Directory
AI coding and development covers assistants, code review tools, and machine learning projects aimed at developers. The topic mixes code completion services, agent frameworks, prompt and context templates, dataset tools, and research notebooks. They sit at different points in the workflow, so compare where each one fits: writing code, reviewing a change, or setting up a model to run yourself. Check the language and editor support, how the tool handles your code and where it sends it, and the licence attached to any generated output. Some entries are production products and others are experiments that may not run without setup.
ChatWithCloud is an AWS natural language CLI that lets users ask questions about their AWS account in plain English from the terminal. It turns questions into AWS API calls against the account, covering cost analysis, IAM audits and troubleshooting, and it can make infrastructure changes. The first 15 runs are free.
Claude Code is Anthropic's agentic coding tool for developers. It understands a codebase, edits files and runs commands. It is available as a terminal, IDE, Slack or web tool for macOS, Linux and Windows. Projects group related coding sessions so multiple Claude agents can run at once, and auto mode runs by default on Pro, Max and Team plans.
Claude Engineer is an interactive command-line interface that uses Anthropic's Claude-3.5-Sonnet model to assist with software development tasks. The framework lets Claude generate and manage its own tools, expanding its capabilities through conversation. It is available both as a CLI and a modern web interface.
Cleanlab supports software development with code generation, analysis, debugging, or documentation.
A Hugging Face Space by livecodebench that presents a collection of coding questions and shows how different AI models perform on each. Selecting a problem displays each model's generated code, its pass/fail rate and a color-coded correctness score.
Code generation with 🤗 is a Hugging Face Space developed by codeparrot. It allows users to generate code snippets by providing a prompt, with options to select from multiple code generation models and adjust settings such as temperature and token length.
CodeAlmanac is a GitHub repository maintained by AlmanacCode. It is a codebase wiki for AI coding agents, designed to capture information including decisions, flows, invariants, and gotchas that are not explicitly stated in code.
CodeGeeX is an open multilingual code generation model with 13 billion parameters, pre-trained on a code corpus of more than 20 programming languages. It supports multilingual code generation, crosslingual code translation and a VS Code extension, and the repository also releases the HumanEval-X benchmark.
CodeGen is an open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.
Manage fleets of local and cloud agents from one surface. Plan, delegate, review, and ship without leaving your editor.
Transform ideas into fully functional WordPress projects with Telex.
ctop is a GitHub repository maintained by aakashadesara. It is an interactive process viewer for AI coding agents, with documentation covering its features, installation process, keyboard shortcuts, and pinned sessions.
Cursor is a coding agent for building software. It can be used to understand a codebase, plan and build features, fix bugs and review changes. Cloud agents run in isolated VMs for parallel work, and it integrates with tools including GitHub, GitLab, Slack and Linear.
Free 3-month individual subscription to learn data science and AI skills.
DataPup is an open-source, AI-assisted, cross-platform database client built with Electron and powered by LangChain for AI assistance. It currently supports ClickHouse and PostgreSQL, with MySQL and SQLite listed as coming soon. It is released under the MIT license.
DB GPT is an open-source agentic AI data assistant developed by eosphoros-ai and hosted on GitHub, designed for use in next-generation AI and data products. It offers capabilities including agentic data analysis and autonomous SQL and code execution.
Supports software work with AI-assisted coding, testing or application development.
DeepSeek Coder is a series of open code language models trained from scratch on 2T tokens, composed of 87% code and 13% natural language in English and Chinese. Models are offered in 1B, 5.7B, 6.7B and 33B sizes, pre-trained on project-level code corpora with a 16K window size and a fill-in-the-blank task for completion and infilling.
Deployed in few seconds via e2b supports software development with code generation, analysis, debugging, or documentation.
Devin is an AI coding agent and software engineer that helps developers build better software faster. It runs in the cloud or on a machine, tests in its own browser, and works from problem to merged pull request. Plans include Free, Pro, Max, Teams, and Enterprise.
DigitalOcean describes an AI-native cloud platform with a unified stack for agents, inference and cloud infrastructure. Products listed include Managed Agents, Learning Services, Data Services, an Inference Engine with over 75 models, and core cloud services such as Droplets, Kubernetes and App Platform. Harness Runtime is listed starting at $0.0535/hr for durable cloud sandboxes for AI coding agents.
This is the documentation for Ellipsis, a platform that enables running internal agents in the cloud via Claude Code or Codex, with support for custom tools, secrets, and MCP servers. Users define agents as YAML configuration files in their repositories, and Ellipsis executes the agents to build features, fix bugs, and investigate production issues. The platform also includes integrations with GitHub, Slack, Linear, and Sentry, plus support for sessions, environments, secrets, permissions, and usage budgets.
Dorothy is a free and open source desktop app for orchestrating Claude Code, Codex, Gemini, Grok and local agents. It runs multiple agents simultaneously, each in an isolated PTY terminal session, and includes a Super Agent that delegates tasks to other agents via MCP tools, plus Kanban task management and scheduled tasks.
An article presenting initial impressions of DSPy, a framework developed by the Stanford NLP group for algorithmically optimizing language model prompts. The author describes DSPy as closing the loop of prompt engineering by turning a manual process into a structured machine learning workflow. The piece notes it is not a substitute for the official documentation and covers topics such as teleprompter, optimization, compile, bootstrapping and metric functions.
