Deep dive
Best LLM for coding: November 2026 benchmarks, compared
The best LLM for coding as of November 2026, by situation: agents, value, large repos, local hardware. Dated scores and who ran each benchmark.
15 min readCoding agents
Topic
Coding agents
Terminal and editor agents that read your repository, run commands, and open pull requests. How they plan, what they can touch, and how to give them the context they need.
Claude Code, Codex, Cursor, Copilot03 articles05 glossary terms07 platforms
Articles
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All articlesDeep dive
What is an AI agent? The loop in code, and where it fails
What is an AI agent? A tested agent loop in TypeScript, run offline against a scripted model, with traces of runaway loops, tool errors, and token growth.
9 min readAgents and frameworks
Guide
What is an MCP server? Build and test one in TypeScript
What is an MCP server? Build a tested TypeScript one with a confirmed write tool, debug it with MCP Inspector, and apply the spec's security requirements.
12 min readMCP and agent protocols
Glossary
Terms you will meet
- Agent
- An agent is a program that calls a model in a loop, runs the tools the model requests, and feeds the results back until a stop condition ends the loop. The tools and the stop condition set what the agent can do.
- Agent loop
- An agent loop is the code that sends the conversation to a model, runs any tool calls in the response, appends the results, and calls the model again. The loop ends when a response contains no tool calls or a limit is reached.
- Context window
- A context window is the maximum number of tokens a model can handle in one request, usually counting the prompt and the output together. Everything the model has to work with for that request has to fit inside it.
- SWE-bench
- SWE-bench is a benchmark that asks a model or agent to fix real GitHub issues by editing the repository, then runs the project's tests to check the patch. The original set has 2,294 problems from 12 Python repositories.
- Tool callingFunction calling
- Tool calling is a model returning a structured request to run a function you defined, with arguments, instead of plain text. Your code runs the function and sends the result back, which is how an agent loop reaches systems outside the model.
Platforms