Discover the Best AI Resources
Curated essentials, no noise — just what matters
Lets developers delegate codebase work from terminal, IDE, desktop, web, Slack, or mobile. It reads projects, edits files, runs commands, opens PRs, and asks for permission before changing files or executing commands.
Autonomous coding agent that runs each task in its own cloud sandbox preloaded with your repo — writing features, fixing bugs, running tests, and opening PRs. Reachable from ChatGPT web, a CLI, desktop apps, and IDEs (VS Code, JetBrains, Xcode).
Ranks LLMs by real production token usage, not benchmarks. Aggregates traffic from millions of users hitting 400+ models through one API — sliced by model, lab market share, tool-call frequency, and image volume, updated weekly.
Turns text, images, voice, files, and live context into conversational help across web and mobile. Its edge is tight access to Google Search, Android, Workspace, and multimodal Gemini models; the tradeoff is ecosystem lock-in and uneven reliability.
Interleaves chain-of-thought reasoning with tool-using actions in one LLM loop: the model plans, queries a source like Wikipedia, then revises from results. Cuts hallucination versus reasoning-only prompting and beats trained agents on interactive tasks.
Gives developers direct REST access to Claude models for chat, coding, agents, batch jobs, token counting, and structured outputs. It is best for teams that want Anthropic's newest features without routing through a cloud marketplace.
Treats the interface between an LM agent and a computer as a design variable. A custom agent-computer interface (ACI) with concise file-edit, repo-navigation, and test commands plus compact feedback reaches 12.5% pass@1 on SWE-bench, 87.7% on HumanEvalFix.
A graph-based RAG framework pairing a knowledge graph with vector retrieval and a dual-level (low/high) query mode. New documents merge into the graph via set operations instead of triggering a rebuild, cutting the cost of keeping the index current.