15 posts about agentic coding by 8 contributors.
Know agentic coding? Share what you know with developers who are learning it.
Explains how Claude Code on Amazon Bedrock in AWS GovCloud supports agentic coding workflows for organizations with security, compliance, and controlled deployment requirements.
Explains how GitHub Copilot dynamic workflows adapt planning, repository exploration, code changes, and testing to complete multi-step development tasks.
Learn how to test Claude Opus 5.5 on a real software project using repository analysis, debugging, refactoring, testing, code review, and agentic coding workflows.
Learn how to compare Claude Opus 5.5 with other AI coding models using real-world development tasks, benchmarks, testing, tool usage, cost, and developer rework.
Andrew Ng’s AI engineering skills map identifies essential capabilities for working with coding agents. Software architect Mahesh Chand expands the map to include customer understanding, product judgment, workflow validation, feature prioritization, scalability, security, and responsible AI autonomy.
Learn how GitHub Copilot in Microsoft Teams can turn team conversations into coding workflows, including agent sessions, collaboration, repository access, and development tasks.
Learn how GitHub Copilot Agent Plugins 1.0 enable portable coding workflows across VS Code, Copilot CLI, and the Copilot app with reusable tools and automation.
Measure AI coding agent cache efficiency by analyzing context compaction, model switching, cache reuse, latency, token usage, and performance across agent workloads.
Benchmark GitHub Copilot agent tool-call retries and measure their impact on compute usage, latency, token consumption, reliability, and overall AI coding performance.
Benchmark context compaction strategies for AI coding agents by measuring cache efficiency, token usage, latency, model performance, and workload reliability.
Explore GitHub Copilot coding agent workloads, context caching, tool failures, retry behavior, and practical strategies for improving AI coding agent performance and efficiency.
Qwen3.6-35B-A3B runs only 3B active params yet beats dense 27B models on coding tasks. Here's what that means for your AI workflow.
See what AI UI design tools do and how to choose between Claude Code, OpenAI Codex, and Google Antigravity to build, refactor, and validate modern interfaces.
Qwen3-Coder, Alibaba's advanced agentic code model, is revolutionizing software development. This 480B parameter MoE model excels in agentic coding, browser use, and tool use, outperforming many open-source and even proprietary models like Claude Sonnet-4. With a 256K context window, it understands repositories, follows instructions, and acts as a true coding agent, pushing the boundaries of AI-driven software engineering.
Nidhi Sharma4 posts · 13.9k reads2
Aarav Patel4 posts · 7.5k reads3
Sarthak Varshney2 posts · 9.7k readsMVP4
Rohit Gupta1 post · 11k readsMVP5
Mahesh Chand1 post · 4.5k readsMVP
DevSocialUpcoming · 3rd editionAI Agents ConferenceNov 23–27, 2026Live onlineMembers only17days leftRegisterPublish an article in this category and earn +1,000 SHARP when it is approved.
Write an article
