33 episodes listed below
Tech career stories, recapped warmly and turned into advice.
Exploiting with Teja Kummarikuntla turns career conversations with data scientists, engineers and educators into practical advice about breaking in, building things and finding purpose. The host plays the admiring student, warmly recapping what a guest has just said before nudging them toward the next turn in their story.
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Exploiting with Teja Kummarikuntla is a conversation show about building a working life in technology, and it pays special attention to the detours. Guests come from data science, software engineering, online teaching, leadership work and company founding. They do most of the talking. Episodes tend to move from origin story to career advice to practical reflection, so a single conversation can travel from a guest's student years to a concrete tip about getting hired. Teja Kummarikuntla plays the admiring student rather than the sceptic. Questions usually arrive inside generous recaps, with the host restating a point, praising it and drawing out a broader lesson before asking the next thing. That habit keeps the pace unhurried and sometimes looping, but it also keeps the spotlight on the guest. The specifics are where the show earns its place. Jalem Raj Rohit once interviewed the host for a data science role; here the seats are swapped, and he tells of failing maths twice before publishing research under the same professor. His interview advice is plain and usable: say less about courses taken and more about the projects built in them. Nidhi Thakkar recalls sitting in on a computer vision meeting full of PhDs simply because she was curious, then explains how to approach a senior data scientist online without a bare request for work. She also argues for an online portfolio, a supportive network and teaching as a way to learn. Boris Paskhaver's first piece of advice is to find a problem and learn whatever solving it demands, and the two also talk about why so few students finish online courses. Christian Clausen describes time-boxing work to avoid the spiral of perfectionism, and recalls a mentor asking who his book was helping while it sat on a hard drive. Heath Slawner, speaking about purpose and leadership, tells of a hotel that promised guests a home and then gave them anti-theft hangers, a neat picture of words and actions drifting apart. The wider list of titles shows how far the range extends. Some carry the word 'Founding', as in 'Bob Belderbos: On How To Build and Grow Communities In Technology | Founding PyBites' and 'Rathinamurthy R: On Disrupting The Way Developers Learn | Founding Crio.Do', while 'Craig Dennis: On Becoming a Developer Educator' and 'Marco Faella: On Building a Seriously Good Software' name teaching and software quality outright. A few entries are labelled 'Unicast', such as 'Unicast | ELI5 ON: Explaining Machine Learning To A Five Year Old', and they appear among the guest conversations. As a place to start, the Jalem Raj Rohit and Nidhi Thakkar conversations centre on moving from campus into data science, Christian Clausen's on getting started and staying consistent, and Heath Slawner's on purpose at work. What comes away is less a technical tutorial than a set of habits other people used to get moving: build something, share it, reach out with care and keep going.
Made for: Suits a listener trying to move into data science, AI or software engineering who wants to hear how others actually made the jump, from internships and interviews to writing books and teaching courses. It also fits someone who prefers encouragement and personal stories over debate or deep technical detail.
What sets it apart: Its interest sits with the person more than the tooling: the host's admiring, student-minded questions draw out detours such as failing maths or a book stuck on a hard drive, then recast them as advice someone could act on. It even reverses roles with a guest who once interviewed the host for a data science role.
The Exploiting Podcast is a weekly show with Conversations and Unicasts, Hosted by Teja Kummarikuntla. We resonate by diving deep into the exploiting actions by the incredible Technical, and Business leaders. With Unicasts we amplify the wisdom in the world that could help us to transform. Sounds exciting? Come exploit with us at: exploit.chat
Based on 5 episodes we listened to · September 2026
Teja Kummarikuntla turns data science careers, coding choices, and project lessons into approachable conversations grounded in guests' firsthand work.
Teja Kummarikuntla builds these conversations around the practical decisions behind technical careers. Data science provides the clearest through-line, with guests discussing the move from academia to industry, the skills employers ask for, and the value of original projects.
A guest failed math twice, then published a research paper: your data science panic deserves a second opinion.
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Short reviews from the PlayNext desk, based on the episodes we processed.
A maths setback story that turns into practical advice on language choice and persistence.
The episode centers on a familiar data science anxiety: that maths can become a barrier. The guest recalls failing his maths course in first year, failing it again in second year, and then publishing a research paper in fourth year under the same professor who had failed both…
Curiosity and experimentation give the conversation its strongest, most practical thread.
Nidhi Thakkar's discussion is most compelling when it connects curiosity with real access to industry. She describes being invited into a meeting with PhDs working on a computer vision project after deciding she wanted more than her course covered and reaching out to people in…
Useful work should reach people, even when it is not perfect yet.
This episode lands on a familiar software pressure point: work is often useful before it is finished, and leaving it on a hard drive helps no one. The point is plain and steady.
Enterprise AI, with the hype pressure-tested.
AI hype, measured against mechanisms.
Sudarshan Ravichandran explains how a college Artificial Intelligence course and a high-school discovery of intuitive mathematics led him into data science.
Boris Paskhaver, a New York University business economics graduate (2013) and Udemy instructor since 2016, describes how four years of abstract economics left him unsure what to do with the degree.
The host opens on the idea that maths can block a data science career.
Nidhi traces her path into industry work.
The guest opens by saying that success in the industry comes from making new customers, project managers, and teams look like superstars.
Teja discusses data science interview preparation with a guest, covering coding challenges and learning from rejections.
Host Teja Kummarikuntla interviews senior AI engineer Matt Lennon about his career journey and offers advice on becoming a data scientist or machine learning engineer.
Interview with Bob Belderbos, co-founder of PyBites, discussing core principles for building and growing a Python learning community.
Host Teja Kummarikuntla interviews Frank Kane, a top Udemy instructor who made over one million dollars, about his journey from corporate to self-employment.