Coding Assistants Overview

The Landscape (2026)

Coding assistants have converged on two form factors: terminal-native (CLI agents) and IDE-integrated (editor extensions/forks). The key differentiator is no longer "can it write code?" but "how much autonomy do you give it?"

Comparison

Tool	Form Factor	Model	Autonomy	Open Source	Key Strength
Claude Code	CLI	Claude	High (agentic)	No	MCP + skills + hooks ecosystem
Codex CLI	CLI	GPT	High (agentic)	Yes	Sandboxed execution, open source
Cursor	IDE (VS Code fork)	Multi	Medium-High	No	Codebase indexing, tab completion
Copilot	IDE extension	GPT	Low-Medium	No	Ubiquity, agent mode growing
Windsurf	IDE (fork)	Multi	High	No	Cascade multi-step flow
Aider	CLI	Multi	Medium	Yes	Git-aware, model-agnostic
Continue	IDE extension	Multi	Low-Medium	Yes	Model-agnostic, extensible

The Autonomy Spectrum

Low autonomy                                          High autonomy
├──────────┼──────────┼──────────┼──────────┼──────────┤
Copilot    Continue   Cursor    Aider      Claude Code
(suggest)  (chat)     (edit)    (multi-    (full agent
                                 file)     + tools)

Low autonomy: Suggests completions, you accept/reject line by line. High autonomy: Plans multi-step changes, runs commands, creates files, uses external tools.

What I Use

• Claude Code for everything. MCP servers extend its reach, skills codify my patterns, hooks automate my workflow.
• Ollama + custom scripts for cost-sensitive batch operations (issue screening).
• Previously tried Cursor — good for exploration, but terminal-native agentic flow is more powerful once you learn it.

Key Trends

1. CLI agents are winning for power users. IDE integration still matters for discovery and onboarding.
2. Model-agnostic tools (Aider, Continue) give flexibility but lack deep integration.
3. Autonomy is increasing — the question is shifting from "can it do this?" to "should I let it?"
4. Tool use > code generation — the value is in agents that can read docs, run tests, check CI, not just write code.