A 6-point listicle based on curl creator Daniel Stenberg's call to verify software supply chain components instead of trusting them blindly.
Learn how AI shifts the SDLC bottleneck, why dogfooding and unshipping matter, and why learning speed is the only advantage from Adam Wolff's Claude Code war stories.
The March 2026 release of VS Code's Python extension introduces opt-in symbol search in virtual environments and an experimental Rust-based parallel indexer for faster performance.
A framework using mutual information directly from noisy measurements enables unified evaluation and optimization of imaging systems, outperforming traditional metrics and end-to-end methods with lower compute.
ServiceNow positions as AI control tower, offering governance for multi-tool development while letting developers choose their preferred AI coding tools.
Q&A on how an AI researcher automated repetitive trajectory analysis using GitHub Copilot, creating eval-agents to enable team-wide agent-driven development.
Learn to enable symbol search in installed packages and the experimental Rust‑based parallel indexer in VS Code’s March 2026 Python release. Step‑by‑step with settings and troubleshooting.
Learn how to coordinate multiple AI agents at scale: define boundaries, use async communication, implement an orchestrator, handle conflicts, and avoid common failures.
Explore how agent-driven development with GitHub Copilot automated benchmark analysis, enabling self-service automation and collaborative innovation within the Copilot Applied Science team.
A step-by-step guide to joining the Python Security Response Team (PSRT), including eligibility, nomination, voting, and onboarding, with tips for success.
Learn how to contribute to the official Python blog via Git and Markdown. Step-by-step guide for submitting posts using GitHub pull requests.
Learn how Intuit engineers Chase Roossin and Steven Kulesza tackle the challenge of scaling multi-agent AI systems—covering communication, conflicting goals, architecture, testing, and real‑world lessons.
Explore why JavaScript's Date object causes common bugs and how the Temporal proposal, with contributions from engine projects like Boa, provides a robust solution.
Six insights on using mutual information to directly evaluate and optimize imaging systems, surpassing traditional metrics and end-to-end methods.
Learn 7 strategies to secure MCP tool calls in .NET using the Agent Governance Toolkit—covering scanning, sanitization, policy, and auditing for safe AI agents.
Intuit engineers reveal that coordinating multiple AI agents at scale is the hardest engineering problem today, citing shared context, conflict resolution, and cascading failure risks.
JavaScript's Temporal proposal, led by Bloomberg's Jason Williams, aims to fix the notoriously broken Date object with immutable, timezone-aware APIs, promising to eliminate decades of time-related software bugs.
Step-by-step guide to connect MCP-compliant agents like Claude Code to Atlassian's Teamwork Graph using the CLI, Cipher queries, and Rovo Chat's Max mode.
Learn how to manage AI agent sprawl using ServiceNow's governance model. Step-by-step guide to implement controls while letting developers use their preferred tools.
Python 3.15.0a5 fixes a build error in a4 and introduces PEP 799 (profiler), PEP 686 (UTF-8 default), PEP 782 (PyBytesWriter), JIT speedups, and improved error messages. Not for production.