DataTalks.Club

DataTalks.Club
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DataTalks.Club - the place to talk about data!

  1. 1d ago

    How AI Agents are Reshaping Modern Work - Philip Christos

    In this talk, Philip Christos, Associate at M2VC, shares his expertise in frontier AI investing from his early days as a data analyst to evaluating cutting-edge deep tech startups. We explore how AI agents are reshaping modern work, the realities of venture capital in the LLM era, and why the future of software engineering relies more on high-level systems thinking than writing syntax.You’ll learn about:- How venture capitalists formulate AI investment strategies and evaluate startup pitch decks.- The rapid adoption of AI in software engineering compared to traditional sectors like accounting.- The crucial difference between data progress and algorithmic progress in frontier models.- Why LLMs still struggle with high-level software architecture, business logic, and design "taste."- How AI is accelerating iterations and breakthroughs in classical engineering and scientific research.- What specific deep tech and AI infrastructure ideas are actually attracting VC funding today.TIMECODES:00:00 Venture Capital Career Journey05:14 VC Analyst vs Data Analyst Roles10:13 AI Investment Thesis Strategy16:00 Emotion Analytics and Voice AI Startups22:09 LLM Impact on Venture Capital28:19 Software Engineering AI Adoption34:18 Data vs Algorithmic AI Progress40:15 Classical Engineering AI Acceleration46:12 Software Architecture AI Limitations51:11 Future Software Engineering Careers57:55 Systems Thinking in DevOps1:03:00 Pitching Deep Tech StartupsThis talk is perfect for software engineers, AI founders, and technical product managers who want to understand the evolving tech job market and venture landscape. It provides essential insights for anyone looking to build VC-backed AI startups or future-proof their career as AI coding tools become ubiquitous.Connect with Philip- Linkedin - https://www.linkedin.com/in/philipchristos/- Twitter - https://x.com/phil_christos- Website - https://t.me/stacked_channelConnect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

  2. Sep 4

    Running a Company on a Multi Agent Dispatch System - Paul Domanski

    In this talk, Paul Domanski, founder of Domanski AI, shares his unconventional journey from film directing and affiliate marketing to becoming a vibecoder running dozens of autonomous AI agents. We explore the realities of building an agentic operating system, how non technical builders can orchestrate complex AI workflows, and the exact strategies used to close high ticket B2B clients using AI generated prototypes.Links:- Headroom: https://github.com/domanski-ai/headroom/You will learn about:- How to build and use custom workspaces like Demox and Tmux setups to orchestrate over 50 concurrent AI agents- Using automated research and rapid AI prototyping to close high ticket B2B sales- Balancing usage across multiple Claude and Codex accounts while navigating API limits and context windows- How to design audit and deploy complex software solutions without a traditional computer science background or deep knowledge of tech stacks- How the skills of a film director like vision stubbornness and delegation perfectly translate to managing autonomous AI teams- Why evaluating LLM outputs is the most critical skill for ensuring reliable products for enterprise clientsTIMECODES:00:00 Welcome and Showcasing Demox08:46 Paul's Background in Film and Digital Marketing16:09 Sales Pipeline and Client Onboarding22:20 Token Efficiency and Open Source Models31:19 Curiosity and the Learning Process37:52 Red Teaming and Code Audits44:51 Building Software Without Knowing the Tech Stack51:02 Parallels Between Film Directing and Managing AI56:32 Using AI for 3D Printing and Personal Projects01:04:34 The Importance of AI EvalsThis conversation is perfect for solopreneurs, agency owners, and non technical builders who want to move beyond basic chat interfaces and start leveraging autonomous AI agents for real world business operations. Whether you are transitioning into AI from marketing, project management, or creative fields, this episode offers a practical blueprint for turning AI curiosity into a scalable business.Connect with Paul:- Linkedin - https://www.linkedin.com/in/paul-domanski-ai/- Twitter - https://x.com/domanski_ai- Github - https://github.com/domanski-ai- Website - https://domanski.ai/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

  3. Aug 28

    The Data Consultant Playbook From Code to Business Impact - Tony Zeljkovic and Juan Manuel Perafan

    In this talk, Tony Zeljkovic, Founder of Narona Data, shares his unconventional career journey from bioinformatics research and clinical genetics to building a successful AI and data platform consulting business. We explore the essential soft skills, networking strategies, and business mindsets required to thrive as an independent data consultant in today’s rapidly shifting tech landscape.Links:- The book pre-order on packt - https://www.packtpub.com/en-us/product/the-data-consultants-handbook-9781806665266- The book pre-order on amazon - https://www.amazon.com/dp/B0H3TBWHH1?lv=shuf&channelId=500&plpRedirect=mhFallbackYou’ll learn about:- How to smoothly transition from a highly technical or academic role into independent data consulting.- The step-by-step process of building a strong digital footprint and growing a reliable client pipeline from scratch.- Strategic positioning: how to stop selling "data engineering" and start selling business outcomes and ROI.- How leveraging platform implementation partnerships (e.g., Snowflake, dbt) can help you land your first major clients.- Adapting to the AI era and ensuring your consulting services stay relevant as market demands change.- The business mindset of a consultant, including when to invest in tools and outsource tasks like accounting to accelerate your growth.TIMECODES:00:00 Landing the First Consulting Client via Academic Research06:06 Transitioning from Research to Consulting11:42 Becoming a Platform Implementation Partner18:20 Building Your Digital Footprint23:22 Positioning: Selling Business Outcomes vs. Technical Skills31:02 Networking Strategies and Finding Industry Pain Points37:24 Is Consulting Right For You?44:17 Adapting to AI and Changing Market Demands50:16 Business Mindset: Investing in Tools and Outsourcing55:52 Start Early and Pay It Forward1:02:37 The Practical Handbook for Data ConsultingThis talk is perfect for data engineers, analytics professionals, and software developers who are considering the leap into freelancing or starting their own consulting practice. It is highly valuable for technical experts who want to master client acquisition, stakeholder communication, and the business side of the data industry.Connect with Tony:- LinkedIn - https://www.linkedin.com/in/tony-zeljkovic/- GitHub - https://github.com/2tony2- Consulting website - https://www.naronadata.com/​Connect with Juan:- LinkedIn - https://www.linkedin.com/in/jmperafan/- GitHub - https://github.com/jmperafan- Consulting website - https://juanalytics.com/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

  4. Aug 21

    Engineering AI-Powered Data Products - Radovan Bacovic

    In this talk, Radovan Bacovic, Principal Data Engineer and Snowflake/dbt Ambassador, shares his two-decade journey, from traditional database administration to leading modern data platform engineering. We explore the essential building blocks of scalable data architectures, the trade-offs of no-code solutions, and how to effectively integrate AI into your data pipelines while maintaining strict security and governance.You’ll learn about:- The evolution of the full-stack data engineer over the past two decades.- Building scalable, business-driven data platforms without premature optimization.- Efficient data modeling and transformation using DuckDB and dbt.- Leveraging AI to accelerate pipeline development and launch data products.- Implementing enterprise data governance and robust pipeline security.- Balancing no-code integration tools with strict DataOps methodologies.LINKS:https://gitlab.com/radovan.bacovic/wsc26_dataops/-/blob/main/README.md?ref_type=headsTIMECODES:0:00 Data Engineering Career Trajectory and Industry Experience6:37 Full Stack Data Engineer Role Evolution and Responsibilities14:45 Scalable Data Platform Architecture and Business Alignment21:59 DuckDB Integration and Premature Database Optimization Avoidance30:04 Data Pipeline Transformation and Data Modeling with dbt35:31 Modern Data Platform Ecosystem and Infrastructure Orchestration42:13 AI Powered Data Products and LLM Pipeline Automation49:42 Enterprise Data Governance and Pipeline Security Best Practices55:06 No Code Data Integration Tools and DataOps MethodologyThis talk is ideal for data engineers, analytics engineers, and data platform leads looking to modernize their tech stacks and future-proof their infrastructure. It provides highly actionable insights for anyone aiming to build resilient, AI-ready data platforms that prioritize real business value and strict security constraints.Connect with Radovan- Twitter - https://twitter.com/Al_Grigor - Linkedin - https://www.linkedin.com/in/agrigorev/ Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

  5. Jul 24

    Engineering Your Own AI Assistant - Paul Iusztin

    In this talk, Paul Iusztin, Creator of Decoding AI and author of the LLM Engineer's Handbook, shares his deep expertise in personal automation from managing a digital life with lightweight data pipelines to architecting autonomous agents for deep research. We explore the mechanics of building personal AI assistants and the critical role of using a "second brain" as a context layer over heavy, over-engineered RAG infrastructure.You’ll learn about:- Organizing your digital life using the PARA method and lightweight data pipelines.- Capturing and retrieving resources effortlessly with Obsidian, Readwise, and custom deep research algorithms.- Leveraging your "second brain" setup as the ultimate context layer for personal AI assistants.- Generating ad-hoc wikis from markdown brain dumps to streamline content creation and research.- Optimizing AI-generated content by deliberately lowering LLM reasoning capabilities for better styling.- Adapting multi-agent workflows and personal wikis to accelerate software engineering and coding tasks.TIMECODES:00:00 Digital life organization using the PARA method and lightweight data pipelines05:21 Seamless resource capture with Obsidian and Readwise09:26 Resource retrieval optimization using a deep research algorithm12:44 High-quality internet curation versus heavy RAG pipelines16:31 Second brain setup as a context layer for personal AI assistants21:40 AI workflow simplification with Anthropic APIs and CLI tools25:26 Ad-hoc wiki generation from markdown brain dumps for content creation29:18 Codebase ingestion and web scraping proxy tool workarounds34:43 Resource reranking and context window management for large texts39:06 Content styling optimization by lowering LLM reasoning capabilities46:18 Multi-agent workflows and personal wikis for software engineering tasks52:32 Personal wiki scaling for enterprise knowledge bases and book writingThis talk is perfect for individual developers, AI engineers, and knowledge workers looking to escape "PoC purgatory" and build practical, low-maintenance personal AI assistants. It offers highly actionable insights for anyone wanting to integrate agentic workflows into their daily productivity systems without over-engineering their tech stack.Connect with Paul- Linkedin - https://www.linkedin.com/in/pauliusztin/- Website - https://www.pauliusztin.ai/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

  6. Jul 17

    Thriving in the AI Era with Human Skills - Maryam Ramezani-Bartsch

    In this talk, Maryam Ramezani-Bartsch, Data and AI Leader with over 20 years of experience at companies like adidas and Zalando, shares her extensive career journey from building foundational ML systems at adidas to coaching data experts through the modern AI landscape. We explore the critical intersection of technical strategy and the essential human skills needed to thrive in the AI era.LINKS:- https://maryamramezani.com/designyourdatacareerYou will learn about:- The surprising similarities and critical differences between the current Generative AI boom and the previous Big Data era.- Why the traditional boundaries between data roles are disappearing and the specific T shaped profile companies are actually hiring for today.- The hidden danger of perfectionism in corporate tech, and what a healthy margin of failure actually looks like in practice.- How to stop leaving your career trajectory to chance by applying product Design Thinking to your own life.- A practical framework for navigating industry uncertainty and tech career anxiety without burning out.- Battle tested strategies for regaining your footing and standing out in a highly competitive job market after a layoff.- The specific non technical human skills that will become your ultimate career moat against automation.TIMECODES:00:00 Human Skills in the AI Era07:07 Building ML Systems at Adidas12:49 Generative AI vs Big Data Era18:39 T-Shaped Data Engineering Roles24:04 Overcoming Perfectionism in Tech30:34 Design Thinking for Data Careers38:59 Managing Tech Career Anxiety45:07 Aligning Passion with Tech Skills50:18 Job Search Strategies After Layoffs56:03 Essential Soft Skills for JuniorsThis talk is essential for data professionals, software engineers, and tech leaders looking to future proof their careers in an increasingly automated world. Whether you are a junior developer navigating a tough job market, an engineer bouncing back from layoffs, or a senior professional looking to strategically design your next pivot, this session provides the tools to build a highly resilient career.Connect with Maryam- Linkedin - https://www.linkedin.com/in/maryam-ramezani-bartsch/- Website - https://maryamramezani.com/- Substack - https://maryamramezani.substack.com/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

  7. Jul 10

    Building a Career in AI From Real Estate to AI Engineering - Gustaf Gyllensporre

    In this talk, Gustaf Gyllensporre, Senior AI Engineer and PropTech Founder, shares his unconventional career journey from selling Miami real estate to shipping production AI systems. We explore the tactical steps for breaking into the tech space as a self taught developer and how to successfully bypass traditional industry gatekeepers.Links:-  @PropTechFounder  - https://youtu.be/leXRiJ5TuQo?si=ymK03qKVEC7hAt9N- https://x.com/gostak_ddYou will learn about:- The strategic approach to crafting an AI engineering resume that actually gets noticed by hiring managers.- Why building another generic RAG chatbot might be hurting your portfolio and the specific high impact projects you should build instead.- The massive difference between interviewing for AI roles at dynamic startups versus traditional big tech companies.- How to leverage open source contributions to prove your technical mastery without a computer science degree.- The surprisingly simple networking tactics and developer ambassador programs that can unlock exclusive job opportunities.- Actionable ways to improve the critical social and communication skills that most developers completely ignore.TIMECODES:00:00 AI Engineering Field Guide05:01 Self Taught AI Engineer Pivot09:39 CPython Open Source Contributions13:49 Tech YouTube Channel Growth18:26 AI Engineer Resume Optimization22:44 AI Engineering Portfolio Projects29:23 Startup vs Big Tech Interviews33:47 Open Source AI Project Ideas38:55 Building Deep Research AI Agents42:52 Landing Your First AI Job46:48 Tech Networking Strategies51:16 Technical Project Demo Videos54:53 Self Taught Developer Mistakes58:53 Soft Skills for Software EngineersConnect with Gustaf- Linkedin - https://www.linkedin.com/in/gustaf-g/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

  8. Jul 3

    How to Build AI that actually Ships in Production - Aleksandr Kim

    In this talk, Aleksandr Kim, Senior Data Scientist at Intuit, shares his expertise in building AI-powered features in production from fine-tuning BERT models in cyber security to engineering scalable data verification platforms. We explore the reality of moving beyond messy research code to build observable, cost-effective AI agents and automated pipelines.You’ll learn about:- Translating traditional machine learning metrics into actionable business outcomes- Validating large language model behavior through robust evaluation and alignment techniques- Pivoting from a generic chatbot project to high-value Slack automation workflows- Structuring outputs and guided reasoning layers to eliminate trivial AI summaries- Defining the overlapping skills between AI engineers, data scientists, and full-stack software engineers- Implementing multi-LLM routing logic and token caching to minimize enterprise API expenses- Identifying critical data infrastructure bottlenecks to determine when to pivot or drop an AI pilotTIMECODES:00:00 AI Engineering Production and Scalability06:12 Intuit Ecosystem and QuickBooks Products12:17 Aligning ML Metrics with Business Outcomes18:52 AI Engineers Conducting Customer Interviews25:13 Structured Output and Guided Reasoning31:13 Defining AI Engineering vs Software Engineering37:20 Cost Optimization and Multi LLM Routing43:26 UI Trends and Token Management in Industry49:33 Future Career Trends in AI Engineering55:46 Data Infrastructure Bottlenecks and ML FailuresThis session is designed for mid-to-senior level Data Scientists, Machine Learning Engineers, and Software Engineers who want to develop a highly practical, production-first approach to generative AI. It is especially useful for technology leads focused on reducing token overhead and building self-correcting agentic systems.Connect with Aleksandr- Website - https://alexkimds.github.io/- Linkedin - https://www.linkedin.com/in/aleksandrkim/

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About

DataTalks.Club - the place to talk about data!

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  • Creator
    DataTalks.Club
  • Years Active
    2020 - 2026
  • Episodes
    226
  • Rating
    Explicit
  • Copyright
    © DataTalks.Club
  • Show Website
    DataTalks.Club

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