ARTICLES
AutoGUI: Engineers, Stakeholders & Vibe Coding on the Same Page | Xebia | Caio Benatti Moretti| 7 min | AI Engineering & Collaboration
A thoughtful look at “vibe coding” as a collaboration layer rather than a shortcut. Caio argues that tools like AutoGUI can align engineers and stakeholders by making intent, constraints, and trade-offs explicit—without turning software development into prompt chaos.
Battle-Testing Lynx.js at Allegro | Allegro Tech | Wojciech Moczydłowski, Tomasz Gębarowski | 8 min | Frontend Engineering
Allegro shares real-world lessons from stress-testing Lynx.js in production. The post covers performance bottlenecks, failure modes, and what breaks when modern JS frameworks meet real traffic and long-lived applications.
Pick Your Agent: Use Claude and Codex on Agent HQ | GitHub | Mario Rodriguez| 5 min | Developer Platforms
GitHub introduces Agent HQ, allowing developers to choose between Claude and Codex when building agents. It’s a clear step toward model-agnostic agent infrastructure embedded directly into developer workflows.
Docker Sandboxes: Run Claude Code and Other Coding Agents Unsupervised—But Safely | Docker | Eric Jia, Srini Sekaran | 6 min | AI Tooling & Security
Docker explains how sandboxed environments let teams run autonomous coding agents without exposing host systems. A practical approach to balancing agent autonomy with isolation, permissions, and reproducibility.
Google Releases Conductor: A Context-Driven Gemini CLI Extension | MarkTechPost | Michal Sutter | 6 min | Agentic Tooling
An overview of Google’s Conductor, a Gemini-based CLI extension that stores context as Markdown and orchestrates multi-step agent workflows—pointing toward more stateful, reproducible CLI agents.
10 strategies to reduce MCP token bloat | The New Stack | Bill Doerrfeld| 7 min | LLM Infrastructure
A practical guide to controlling token growth in Model Context Protocol (MCP) systems. Covers schema design, context pruning, and architectural patterns that keep agent costs predictable at scale.
NEWS
The latest Comet release improves query performance, stability, and Spark interoperability—continuing DataFusion’s push toward production-grade, high-performance analytics.
FREE COURSES
DATATube
AI in Practice: Claims Handling, Video Labeling & Scalable AI Use Cases | Diederick Greveling, Jeroen Overschie |1h
In this video, we explore practical, real-world AI use cases that are already transforming organizations, including:
- AI-powered claims handling
- Video labeling and intelligence
- Automated decision support and operational optimization
TOOLS
Anthropic’s latest Opus release focuses on stronger reasoning, longer context, and improved reliability for complex agent workflows.
OpenAI introduces GPT-5.3 Codex, optimized for code understanding, refactoring, and multi-step programming tasks.
Deno Sandbox enables safe execution of untrusted code with fine-grained permissions—useful for running AI agents, plugins, or user-generated scripts.
CONFS, EVENTS, WEBINARS & MEETUPS
Data & AI That Matter From systems to people: building data and AI with real-world impact| Webinar Online | March 26, 2026
Not all data and AI initiatives deliver value. This webinar series focuses on impact over hype — how data platforms, AI systems, and teams can be designed to genuinely support people, decisions, and outcomes.
PINNACLE PICKS
Your last edition top picks:
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.
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.
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.
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.
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