Big Data Conference Europe 2025
2025-11-19..2025-11-21
-- online --
[Big Data Conference Europe 2019, Big Data Conference Europe 2022, Big Data Conference Europe 2023, Big Data Conference Europe 2025]
who it's for
data engineers, data platform architects, machine learning engineers, data scientists, engineering managers, security engineers
topics
Apache Iceberg REST catalog; dbt with DuckDB pipelines; embedding models for search; secure LLM pipeline design; streaming data security; Apache Spark declarative streaming; real-time data ingestion for AI; retrieval augmented generation tooling; prompt engineering best practices; data contracts and lineage; running databases in cloud-native environments; computer vision with generative AI
| title | author | length |
|---|---|---|
| AI That Reads Emotions: What It Means for Data Privacy, Consent, Your Teams | Ana Catarina de Alencar | 46m |
Clear claims about harms and fixes: emotionally responsive systems (Replica and Character AI, ChatGPT used as companion, Mattel/OpenAI Barbie) drive measurable… | ||
| Data Observability - System Health to Business Health | Sathish KS | 41m |
Claims measurable metrics: Data Downtime as time series of partial/error/missing/inaccurate data, Data Flowtime as source-to-ready latency, and a contractual… | ||
| Use dbt and DuckDB Instead of Databricks for Data Processing | Niels Claeys | 43m |
Claim: dbt + DuckDB replaces Databricks for many medium workloads by running DBT SQL run dbt in-process against Parquet/Iceberg on blob storage; benchmarks… | ||
| How AI and Digitalization Are Reshaping the Business Landscape | Lauri Antalainen | 45m |
Demo shows concrete results: consulting work across 100+ companies in 8 countries maps common wastes and produces a digital roadmap that standardizes… | ||
| Embedding AI: Don’t Burn Your Fingers in the Heat of the AI revolution | Kyra Goud | 47m |
Claim: don’t treat AI as a single API call — build a platform so models run reliably and legally. Practical tools and outcomes: Kubernetes/OpenShift for… | ||
| AI vs. Karen: Real-Time Customer Sentiment Detection at Scale | Josef Goldstein | 47m |
A live streaming pipeline is built that ingests customer messages via Apache Kafka and Apache Flink, calls models per message and writes sentiment into a… | ||
| The Seven Deadly Sins of Streaming | Giannis Polyzos | 40m |
Claim: Fluss columnar streaming storage replaces Kafka+Flink patterns by exposing streaming tables that are directly queryable and enforce schemas… | ||
| Agile Strategies for High-Impact Data Science & Machine Learning Projects | Ganesh Kumar Suresh | 43m |
Argues that treating data work as experiments with timeboxed experiments and synchronous demos shortens cycles, separates research from implementation, and… | ||
| Metadata as a Control Plane: Inside the Apache Iceberg REST Catalog | Viktor Kessler | 39m |
Claims Iceberg’s REST catalog becomes the control plane for compute independence, governance and automation; a concrete implementation called Lakekeeper (Rust)… | ||
| Latency, Throughput & Fault Tolerance: Building a Modern Database | Guy Shtub | 40m |
Shows a concrete migration and measurable wins: migrated 177 Cassandra nodes to 72 CLAB nodes, P99 40–125ms → 15ms, and claims 1.1M ops/s at <1ms P99 on AWS… | ||
| Behind the Firewall: Designing Secure LLM Pipelines for Regulated Data | Yann Stoneman | 38m |
Reference architecture shows running LLMs entirely inside the security perimeter with concrete artifacts: cryptographic model signing to verify provenance, a… | ||
| Breaking Down Data Warehouses: What to Know Before You Choose | Andrew Miller | 43m |
Defines data warehouse by concrete tradeoffs: columnar vs row storage shows a ~1 GB sample (100 projects × 3,000 issues × 5 years × ~700 bytes) reads in ~8s… | ||
| How to Analyze Terabytes of Data from GitHub Archive at High Speed | Aliaksandr Valialkin | 48m |
Shows a working pipeline that loads gharchive JSON lines, stores them in Victoria Locks, and runs real queries on a playground backed by a single Kubernetes… | ||
| The Hidden Cost of Data Debt | Sayantan Ghosh | 40m |
Claim: unnoticed data debt silently degrades pipelines and product metrics, sometimes causing catastrophic losses (460 million lost in 45 minutes cited as a… | ||
| Leading Without Authority: A CTO’s Journey from Product to Services | Roberto Freato | 46m |
Claim: sustained hands‑on credibility beats formal authority; method: Trojan horse proof‑of‑concepts—small, focused builds that land business outcomes. Tools… | ||
| Making AI Resources Easy to Find, Use, and Connect | Ville Tenhunen, Susanne Kührer | 43m |
A federated European platform claims to make AI resources discoverable and reusable and already exposes a metadata catalogue with REST APIs plus a Python SDK… | ||
| Delivering enterprise agentic solutions at scale | Andy Eva-Dale, Lukasz Madrzak-Wecke | 40m |
Prototype becomes an enterprise Reed.AI MVP that handles 50 million CVs with a 1,000‑concurrent‑user SLA, built on AWS with RabbitMQ and EKS, OpenAI… | ||
| Streaming & Eventing for Top Management | Fabrizio Lazzaretti, Jens Muller | 29m |
Allianz frames a concrete claim: shifting a brownfield online shop to event‑driven architecture with Kafka and Apache Flink produces measurable business… | ||
| Can AI See You? Your Introduction to Computer Vision and GenAI | Lennard Schiefelbein, Daniel Hirsch | 44m |
Starts from pixels and RGB then shows concrete pipelines: convolutional nets for classification, bounding boxes and pixelwise segmentation, real‑time face… | ||
| PipeOps: Why Idempotency Matters | Axel Neergaard | 41m |
Claims that idempotent pipelines let teams rerun only failed partitions, cut ops time, and eliminate duplicates and data loss by design. Implements… | ||
| Unlock AI Growth: Build Your Exponential Organization - No Magic Required | Valentin Nemeth | 43m |
Claims that reworking operations around Exponential Organization principles yields roughly 10x potential growth and reports a best practical outcome of 7.2x… | ||
| Realtime Analytics with StarRocks in Wellness Booking | Anton Borisov, Emiliano Mancuso | 43m |
Fresha replaces a brittle Postgres + Snowflake mix with StarRocks sitting between Iceberg lake tables and Kafka/Flink CDC, handling half a million bookings per… | ||
| How MySQL Configuration Tuning Boosts App Performance | Roman Agabekov | 26m |
Research runs real-world apps (Drupal Commerce, Laravel stores, WordPress, PrestaShop) on EC2 with JMeter-driven workloads and compares default vs tuned… | ||
| Securing RAG Pipelines with Fine Grained Authorization | Sohan Maheshwar | 39m |
Claims that Relationship‑based Access Control (Zanzibar/ReBAC) prevents RAG leaks by pre-filtering vector DB queries with authorized object IDs and by… | ||
| The AI Software Architect: Revolution or Illusion? | Lee Blum | 45m |
Claims that AI augments architects not automates them, demonstrated by concrete uses: ChatGPT for initial HLD drafts, Copilot 365 for email/thread… | ||
| How We Created a Thinking Robot? | Grigorij Dudnik | 42m |
A team builds robots that run a local on-board LLM and combine it with fast control models, showing a prototype that solves the trolley problem and a wheeled… | ||
| Running Non-Cloud-Native Databases in Cloud-Native Environments | Alkin Tezuysal | 44m |
Shows concrete tactics and failures: use operators automate failover and upgrades but expect missing backup/restore bells, favor a replica model over… | ||
| Leveraging Azure PaaS for Real-Time Social Media Analysis | Vivek Singh | 31m |
Claims a working serverless pipeline that pulls live social data with Azure Event Hubs, ingests via Azure Functions, and analyzes in Azure Databricks using SQL… | ||
| AI, ML, and the Ceph Advantage: Scalable Storage for Smarter Workflows | Kenneth Tan | 31m |
Ceph serves as object block and file storage for AI/ML pipelines, with live multi‑site replication, scrubbing to detect silent disk failure, and automation to… | ||
| Transforming Legal Services with AI: A Norwegian Perspective | Katrine Lund | 26m |
DigiRett claims a working hybrid system that mixes custom GPT fine-tuned on case documents, automation built in NA10, and a lawyer-in-loop risk-assessment… | ||
| AI for Healthcare | Ronni Gamzu | 48m |
Claims that healthcare hoards usable data but still runs old workflows and gives concrete examples: 1,600‑bed hospital with crowded ERs and 50 operating… | ||
| Are You Ready for AI Agents? How Finance Teams Can Unlock Real Value From Data | Gerlyn Tiigemäe | 48m |
Claim sets the bar: most organisations are not ready and MIT-style audits show 95% of AI investments don’t reach production. Concrete wins exist—JP Morgan runs… | ||
| AI Meets Cybersecurity: Boosting Speed Without Losing Control | Giedrius Meskauskas | 44m |
Claims that AI finds baselines and flags anomalies for zero day detection, shows real use of the MITRE ATT&CK framework to map detections, and reports endpoint… | ||
| Databricks as the Foundation for GenAI: What’s New and What Works | Awadelrahman M. A. Ahmed | 36m |
Latest Databricks features and concrete behaviors are detailed: Agent Bricks (declarative agent patterns, built-in evaluation, beta and region-limited)… | ||
| Hitchhiker’s Guide for Software Architects: Legacy Migration | Marc Schuh | 45m |
Migrating a decades‑old Microsoft stack succeeds by replacing components incrementally: run new web frontend and services side‑by‑side, write back to the… | ||
| Hyperpersonalization with Agents: Building Next-Generation MarTech Solutions | Nensi Hakobjanyan | 39m |
Claims a realistic production pattern: hyperpersonalization can be built with agent workflows that catch intent, check inventory and create refunds or… | ||
| AI and Gender: Building Fair AI Systems for the Future | Maria Zarotiadou | 34m |
Concrete numbers and concrete fixes: only 28% aware of gender bias, 66% want government regulation and people give tech companies only 32% trust; documented… | ||
| Training: Building an Online Learning Center for a NoSQL Database | Guy Shtub | 37m |
A free, self‑paced training site called ScyllaDB University is built with a WordPress/LearnDash LMS, short videos, quizzes and browser‑hosted hands‑on labs… | ||
| Deepfake Threats in Business: What You Need to Know | Silviu Gresoi | 41m |
Claims that AI fraud jumps 350% between 2023 and 2025 and that 77% of organizations face deepfake attacks, backed by cases: a CEO-voice call leading to a… | ||
| You Don't Need Data Storytelling If You Do Dashboards | Martynas Jocys | 43m |
Claim: traditional data storytelling for slides fails on interactive dashboards, so replace narrative sequences with a clear hierarchy, navigation and… | ||
| AI Lofi HipHop - How Not To Generate AI-Music | Jonas Mayer, Elias Schecke | 45m |
Builds a real-time pipeline that tries to run a 24/7 AI Lofi Radio livestream: generates MIDI with Magenta and a music_vae latent-space approach, uses a… | ||
| Own Your Story: Turning Generative AI into Human-Sized Narratives | Adebola Olomo | 33m |
Claims that anchoring prompts in lived narrative makes generative AI produce brand‑true copy not interchangeable text and delivers repeatable business… | ||
| Modular & Reusable: A Recipe to Scaling Data Across a Portfolio | Matteo Molteni, Johannes Larsson | 41m |
A small central team of three data engineers builds a BigQuery-based ELT platform using Airflow (Astronomer) and dbt, onboarding eight e‑commerce companies… | ||
| From MongoDB to Postgres: Building an Open Source Standard for Document Databases | Peter Farkas | 42m |
Claims that Postgres can act as an open-source backbone for MongoDB workloads, using FerretDB as a compatibility layer that accepts MongoDB drivers unchanged… | ||
| Real-Time Data Ingestions for Data Fabric and AI Applications | Deniz Sendil | 30m |
Oracle GoldenGate claims real‑time ingestion into Apache Iceberg with two replication designs including engineless iceberg ingestion that writes parquet files… | ||
| Building Agentic Workflows in Cursor IDE | Olle Pridiuksson | 44m |
Clear claim: a repeatable framework and repo of templates for multi-step agentic workflows inside Cursor that actually run against GitHub, Linear, Sentry and… | ||
| From Buzz to Benefits: Google AI in Action | Giedre Kirejeva, Aivaras Tucius | 45m |
Claims include concrete numbers and outcomes: a Google survey finds Vertex AI adopters report 74% see ROI and 86% see >6% annual revenue lift, models scan… | ||
| Building an AI Agent on Top of Your API | Pavel Filonov | 44m |
Builds a working AI agent for the HiPerWare energy‑monitoring platform that connects LLMs to product APIs via LangChain, defines callable tools from an OpenAPI… | ||
| 7 Steps to Becoming an AI Pioneer in Your Company | Peter Mesarec | 39m |
Seven concrete steps claim to move a nontechnical employee into an internal AI lead by teaching one tool, connecting it to company data, and shipping tiny… | ||
| Our New AI Coworkers & Enemies | Alex Northstar Enache | 41m |
Claims a team of 10 in one is possible but only with human oversight and incremental rollout, not an out of the box miracle. Demonstrated tools include… | ||
| Build Without Limits - Lessons Learned Working with Data and AI Coding Assistants | Ricardo Sueiras | 42m |
Over the last 12 months of hands‑on use the claim is concrete: generative assistants speed prototyping, debugging and SQL work but they hallucinate without… | ||
| Utilizing Lithuanian Public Sector Big Data to Make the Country Run Smarter | Aistis Raudys | 48m |
Concrete deployments across Lithuania: call-center assistant using Whisper and wav2vec for live speech recognition and LLM guidance with Llama 70B, transport… | ||
| Mastering Enterprise Open Source for Cloud and Vendor Independence | Sune Dalby | 32m |
Three concrete claims guide the session: open source powers vendor agility but hides lock‑in in the surrounding stack, evidenced by Apache Airflow deployments… | ||
| AI and Human Synergy: Crafting Teams for the Future | George Tsiramua | 41m |
Platform called OptiCrew claims to build multifunctional teams using a combinatorial optimization algorithm plus structural‑system analysis to report project… | ||
| RAG, Tooling, MCP, Agents ... and What is Missing? | Andreas Buhlmeier | 37m |
Explains concrete wins and failures: retrieval-augmented generation avoids costly retraining by embedding recent docs but requires careful chunking (15… | ||
| Spark Performance Tuning and Troubleshooting | Marcin Szymaniuk | 34m |
Shows concrete fixes and measured wins: a UDF that makes an HTTPS call is slow because of connection-per-record and becomes fast when a single connection is… | ||
| A Simple Framework for Green-Lighting AI Projects | Max Golikov | 42m |
A clear decision framework appears: use an AI value matrix that scores data access, tech complexity, skills, sponsor support and measurable KPIs. Three… | ||
| How Netflix Built a Real-Time Distributed Graph for Internet Scale | Adrian Taruc | 42m |
Netflix builds a real‑time distributed graph (RDG) using Apache Kafka and Flink for near‑real‑time ingestion, a Key‑Value Abstraction Layer (KV doll) backed by… | ||
| Beyond dbt: Modern SQL Transformation and Lineage with SQLGlot and SQLMesh | Tomas Peluritis | 36m |
SQLGlot is shown as a 24‑dialect parser built on an AST with a Rust tokenizer and reproducible dialect‑agnostic transpilation, enabling column‑level lineage… | ||
| The Protocol Wars: Clash of Titans | Robert Dzisevic | 43m |
Claims that MCP centralizes tool integrations via an MCP server/client pairing and that A2A standardizes agent-to-agent discovery and delegation. Demonstration… | ||
| Rebuilding the Industry: How AI Is Transforming Construction from the Ground Up | Jokubas Vaisvila | 42m |
Construction totals about $13 trillion globally and nine out of ten projects run late with 30 percent cost overruns; AI tools cut simulations from days to… | ||
| A Bayesian Approach to the Cold Start Problem | Agustin Figueroa Nazar | 42m |
Bayesian binomial modeling estimates CTR for cold‑start listings so the ranking system gets enough signal before the reranker takes over. It treats impressions… | ||
| Deep Dive into Data Streaming Security | Olena Kutsenko | 45m |
Concrete failure stories, precise mitigations, and measurable outcomes guide the decision: deployments use Apache Kafka, Apache Flink, Apache Iceberg… | ||
| Pimp My Llama - How to Customize LLMs for Your Business Case | Jonas Mayer, Christoph Bergemann | 50m |
An off‑the‑shelf LLM becomes useful here by concrete steps: LLaMA 3 37B runs the Jonas simulator as a 24/7 Q&A brain, prompt engineering fixes tone and format… | ||
| How to Monetize Innovation and Avoid Leaving Money on the Table | Krzysztof Szyszkiewicz | 43m |
Argues pricing is the highest-leverage profit lever — a 1% pricing lift yields ~11–12% profitability — and AI demands charging for output or success instead of… | ||
| 6 Creative AI Wins — Tested by Startups, Ready for Any Business | Andras Baneth | 36m |
Six concrete methods appear: use an AI‑powered mood‑matching flower shop as a running example, ask 11 practical challenging questions to surface risks and… | ||
| Scaling Data at Ovoko: The Succesful Strategy | Alessandro Pregnolato | 42m |
A four to six week Data Operating System discovery produces concrete deliverables: a hiring roadmap (from seven individual contributors to managers and three… | ||
| MCP Tools as Your Database Engineer | Bobur Umurzokov | 41m |
Claims automation saves 20% development time by using AI agents to design schema, provision branches, seed data, run migrations and create PRs. Live demo uses… | ||
| You Migrated to Apache Iceberg—Now What? Speed, Efficiency, and Cost in the Real World | Amit Gilad | 42m |
Catalog choice, query engine, file format and maintenance decisions determine whether Iceberg actually saves money and speeds queries: Avro writes 2–2.5×… | ||
| Sleeping Through the Volatility: Building an AI Agent for Automated Crypto Trading | Thomas Kampioni | 40m |
A fully automated crypto agent runs hourly price pulls via Binance API, stores data in SQL Express, and uses Python PyTorch Pandas to compute VWMA(20), MACD… | ||
| How to Really Scale AI: Combining Traditional and Agentic Automation | Sara Maldon | 45m |
Claims that scaling fails for process reasons not model limits and shows a concrete hybrid build: SEO research automation that pulls Google Sheets Google… | ||
| Pannel Discussion | From Hype To Value: Real World Applications Of Generative AI And LLMs | Ganesh Kumar Suresh, Thomas Endres, Ivo Moring, Graeme Lipschitz, Agustin Figueroa Nazar, Martin Förtsch | 40m |
Panel reports concrete wins and stumbles: multi‑day tours get reshaped by ticket‑text analysis and pattern clustering, an on‑prem model stack (Chimera local… | ||
| Pannel Discussion | Business Of AI And Data Products From Product Management To ROI | Alessandro Pregnolato, Anton Borisov, Devesh Prasad, Emiliano Mancuso, Pavel Filonov, Viktor Kessler | 44m |
Panel gives concrete outcomes not hype: a scraped-duplicates problem gets solved with SQL de-dup solved in 2–3 hours instead of months of ML, simple heuristics… | ||
| Pannel Discussion | Agentic Automation: Are AI Agents The Future of Digital Work | Jochen Doppelhammer, Florian Gather, Olle Pridiuksson, Adebola Olomo, Valentin Nemeth, Eduard Shlepetskyy | 44m |
Panel claims a portfolio of 45 AI agents and concrete deployments: trade finance automation that drops case handling from three hours to eight minutes, a… | ||
| From Data Silos to Smart Systems: The AI Integration Playbook | Marty Weintraub | 49m |
Claims the problem is data disconnection not scarcity and offers a field‑tested roadmap: sort what you already have, align decision‑makers, and build MVPs that… | ||
| Advanced Prompt Engineering and Beyond | Marcin Szymaniuk, Bartek Sadlej | 43m |
Claims specific performance gains from techniques and clear failure modes for production: shows retrieval pipelines using Hyde and ColBERTv2 and re‑ranking… | ||
| Beyond Black-Box AI: Designing Transparent Automation for Regulated Industries | Jochen Doppelhammer | 46m |
Claims a concrete method called Chain-of-Work that pairs LLM reasoning with code-based execution to produce a full audit trail and reproducible runs, not just… | ||
| AI Hits Different - A Music Album From the Machine Room | Martin Förtsch, Ivo Moring | 01h 03m |
Claims a full album is produced in weeks using a concrete pipeline: large language models generate lyric drafts with a personal corpus, Suno AI → Splitter AI →… | ||
| AI and the Future of Learning: Breaking Barriers, Unlocking Potential | Graeme Lipschitz | 43m |
Starts with concrete results: MindSpark: +0.37 SD in math, +0.23 SD in Hindi from RCTs and under $2/month at scale, showing personalization that actually moves… | ||
| Robots Among Us: Advances in AI for Everyday Androids | Thomas Endres, Florian Gather | 48m |
Claims a working pipeline: train agents in Isaac SIM (they run ~4,000 simulated robots, show progress at ~100 and ~300 epochs), fine‑tune a robotics foundation… | ||
| Data Contracts VS Data Chaos: A Survival Story | Eugene Klyuchnikov | 50m |
Claims a pragmatic path from napkin to registry: start with a humble empty document as a machine-readable data contract, register it centrally, version it, and… | ||
| When AI Agent Teams Work (And When They Just Create More Work) | Ben Slavin | 57m |
Argues that agent teams pay off only when orchestration, tool access and governance are concrete not conceptual: shows Walmart Element agent mesh running… | ||
| The Art of Prompt Engineering: Best Practices for Effective AI Interactions | Aurimas Paulius Gircys | 47m |
Shows concrete methods and results: uses chain-of-thought prompting (run 3–5 times for self-consistency), implements self-reflecting systems that evaluate and… | ||
| How to be an AI First company | Alex Northstar Enache | 49m |
Claims concrete enough to act on: upskilling 6,000 people yields measurable gains, clients see about a 20% productivity increase and roughly two months back… | ||
| Learnings from over 800 Processes Automated. Success and Failure stories | Eduard Shlepetskyy | 39m |
Claim: the team automates over 800 processes automated and runs customers with 300+ processes and 100+ unattended robots, yet maintenance, scheduling and SLAs… | ||
| Smarter AI for Smaller Teams: Scaling Automation Without Breaking the Bank | Devesh Prasad | 32m |
Claims a £245,000 UKRI grant and KTP with University of Glasgow funds a one‑person build that cuts a quoted £50–100k data‑lake cost to ~£300 using AWS credits… | ||
| AI-Powered Learning Pathways & Skills Development | Norbert Faniszlo | 52m |
Claims a workable pipeline that turns static L&D into personalized, measurable learning: content generation with ChatGPT and Canva, background profiling with… | ||
| How to Improve your Persuasion Skills with AI Personas and Frameworks | Andras Baneth | 43m |
Claims a working prototype called Pura AI prototype that uses play.ai voice clones and fed PDFs to simulate audiences, builds 20–30 detailed personas and tests… | ||
| Apache Spark's New Declarative Streaming Pipelines in Action | Frank Munz | 45m |
Shows a concrete pipeline that processes 8 billion daily flight events using Spark’s Declarative Pipelines donated to Apache Spark in June 2025, not marketing… | ||
| The Future of Product Storytelling: How AI is Reshaping Video Creation | Tomas Sakro | 44m |
Claims studio-quality product videos go from weeks to hours and the demo shows exactly how: image-to-image frame interpolation stitches stills into 5–10s clips… | ||
| Investigation: Data Platforms on European Cloud Providers | Gergely Soti | 35m |
Claim: an open source, Kubernetes-based minimum viable data platform runs on multiple European clouds and meets analytics, scheduling and IAM needs… | ||
| Real Time Architectures Real Fast | Hugh Evans | 41m |
Claims a workable sub-1s end-to-end latency for live ADSB aircraft tracking using entirely OSS; pipeline is Raspberry Pi + SDR decoder feeding CFKA, Click… | ||
| Building an MCP Server for Tesla Before Elon Lost the Plot | Arturo Opsetmoen Amador | 44m |
A working MCP server connects TeslaMate to LLMs so vehicle telemetry (drives, battery, GPS, tire pressure) becomes conversational: deployed on GCP with… | ||
| Beyond the Dashboard: Building Trustworthy Data with Observability at PAYBACK | Natalia Sokolowska | 41m |
PAYBACK shows concrete steps to make data trustworthy: dbt unit tests in CI/CD that catch logic regressions, row-level dbt data tests and regex checks for… | ||
| Lets Deeploy Flink - Uncovering Hidden Depths of Yarn, Docker, Kubernetes & Beyond | Naci Simsek | 44m |
Compares concrete Flink deployment choices—Standalone, Docker, Kubernetes, YARN—with how each manages artifacts, HA, scaling and savepoints and when to use… | ||
| C-Level AI: Lead, Don’t Just Deploy | Sarunas Chomentauskas | 44m |
C-level leadership runs an experiment that stops doing work and asks AI to handle every task, measurements show dramatic speedups (sales research 1 hour to… | ||
| Data Contracts | Jochen Christ | 47m |
Claims that data contracts act like an API for datasets, specified in YAML and now standardized as the Open Data Contract Standard, and that they are… | ||
| AI-Powered Search in Modern E-Commerce | Stanko Kuveljic | 39m |
A custom two-tower model trained on millions of queries and historical clicks uses contrastive loss to create domain embeddings and delivers a 21% increase in… | ||
| The Machines Did Not Make Us Redundant (Just Yet) | Jorge Garcia de Bustos | 44m |
Godel reports concrete outcomes: five of six customer engagements adopt AI tools (Copilot, Cursor, Devon AI) by late 2025, internal R&D shows ~17.5× ROI—one… | ||
| Event Design with AsyncAPI, DDD, and AI | Annegret Junker | 39m |
Claims that Domain Storytelling, Event Storming and Context Mapping plus LLM prompts can generate real AsyncAPI specs from workshop artifacts and that GitHub… | ||
| Mastering AI Video Creation: Simplifying Complex Products for Business Success | Marina Meli | 46m |
Claims a repeatable process: plan, script, AI visuals, voice work, and edit into sub-3‑minute explainer videos that hold attention and drive sales; cites… | ||
| nothing matches | ||