Notes from my Thoughtworks colleagues on AI-assisted software delivery
What spec-driven development gets wrong
The most powerful AI software development platform with the industry-leading context engine.
Priivacy-ai/spec-kitty
Spec-Driven Development for serious software developers. Spec Coding with with Claude, Cursor, Gemini, Codex. Kanban dashboard, git worktrees, auto-merge and more.
Exploring Generative AI
Notes from my Thoughtworks colleagues on AI-assisted software delivery
Exploring Generative AI
Notes from my Thoughtworks colleagues on AI-assisted software delivery
The Economic Benefit of Refactoring
Notes from my Thoughtworks colleagues on AI-assisted software delivery
scaleapi/SWE-bench_Pro-os
SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
Measuring the Impact of Early-2025 AI on Experienced Open-Source...
Despite widespread adoption, the impact of AI tools on software development in the wild remains understudied. We conduct a randomized controlled trial (RCT) to understand how AI tools at the...
From OSS to Open Source AI: an Exploratory Study of Collaborative...
AI development is embracing open-source paradigm, but the fundamental distinction between AI models and traditional software artifacts may lead to a divergent open-source development paradigm with...
Codex | AI Coding Partner from OpenAI
The best way to build with agents. Codex accelerates real engineering work, from planning and building features to refactors, reviews, and releases—working seamlessly across your tools.
SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
Large Language Model (LLM) agents have been widely adopted in modern software development workflows. SWE-bench [13] and related works [23, 24, 22, 25, 15] establish the task of issue resolution as a de-facto standard for assessing their capability and usefulness. In this setting, an agent is given an entire codebase, a task description (e.g., a bug report or feature request) in natural language and is instructed to produce a code patch that resolves the issue and passes the repository’s test suite. These benchmarks have been instrumental in demonstrating both the substantial potential and the persistent limitations of current models as SWE agents.
Malleable Software in the Age of AI - Geoffrey Litt
Enosis Solutions - Software Development and Testing Services
We design, build, test, modernize, and scale software across the entire product lifecycle, combining deep technical expertise with an AI-accelerated build process.
Full Spec MCP: Hidden Capabilities of the MCP spec — Harald Kirschner, Microsoft/VSCode
Quint (@quint-lang.org)
New podcast with @bugarela.com on @ColorsofWeb3pod talking spec-driven development and how we benefit from precision and executability of specs, especially in the AI era. Why specs can't just be English and markdown↓
LukeW | Common AI Product Issues
At this point, almost every software domain has launched or explored AI features. Despite the wide range of use cases, most of these implementations have been t...
