ARTICLES
The AI Evolution of Graph Search at Netflix | Netflix Tech Blog| 6 min | Graph Search & AI
Netflix describes how its knowledge‑graph search moved from rule‑based queries to an AI‑powered system that uses embeddings and reinforcement learning to personalise results. The blog outlines challenges like cold‑start content and context‑aware recommendations and explains how graph neural networks and offline/online evaluation pipelines improved discovery.
Ads Candidate Generation Using Behavioral Sequence Modeling | Pinterest Engineering| 8 min | AdTech & Sequence Models
Pinterest shares how modelling user behaviour as sequences (rather than static profiles) improves the diversity and relevance of ad candidates. The post covers the transition from collaborative filtering to recurrent neural networks and sequence‑aware embeddings, with improvements in click‑through rates and latency.
Tracking Feature Lineage in Feast with OpenLineage | Feast Blog | Nikhil Kathole & Francisco Javier Arceo | 5 min | Data Lineage & ML Ops
Feast added native OpenLineage integration, allowing teams to automatically record end‑to‑end feature lineage across their ML pipelines. The integration uses Marquez as a backend and tracks feature definitions, materialisation jobs, and data sources, enabling unified visibility across systems and simplifying compliance and debugging
Demystifying Evals for AI Agents | Anthropic Engineering | Mikaela Grace, Jeremy Hadfield, Rodrigo Olivares & Jiri De Jonghe | 8 min | Agent Evaluation
Anthropic explains why evaluating agentic systems is hard and proposes a framework that breaks evaluations into tasks, trials, graders and outcomes. The article emphasises that tests should be recorded via transcripts and outcomes, enabling reproducibility and continuous improvement
From Building AI Infrastructure to Shaping Its Standards: Lambda Joins OCP | Lambda Blog | Alee Fong | 3 min | AI Infrastructure
Lambda joins the Open Compute Project Advisory Board to help define standards for high‑density, composable AI infrastructure. The post outlines how Lambda’s production experience in building GPU data centers can inform reference architectures, power delivery standards and hybrid cooling frameworks
Building Reliable LLM Batch Processing | The Neural Maze | MIGUEL OTERO PEDRIDO AND ALEXANDRU VESA | 7 min | Batch Processing & LLM Ops
An opinionated guide on how to run large batches of LLM queries reliably. The post discusses queue‑based architectures, exponential backoff, cost control, and test harnesses to ensure outputs meet quality requirements.
DATATube
Qwen3 Multimodal Embeddings: Finally, RAG That Sees | Sam Witteveen |1h
An in‑depth talk exploring how RL can automate bug fixing, performance tuning and other software engineering tasks using program state as feedback.
TOOLS
An open‑source repository of system prompt templates for Claude models. The repo provides task‑specific instructions for code generation, testing, refactoring, and debugging, enabling consistent prompt engineering.
Moltbook introduces an open‑source platform for running agentic LLM workflows locally. It provides a notebook‑like interface, a pipeline builder and integrations with local embeddings, allowing developers to experiment with retrieval‑augmented generation and multi‑agent chains without sending data to the cloud.
CONFS, EVENTS, WEBINARS & MEETUPS
Serving LLMs in Production: Performance, Cost and Scale| Ioana Apetrei, Igor Šušić, Demetrios Brinkmann |ML Community| February 5 | Webinar online
MLOps Community webinar covering best practices for serving LLMs at scale, including latency, throughput and cost trade‑offs.
Building AI Systems with Databricks: From Concept to Deployment| Databricks | February 18 | Webinar online
Databricks hosts a series of foundational workshops for practitioners beginning their data and AI journey.
TechByte: Digital Sovereignty as a Superpower| Google | Webinar online |February 24 2026
A Google Cloud event discussing how organisations can leverage digital sovereignty to build compliant, resilient cloud architectures.
PINNACLE PICKS
Your last edition top picks:
Multi-Agent Warehouse AI: A Command Layer for Operational Excellence and Supply-Chain Intelligence | NVIDIA Developer Blog | Tarik Hammadou and Jeremy Coupe | 8 min | Agentic Systems & Industrial AI
NVIDIA presents a real-world multi-agent architecture for warehouse operations, where specialized agents coordinate planning, perception, optimization, and execution through a shared command layer. The post shows how agent hierarchies, event-driven orchestration, and simulation-backed decision loops enable resilient, scalable supply-chain intelligence.
Prompt Engineering for AI Models (Full Course) | Simplilearn | 2 h course | Prompt Engineering
A comprehensive introduction to prompt engineering covering how to craft effective prompts, use context windows, chain prompts for complex tasks and debug model outputs. Real examples and live demos help students practice constructing prompts that elicit accurate, useful responses.
Data & AI Warsaw Summit 2026| Warsaw | April 2026
A two‑day conference covering data engineering, analytics and AI. Speakers from global tech firms share case studies on lakehouse architectures, streaming, feature stores and agentic applications. Use code datapill10 for a 10% discount on tickets.
NVIDIA presents a real-world multi-agent architecture for warehouse operations, where specialized agents coordinate planning, perception, optimization, and execution through a shared command layer. The post shows how agent hierarchies, event-driven orchestration, and simulation-backed decision loops enable resilient, scalable supply-chain intelligence.
Prompt Engineering for AI Models (Full Course) | Simplilearn | 2 h course | Prompt Engineering
A comprehensive introduction to prompt engineering covering how to craft effective prompts, use context windows, chain prompts for complex tasks and debug model outputs. Real examples and live demos help students practice constructing prompts that elicit accurate, useful responses.
Data & AI Warsaw Summit 2026| Warsaw | April 2026
A two‑day conference covering data engineering, analytics and AI. Speakers from global tech firms share case studies on lakehouse architectures, streaming, feature stores and agentic applications. Use code datapill10 for a 10% discount on tickets.
_____________________
Have any interesting content to share in the DATA Pill newsletter?
