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Match Workflow Weight to Task Size

beginner 5 min 📋 Copy-paste ready
Sources verified Dec 27, 2025
workflowlightweightefficiencydecision-guide

Scenario

Context: You're about to start work on different sized tasks and need to decide how much process to use

Goal: Learn to match workflow weight to task size—avoiding both over-engineering small tasks and under-engineering large ones

Anti-pattern: Using the same heavy documentation process for a 10-line bug fix that you'd use for a multi-day feature

Tools: Any AI coding assistant

Conversation

The Problem

Many AI workflow guides prescribe heavy processes: 'Document in a spec file, clear context, resume with progress notes...'

This is overkill for a quick bug fix. But it's underkill for a multi-day feature.

The answer: Match workflow weight to task size.

The Decision Framework

Task Size Duration Workflow Context Approach
Trivial < 30 min None Inline in prompt
Small 30 min - 2 hr Light Brief context block
Medium 2 hr - 1 day Standard Project rules file
Large Multi-day Full Spec + progress docs

Trivial Tasks (< 30 min)

Examples: Fix typo, add console.log, simple CSS tweak, rename variable

Workflow: None—just prompt and go

👤 You

Fix the typo in src/utils/format.ts line 42—'recieve' should be 'receive'

For trivial tasks, one-liner prompts are fine. No setup needed.

Small Tasks (30 min - 2 hr)

Examples: Bug fix with investigation, add form validation, refactor single function

Workflow: Light—use inline context block

👤 You
Project: E-commerce checkout flow
Issue: Cart total doesn't update when quantity changes
Stack: React 18, Zustand for state
Constraint: Can't change CartItem interface (shared with mobile)

Debug why quantity changes don't update the total. Start in src/store/cartStore.ts

For small tasks, a brief context block provides enough background without creating separate files.

Medium Tasks (2 hr - 1 day)

Examples: New API endpoint, multi-file refactor, add feature to existing component

Workflow: Standard—use project rules file

👤 You

I'm adding user preferences to our API. Context is in .cursorrules and docs/api-patterns.md.

Create a new /users/:id/preferences endpoint following our existing patterns. Start by reading:

  1. src/routes/users.ts (see existing patterns)
  2. .cursorrules (coding standards)
  3. docs/api-patterns.md (API conventions)
For medium tasks, reference existing project context files rather than repeating everything inline.

Large Tasks (Multi-day)

Examples: New feature spanning multiple systems, architectural change, major refactor

Workflow: Full—spec file + progress tracking

👤 You

I'm implementing real-time notifications across our app. This is a multi-day feature.

Read first:

  • docs/notifications-spec.md (full requirements)
  • docs/notifications-progress.md (what's done)
  • .cursorrules (standards)

Continue from where we left off in notifications-progress.md. Update the progress file before ending.

For large tasks, use dedicated spec and progress files. This enables context handoff between sessions.

Key Heuristic

If you won't remember the context tomorrow, write it down.

If you'll forget by tomorrow, you need at least a progress file.
If it spans days, you need a spec.
If it's done in an hour, inline context is fine.

Key Takeaways

  • Match workflow weight to task size—don't over-engineer small tasks
  • Trivial (< 30 min): Just prompt and go, no setup needed
  • Small (30 min - 2 hr): Use inline context blocks in your prompt
  • Medium (2 hr - 1 day): Reference project rules files
  • Large (multi-day): Use spec files + progress tracking
  • Heuristic: If you won't remember context tomorrow, write it down

Try It Yourself

Prompt Template

Before your next task, estimate duration:
- < 30 min → just prompt
- 30 min - 2 hr → add context block
- 2 hr - 1 day → reference rules files
- Multi-day → create spec + progress files

Variations to Try

  • Try upgrading a task mid-stream if it turns out larger than expected
  • Create a reusable context block template for common small-task types
  • Start tracking which task sizes actually need which workflow weight

Sources

Tempered AI Forged Through Practice, Not Hype

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