Techie Talks with Kuldeep

Techie Talks with Kuldeep

🌟Whether you're a student exploring tech, a professional leveling up your career, or a startup founder navigating innovation, this is your space to grow. 🔥What you’ll discover here: - Learn from the best - Stay ahead in tech - Fuel your ambitions - Honest discussions about challenges, failures, mindset, growth, and learning in the tech world - Practical advice for students, job seekers, tech enthusiasts, and startup builders - Inspiring career journeys of successful tech professionals - Deep dives into cutting-edge topics Artificial Intelligence, Cloud Computing, Cybersecurity, Blockchain

  1. Oct 24

    Building Missed-Call Voice AI for India & Human-Centered Tech | Challenges & Evolution of Search

    SuperOwl COO Farah on Why Keywords Are Dead, Missed-Call Voice AI for India & Building Human-Centered TechIn this episode of Techie Talks with Kuldeep, host Kuldeep Singh interviews Mrs. Farah, co-founder and COO of SuperOwl, about her decade-plus entrepreneurial journey and the centrality of understanding customers. Farah recounts her 2008 work at Yahoo, including a provisional US patent around keyword trading, and contrasts keyword search then with today’s intent-driven systems that can choose and book services like a dentist appointment. She discusses her IISc research on intellectual property and early mobile payments, highlighting user trust barriers and technologies like NFC and USSD. Farah explains SuperOwl’s niche focus on missed calls for local businesses, the need for empathetic, low-latency, highly accurate voice AI, and India’s price sensitivity. She also shares her work on tactile children’s products like wooden blocks to balance gadget time, emphasizes empathy in tech, comments on women founders, and closes with lessons on ego, objections, and time management.Time Stamps00:00 Precaps01:24 Welcome And Guest Intro01:41 Entrepreneurship Lessons03:57 Yahoo Keywords To AI08:10 IISC Research And IP12:35 Engineering And Adoption17:11 Unit Economics In India20:10 Women In Deep Tech22:53 New Startup26:43 Human Empathy In AI29:31 Rapid Fire Round31:21 Closing ThoughtsYouTube Channel: @techietalkswithkuldeep WhatsApp Channel: https://www.whatsapp.com/channel/0029...LinkedIn:   / techietalkswithkuldeep  Facebook: https://www.facebook.com/profile.php?...Instagram:   / techietalkswithkuldeep  Follow Farah Ahmad on LinkedIn:   / farah-ahmad-2a864939

  2. Oct 12

    The Hidden Risk of Enterprise AI: Are You Still Stuck In Pilot Mode | MLOPs Reality Check

    Stop getting stuck in pilot projects. Learn how to scale your enterprise AI strategy beyond simple tests and into real value.Kuldeep Singh hosts Sandhya Gopalan, who shares many organizations treat AI like a science experiment, constantly stuck in the prototyping phase. We analyze why your machine learning operations are stalling and how to bridge the gap between initial tests and production-ready systems. It is not enough to have a working model if you cannot support it at scale.Moving past pilot projects requires a fundamental shift in how you analyze your cost, people, data, and technology. We discuss the necessary platform architecture to support sustainable growth and why Trusted AI is the missing piece for organizations trying to operationalize their efforts. If your team is running in place, this breakdown will help you reorient toward a strategy that actually works.Time stamps0:00 Highlights1:20 A Journey Through 21 Years of Tech5:48 Breaking Cultural and Architectural Barriers13:13 Avoiding Cloud Vendor Lock-in21:01 Operationalizing Trusted AI31:26 The Shift in DevOps Responsibilities38:19 Preventing Catastrophic AI Failures41:41 Closing remarksYouTube Channel: @techietalkswithkuldeep WhatsApp Channel: https://www.whatsapp.com/channel/0029...LinkedIn:   / techietalkswithkuldeep  Facebook: https://www.facebook.com/profile.php?...Instagram:   / techietalkswithkuldeep  Follow Sandhya Gopalan on LinkedIn:   / sandhya-gopalan01   #ai #technology #machinelearning #mlops #softwareengineering #startup #techpodcast #techietalkswithkuldeep

  3. Oct 3

    How to Fix the Product Execution Leak & Why High Growth Companies Fail At Revenue?

    Stop shipping features that don't move the needle. We are breaking down why your product execution might be the silent leak costing you revenue.High-growth companies often fall into the trap of confusing activity with progress. Just because your roadmap is full of shipped features does not mean your revenue generation is actually scaling. We analyze how to identify when your team is optimized for output rather than impact and why flat growth often points to a disconnect between engineering goals and business reality.Instead of blindly adding to the backlog, start asking your recent hires about how they navigate these complexities. Aligning your technical roadmap with actual market value is the only way to stop the bleed and get back to sustainable growth.Time Stamps0:00 Highlights1:08 Meet the Guest3:28 Shipping vs. Revenue: The Output Trap6:51 Identifying Friction in Your Development Process10:17 The Altitude Gap: Why Teams Fail to Align16:14 Playbooks for Engineering Velocity21:26 Finding True Levers for AI-Driven Growth23:41  Hard Truth & Advice about scaling product organization 24:46 Closing ThoughtsYouTube Channel: @techietalkswithkuldeep WhatsApp Channel: https://www.whatsapp.com/channel/0029Vb7Q4JHAjPXUt8hBgm2TLinkedIn: https://www.linkedin.com/company/techietalkswithkuldeepFacebook: https://www.facebook.com/profile.php?id=61574642927780Instagram: https://www.instagram.com/techietalkswithkuldeepFollow Ashvita MandalLinkedIn: https://www.linkedin.com/in/ashvita-m/#ai #technology #startups #developers #productmanagement #techleadership #softwareengineering #techpodcast #techietalkswithkuldeep

  4. Sep 22

    Surviving High-Stakes Tech: The Engineer’s Guide to Compliance | ft. Kshitiz Agarwal

    Scaling Fintech Systems & Tech Orgs: UPI Reliability, Monolith vs Microservices, and AI Blind Spots In this episode of Techie Talks with Kuldeep, host Kuldeep Singh speaks with industry veteran Kshitiz Agarwal about nearly two decades of experience across Samsung, Intel, OYO, Paytm, and ticketing/travel platforms. They discuss how architecture priorities shift in regulated, high-stakes systems like UPI, emphasizing fraud prevention, security, and reliability as critical to consumer trust. Kshitiz shares a framework for scaling engineering organizations by focusing on velocity (directional impact) over speed, using clear goals and iterative feedback loops. He explains why monolith-to-microservices migrations should be driven by specific problems and measurable outcomes, not trends, and outlines team-splitting approaches using product-aligned verticals and shared horizontal platforms with standard APIs. They also cover developing technical leaders through goals, autonomy, and minimal micromanagement, daily metric tracking for managers, career advice to learn the business and collaborate, and AI’s risk of encouraging careless attention to important details like sensitive logging.00:00 Precaps01:27 Introduction01:44 Career Journey Highlights03:13 Architecture For Trust05:19 Fintech Compliance Reality08:21 Scaling Teams With Velocity11:13 Monolith Vs Microservices14:34 Growing Technical Leaders16:37 AI Blind Spots For Leaders19:40 Rapid Fire Playbook22:25 Closing ThoughtsYouTube Channel: @techietalkswithkuldeep WhatsApp Channel: https://www.whatsapp.com/channel/0029Vb7Q4JHAjPXUt8hBgm2TLinkedIn: https://www.linkedin.com/company/techietalkswithkuldeepFacebook: https://www.facebook.com/profile.php?id=61574642927780Instagram: https://www.instagram.com/techietalkswithkuldeepFollow Kshitiz Agarwal on LinkedIn: https://www.linkedin.com/in/kshitiz-agarwal/#ai #technology #softwareengineering #systemdesign #techleadership #softwarearchitecture#cloudcomputing #techpodcast #techietalkswithkuldeepEngineering Leadership, System Design, Monolith to Microservices, Fintech Architecture, Techie Talks with Kuldeep, Scaling Engineering Teams, Software Architecture Best Practices

  5. Sep 6

    Is Your AI Infrastructure Ready? GPU Utilization , Governance, Edge AI and The Blackwell Paradox

    The Blackwell Paradox: GPU Utilization vs P99 Latency, AI Governance, and Edge AI Kuldeep Singh hosts Akhil Gupta to discuss operating AI systems in production, focusing on the “Blackwell Paradox” where pushing GPU utilization toward 95%+ via batching and speculative decoding can improve average latency but dangerously worsen P99, which is unacceptable for critical use cases like real-time fraud detection. Akhil argues CFO cost comparisons should weigh idle GPU headroom against outage and SLA-penalty costs, using an elevator-capacity analogy. They contrast classical ML for SLA-critical “fast lane” decisions with GenAI for “slow lane” post-transaction reasoning, behavioral analysis, and compliance support. In multi-tenant inference, Akhil proposes three-layer governance—admission control, per-tenant KV-cache isolation, and SLA-priority decoding—to prevent noisy workloads from impacting others. They also cover Edge AI with ExecuTorch, small/quantized models, and a routing metric favoring edge for latency/privacy and cloud for complex cross-domain needs, concluding governance must precede scaling AI systems.Understanding the Blackwell Paradox is critical for balancing GPU utilization and P99 latency in production AI systems.Kuldeep Singh hosts Akhil Gupta to break down why the Blackwell Paradox makes pushing GPU utilization above 95% often backfire. They explain how batching and speculative decoding might improve average latency but degrade P99 performance, creating unacceptable risks for real-time fraud detection.The discussion covers necessary AI governance frameworks, including admission control and priority decoding, to isolate noisy workloads. Akhil also shares a practical approach to inference optimization, comparing when to route traffic to edge AI versus the cloud, ensuring your infrastructure is built for reliability, not just raw compute density.Subscribe for weekly engineering and cloud architecture breakdowns. What is your biggest challenge when scaling LLM inference? Let us know in the comments.00:00 Highlights01:15 Introduction01:48 Akhil Career And AI Costs04:14 Blackwell Paradox Explained06:34 CFO View Idle Capacity09:40 Fast Lane Vs Slow Lane13:11 Shared Infra And Fallbacks16:06 Multi Tenant Governance Layers20:46 Edge AI Reality Check24:43 Route Requests Edge Or Cloud26:38 India Compute And Access28:08 Future Inference Ops Shifts30:58 Wrap Up And Takeaways32:43 Closing And Sign OffCONNECT WITH US 🌐YouTube Channel: @techietalkswithkuldeep WhatsApp Channel: https://www.whatsapp.com/channel/0029Vb7Q4JHAjPXUt8hBgm2TLinkedIn: https://www.linkedin.com/company/techietalkswithkuldeepFacebook: https://www.facebook.com/profile.php?id=61574642927780Instagram: https://www.instagram.com/techietalkswithkuldeepFollow Akhil Gupta on LinkedIn: https://www.linkedin.com/in/akkhil/👍 Like, subscribe, and comment your biggest challenge when scaling LLM Inference#ai #cloudcomputing #gpu #cloudsecurity #edgeai #aiintech #techpodcast #cloudcostoptimization #softwareengineering #cloudarchitecture #opensource #techietalkswithkuldeep

  6. Aug 30

    DevSecOps in Fintech & EdTech: Crypto Infra, AI & Million-Dollar Cost Cuts |Co-Founder Nishant Gupta

    DevSecOps isn't just about tools — it's about culture. In this episode of Techie Talks with Kuldeep, host Kuldeep Singh sits down with Nishant Gupta, CEO & Co-Founder of DevSecOps.ai, to unpack how he scaled crypto exchange infrastructure, slashed DevOps SLAs, and saved companies over $1 million in cloud costs.We cover managing blockchain full nodes at scale, migrating stateful workloads to Kubernetes, cutting FinOps waste, replacing paid monitoring tools with open-source alternatives, building self-service infrastructure with security guardrails, and where AI actually fixes security gaps vs. where it's just hype.⏱️ TIMESTAMPS00:00 – DevSecOps is about culture, not just tools00:04 – Managing crypto exchange infra at high volume00:19 – Persistent storage: the first big challenge01:53 – Scaling ZebPay's blockchain nodes under compliance01:57 – Surviving state sync & consensus failures04:32 – Migrating full nodes from EC2 to EKS04:33 – Containerizing stateful blockchain workloads07:26 – FinOps: how $1M+ was saved in hybrid cloud09:23 – Fixing the architecture that was bleeding money13:08 – Replacing paid monitoring with open-source (Loki, Prometheus, Grafana)14:21 – Saving $25-30K/month on observability costs14:24 – Slashing DevOps SLA at WhiteHat Jr from 1 week to 2 days17:41 – Why engineering teams fail at automation19:16 – Self-service infra & security guardrails for developers20:50 – Why he left corporate after 18 years to found DevSecOps.ai24:04 – Where AI actually fixes security gaps (and where it's hype)30:14 – Rapid fire: legacy cloud practices that need to die31:52 – The psychological blind spot founders must fix32:56 – Life after leaving corporate: risk, finance & convictionCONNECT WITH US 🌐YouTube Channel: @techietalkswithkuldeep WhatsApp Channel: https://www.whatsapp.com/channel/0029Vb7Q4JHAjPXUt8hBgm2TLinkedIn: https://www.linkedin.com/company/techietalkswithkuldeepFacebook: https://www.facebook.com/profile.php?id=61574642927780Instagram: https://www.instagram.com/techietalkswithkuldeepFollow Nishant Gupta on LinkedIn: https://www.linkedin.com/in/nishant-gupta-83322210/👍 Like, subscribe, and comment your biggest DevOps/cloud challenge below!#DevSecOps #devops #fintech #edtech #cloudcomputing #kubernetes #aws #cloudsecurity #finops #blockchain #cryptoinfrastructure #aiintech #techpodcast #startupjourney #cloudcostoptimization #softwareengineering #cloudarchitecture #opensource #devopsengineering #techietalkswithkuldeep

  7. Aug 23

    Is Your Recruitment Strategy Failing? The Truth About Bulk Hiring | AI Hiring reality check

    In this episode of Techie Talks with Kuldeep, host Kuldeep Singh sits down with Mr. Daya Prakash, Founder of TalentOnLease and former CIO of LG India, to unpack why traditional corporate hiring is broken, how IT service companies can monetize bench resources without risking client confidentiality, and why "AI-powered" hiring platforms still need human judgment to earn trust. Daya also shares his entrepreneurial journey — moving from a corporate safety net to building TalentOnLease — and how it reshaped his perspective on risk and digital transformation.**Timestamps**0:00 – Highlights1:08 – Intro1:30 – Daya Prakash's career journey & how TalentOnLease started4:43 – Is traditional corporate recruitment fundamentally broken?8:14 – Monetizing IT bench resources without client confidentiality risk14:24 – Why recruitment agencies fail on large bulk-hiring demands18:30 – Deploying talent in 2-3 days: how quality is really ensured18:45 – "Everyone's overusing the word AI" — trust over hype24:30 – Short-term trials becoming long-term partnerships29:35 – From LG's CIO to founder: how his view on risk changed31:48 – Why entrepreneurs have no choice but to bounce back36:58 – Closing thoughts CONNECT WITH US 🌐YouTube Channel: @techietalkswithkuldeep WhatsApp Channel: https://www.whatsapp.com/channel/0029Vb7Q4JHAjPXUt8hBgm2TLinkedIn: https://www.linkedin.com/company/techietalkswithkuldeepFacebook: https://www.facebook.com/profile.php?id=61574642927780Instagram: https://www.instagram.com/techietalkswithkuldeepFollow Daya Prakash on LinkedIn: https://www.linkedin.com/in/dayaprakash/#ai #technlogy #futureofwork #techhiring #techcareer #startupjourney #hrtech #entrepreneurship #leadership #techpodcast #mindset #techietalkswithkuldeep

  8. Aug 16

    Edge AI Strategy: Why You Need to Pivot |Real Reason EdgeAI Is Taking Over

    In this Techie Talks with Kuldeep episode, Kuldeep Singh interviews Kartikeya, a senior developer advocate and senior engineer at Qualcomm, about deploying and optimizing AI models on edge devices. They discuss why many web and cloud engineers struggle with edge deployment due to limited understanding of ML fundamentals, inference engines, and model optimization techniques like quantization and pruning. Kartikeya explains the TensorFlow Lite to LiteRT transition as primarily a front-end change, with Qualcomm’s QNN runtime and NPUs enabling private, offline on-device inference, and highlights Qualcomm AI Hub for model conversion, profiling, and deployment across Snapdragon-powered devices. They cover quantization trade-offs (PTQ vs QAT), data quality impacts on accuracy, kernel/runtime considerations for power and performance, the feasibility of local RAG with vector databases, and why enterprises adopt edge AI for cost reduction, privacy, and hybrid edge-cloud architectures.TimeStamps00:00 Precaps01:15 Meet the Guest02:38 Misconceptions and Model Shrinking05:50 LiteRT and Snapdragon Runtime09:45 Why Edge AI Matters12:06 Local LLM IDE Demo14:13 Quantization Beyond PTQ19:00 Battery and Kernel Optimization23:18 Local RAG on Device25:29 Enterprise Hybrid Edge Cloud30:59 Edge AI Learning Path35:47 Edge AI Is Everywhere38:41 Wrap Up and GoodbyeCONNECT WITH US 🌐YouTube Channel: @techietalkswithkuldeep WhatsApp Channel: https://www.whatsapp.com/channel/0029Vb7Q4JHAjPXUt8hBgm2TLinkedIn: https://www.linkedin.com/company/techietalkswithkuldeepFacebook: https://www.facebook.com/profile.php?id=61574642927780Instagram: https://www.instagram.com/techietalkswithkuldeepFollow Kartikey Rawat on LinkedIn:https://www.linkedin.com/in/carrycooldude/#ai #technology #edgeai #edgecomputing #machinelearning #artificialintelligence #aiedge #quantization #modeloptimization #tinyml #hybridai #qualcomm #deeplearning #futureofai #techpodcast

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About

🌟Whether you're a student exploring tech, a professional leveling up your career, or a startup founder navigating innovation, this is your space to grow. 🔥What you’ll discover here: - Learn from the best - Stay ahead in tech - Fuel your ambitions - Honest discussions about challenges, failures, mindset, growth, and learning in the tech world - Practical advice for students, job seekers, tech enthusiasts, and startup builders - Inspiring career journeys of successful tech professionals - Deep dives into cutting-edge topics Artificial Intelligence, Cloud Computing, Cybersecurity, Blockchain

Information

  • Creator
    Techie Talks with Kuldeep
  • Years Active
    2025 - 2026
  • Episodes
    43
  • Rating
    Clean
  • Copyright
    © Techie Talks with Kuldeep
  • Show Website
    Techie Talks with Kuldeep