Coding Agents: Windsurf, Cursor, Devin & More
5 min read
Eng Manager
Agents can own small, well-scoped tickets. They can't own ambiguous features or cross-team work.
Tech Lead
Use agents for spikes and prototypes. Reserve human review for anything that ships to prod.
Coding Agents: Windsurf, Cursor, Devin & More
TL;DR
- Claude Code (~$20/mo) leads on complex reasoning: 80.9% SWE-bench with Opus 4.6. Cursor ($20 Pro, $200 Ultra) hits 73% first-try debugging. Devin is fully autonomous but ~15% success on complex tasks; ACU costs burn fast.
- Best at: well-defined tasks, bulk refactoring, legacy migration. Devin + Nubank: 12x efficiency, 20x cost savings on 6M+ line migration.
- Treat them as junior contractors. Give clear specs. Review everything. Top agents fail 15–40% of complex tasks.
As of 2026, "AI software engineers" are real. They aren't replacing senior devs, but they are automating the "implementation details" loop that used to consume 60% of a developer's day.
The Landscape: Capabilities & Pricing (Feb 2026)
| Tool | Capabilities | Pricing | Notes |
|---|---|---|---|
| Claude Code | Agentic CLI; 1M context (beta); multi-file refactors; terminal execution; VS Code, JetBrains, web, GitHub Actions | ~$20/mo Pro | 80.9% SWE-bench (Opus 4.6). Best for complex reasoning. "Agent" not "assistant." |
| Cursor | IDE-native; Agent Mode; multi-file edits; 8 parallel agents; @-file refs; codebase context | $20/mo Pro, $200/mo Ultra | 73% first-try debugging. IDE integration is the differentiator. |
| GitHub Copilot Pro+ | Multi-model (Claude, GPT-5.2, Gemini); agent mode; trained on GitHub | $39/mo | 1.8M paying subscribers. Strong value for GitHub-centric teams. |
| Devin | Fully autonomous; planning, coding, debugging, testing, deploy; sandbox; self-healing; legacy migration | ACU-based — $20 starter ≈ 150 ACUs | Simple bug: 5–8 ACUs. Feature: 15–25. Complex: 30+. $20 plan often exhausted in days. Best for bulk refactoring; struggles with ambiguity. |
| Windsurf | Cascade agent; multi-file reasoning; Plan Mode; MCP (Figma, Slack, Stripe); 1M+ users | Free / paid | Claude Opus 4.6, Arena Mode for model comparison (Wave 14, Jan 2026). |
| Antigravity (Google) | Parallel workflows; frontend verification via browser | Free (preview) | Endorsed by Linus Torvalds. |
Devin specifics: Works best for large-scale, repetitive refactoring and legacy migration (COBOL, Fortran, Objective-C → modern). Nubank saw 12x engineering efficiency and 20x cost savings on a 6M+ line migration. Don't use for vague tickets — ACU burn and failure rate spike.
What Agents Can Do
- Implement features from specs — Given a clear ticket ("Add validation for email field on signup form"), they can write code, add tests, and open a PR.
- Fix bugs — Especially when provided with a stack trace or reproduction steps. They can run the code, see the error, and iterate.
- Refactors — "Replace all usages of deprecated API X with Y" — mechanical changes at scale.
- Spikes and prototypes — "Spin up a Next.js app with a Postgres connection and a Todo schema." Done in 3 minutes.
- Boilerplate generation — New service skeleton, CRUD endpoints, basic tests.
What Agents Can't Do (Yet)
- Ambiguous requirements — "Make the onboarding better" → they'll guess. Badly.
- Invisible Context — They don't know that "UserType 2" is deprecated because of a verbal agreement with Sales.
- Architecture Strategy — They'll implement an approach. You must decide which approach.
- Security-Critical Logic — Don't let an agent write auth, crypto, or payment logic without deep human review.
- "Figure out what we need" — They execute. They don't discover.
How to Use Them Effectively
- Write specs that a junior could follow. Clear acceptance criteria. Example inputs/outputs. No "figure it out."
- Scope small. One ticket, one PR. Don't ask for "the whole auth system." Ask for "the login screen."
- Provide context. Use
@mentions (in Cursor/Windsurf) to link relevant files, docs, and conventions. - Review like you're reviewing a contractor. Would you ship this? What's missing?
- Iterate. Agent got it 70% right? Refine the prompt and run again. Or finish the last mile by hand.
When Not to Use an Agent
- Tight deadline + high complexity — You need total control.
- Novel problem — You're still exploring the solution space; the agent will converge too early.
- Tiny change — Faster to do it yourself than to prompt and wait.
- Team alignment — Don't surprise your team with agent-generated PRs that ignore established patterns.
You're given 'Add validation for the signup form.' You implement it. PR gets rejected — they wanted client + server validation, specific error messages, and to match the login flow. Rework.
Click "Clear spec → agent executes" to see the difference →
Quick Check
When should you NOT use an autonomous coding agent like Devin or Cursor Agent?
Do This Next
- Try Claude Code on a multi-file refactor — 200k context means it can see your whole module. Compare to Cursor.
- Write a "agent-ready" ticket for a real backlog item. See how clear you have to be for a machine to execute it.
- If you use Devin — Track ACU consumption on one task. Simple bug fix vs. feature vs. "figure it out" — see where the burn happens.