404 summarised stories about AI Coding Agents, each linking back to the original source. Browse all topics →
Product Hunt 2 months ago 53
Gauge announced a platform that enables AI agents to be embedded directly into customer codebases for development tasks. The company targets integration into engineering workflows as a core distribution strategy. This shifts how AI coding tools reach users from standalone access to built-in collaboration within existing development environments.
IEEE Spectrum 2 months ago 37
AI-driven software engineering at AMD has expanded from copilots into agent-based workflows across the SDLC, with agents generating and validating code, tests, and release artifacts. AMD says AI now produces a 30 percent overall productivity boost and has resolved RSX issues automatically from 6% to more than 75% between October 2025 and June 2026. AMD credits continuous learning loops and refinements to agent objectives—rather than retraining models—so the next change is enabling collaborative agent swarms to independently propose and optimize solutions under human-defined goals.
Product Hunt 2 months ago 10
Viso Now launched as a self-building AI vision platform that converts images, video, and camera feeds into computer vision applications. It shows 86 followers on the listing. It removes the need for model training, annotation, or writing code by generating the vision logic and live dashboards automatically.
Together AI 2 months ago 42 ● 2 sources
DeepSeek V4 Pro 0813 and Claude Fable 5 were tested on DeepSWE, a software engineering benchmark, revealing a 90x cost difference ($0.24 vs $21.63 per rollout) with Fable leading 69.7% to 62.8% on first attempt but Pro matching or exceeding Fable at higher retry counts. A cascading strategy—running Pro first and escalating to Fable only on failures—achieves 82.7% accuracy at $8.28 per task, outperforming either model alone by 13 percentage points while costing 62% less than Fable standalone. The models disagree on 0.39 correlation, making them complementary: Fable excels in Rust and data serialization while Pro handles concurrency and stateful reactivity better.
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25 October 2026
The biggest throughline today wasn’t a single model release—it was the shift from “AI as a chatbot” to AI as operational infrastructure. Microsoft Research open-sourced Agensh, a decentralized multi-agent harness that scales a coding workflow from 1 to 1,024 agents without a central orchestrator, reporting a 30-minute milestone where pandoc hit 30% passing at 128 agents, and a final mean test-pass rate rising from 19.31% (1 agent) to 28.78% (128 agents). Cognition upped the practicality angle with an open-source Devin Vulnerability Fixes plugin that targets specific remote code execution advisories across PHP, Node.js, and self-managed GitLab—down to CVE-2026-110264 (CVSS 10.0)—by combining read-only inventory, approval-gated changes, and before/after tests to generate one pull request per repo.
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