. Give us your bold, bold prediction for the future.

[B]

What I probably think is that AI won't replace developers, but developers who use AI will replace those who don't.

[A]

I love that. I absolutely love that. I have so enjoyed this conversation. Tell us again, what's the website? How do we connect with productive AI? How do we connect with you on social media?

[B]

Yeah, you can surely connect with me on LinkedIn, Twitter, Instagram. So the website for Productive AI is ProductiveAI Netlify app. You can just go and check it out. Surely it will help you a lot.

[A]

Awesome. And then we'll have the correct spelling of both productive AI and the website as well as his name here below. Thank you so much, Aditya. We just love hearing about productive AI and everything that it's doing to change the world.

[B]

Thank you. Thank you a lot. It was great fun having a chat with you.

[A]

Absolutely. Okay everyone, until next time, remember to lead with AI. Thanks for tuning in to lead with AI. I'll see you next time as we continue exploring, exploring the cutting edge innovations shaping AI across the public and private sectors. Until then, keep leading with AI.