Most developers treat Git commits like digital breadcrumbs—quick markers they drop without much thought, assuming they'll remember the context later.
They don't.
Six months down the line, staring at a commit message that reads "fix stuff," they're basically archaeological detectives trying to decode their past self's intentions. The code diff shows what changed, but the why is lost forever.
I learned this lesson the hard way during a production bug hunt at 2 AM. Three developers, two hours, and dozens of cryptic commit messages later, we finally traced a critical issue to a "small fix" from two months ago. The fix itself was one line. Understanding its purpose took longer than rewriting the entire feature.
That's when I started treating my Git commits like entries in a personal journal—and it transformed not just my debugging process, but my entire approach to writing code.
The Journal Entry Mental Model
Think about how you write in a personal journal. You don't just note that you "did stuff today." You capture:
- What happened and why it mattered
- How you felt about the experience
- What you learned from the process
- Context that would help your future self understand
Your Git commits deserve the same treatment.
Instead of:
fix login bug
Write:
fix: prevent double-click submission causing duplicate user sessions
Users were accidentally creating multiple sessions by double-clicking the login
button before the first request completed. Added button state management to
disable submissions while request is pending.
This addresses the surge in "already logged in" support tickets from last week.
Same fix. Completely different information density.
The Three Layers of Commit Storytelling
Every meaningful commit should tell a story with three layers:
Layer 1: The What (Technical Change)
This is the diff—what code actually changed. But don't just repeat what the diff shows. Summarize the change in human terms.
Layer 2: The Why (Business Context)
This is the missing piece in most commits. Why did this change matter? What problem were you solving? What user pain point or business requirement drove this?
Layer 3: The How (Implementation Decision)
When you had multiple approaches, why did you choose this one? What trade-offs did you consider? What alternatives did you reject and why?
Here's how this looks in practice:
refactor: extract user validation logic into UserService class
WHAT: Moved validation logic from UserController into dedicated service class
WHY: Validation was duplicated across 3 controllers and becoming a maintenance nightmare
HOW: Used factory pattern to handle different validation contexts (registration vs profile updates)
This sets us up for easier testing and the upcoming admin user management feature.
The Future Self Test
Before committing, I ask myself: "If I came back to this code in six months, what would I need to know to understand not just what I changed, but why I changed it?"
Sometimes the answer is simple:
docs: add API rate limiting examples to README
New developers keep asking about rate limit handling in our Slack channel.
These examples should reduce support overhead.
Sometimes it requires more context:
perf: implement Redis caching for user preference queries
User dashboard was taking 3+ seconds to load due to N+1 queries on preferences table.
Considered denormalizing the data but caching gives us the perf win without schema changes.
Cache TTL set to 1 hour based on preference update frequency analysis.
Before: avg 3.2s dashboard load
After: avg 0.4s dashboard load
The Debugging Dividend
This journaling approach pays massive dividends during debugging sessions.
When a bug surfaces, I don't just grep through code—I grep through commit messages. Searching for "authentication" or "session" or "validation" in my commit history often surfaces the exact change that introduced an issue, complete with the reasoning behind the implementation.
Even better, the commit message often contains the context I need to determine if the bug is a regression (the code isn't working as intended) or a design flaw (the code is working as intended, but the intention was wrong).
Last month, a colleague was debugging a mysterious caching issue. Instead of diving into the code, we started with:
git log --grep="cache" --oneline
The relevant commit message immediately revealed the problem:
feat: add aggressive caching to product API endpoints
Set cache TTL to 24 hours to reduce database load during flash sales.
Note: This will cause stale data issues if products are updated frequently,
but marketing confirmed product updates only happen during maintenance windows.
The "stale data issue" was happening because marketing's assumptions had changed, but the code was working exactly as designed. Without that commit context, we would have spent hours debugging code that wasn't actually broken.
The Code Review Revolution
Detailed commit messages transform code reviews from syntax checking into actual collaboration.
When I see a PR with commits like:
fix auth issue
update tests
small cleanup
I have to reverse-engineer the entire change from the code diff. It's exhausting and error-prone.
But when I see:
fix: resolve race condition in JWT token refresh logic
Users were occasionally getting 401 errors when their tokens expired
during active sessions. The refresh mechanism wasn't handling concurrent
requests properly, causing some requests to fail with expired tokens.
Added request queuing to ensure only one refresh happens at a time,
with other requests waiting for the refreshed token.
---
test: add integration tests for concurrent token refresh scenarios
Previous unit tests only covered single token refresh. Added tests that
simulate multiple simultaneous API calls during token expiration to
ensure the queuing mechanism works correctly.
---
refactor: extract token management into dedicated TokenManager class
The auth middleware was getting complex with the new refresh logic.
Extracted token operations into a separate class to improve testability
and separation of concerns.
I can review intelligently. I understand not just what changed, but why it changed and how the author thought through the problem. I can suggest better approaches or spot edge cases they might have missed.
The Documentation Side Effect
Here's an unexpected benefit: journaling commits creates living documentation.
When writing feature specs or onboarding new team members, I often start by reading the commit history for a feature. The commits tell the story of how the feature evolved, what challenges were encountered, and why certain decisions were made.
Crompt's Document Summarizer is great for processing large documents, but well-written commits create documentation that doesn't need summarizing—it's already distilled to the essential information.
The Learning Accelerant
Writing detailed commits forces you to understand your own changes more deeply.
When you have to explain why you chose approach A over approach B, you naturally think more critically about your decisions. You catch logical flaws, recognize missing edge cases, and spot opportunities for better solutions.
It's like rubber duck debugging, but for your decision-making process.
I've lost count of how many times writing a commit message made me realize I was solving the wrong problem or taking a suboptimal approach. The act of documentation becomes a quality gate for the code itself.
The Collaboration Multiplier
In team environments, journaling commits becomes a superpower for knowledge sharing.
New team members can read commit history like a tutorial, understanding not just how the codebase works, but how it evolved and why. Senior developers can spot patterns and share context that would otherwise be lost.
When someone leaves the team, their detailed commits preserve their knowledge and decision-making process. The codebase doesn't become a mystery—it remains comprehensible.
The Habit Formation
Like any journaling practice, the key is consistency over perfection.
Start with one repository. Set a personal rule: no commit without a meaningful message. Use a commit template if it helps:
# Title: One line summary (50 chars or less)
# Body: Explain what and why (wrap at 72 chars)
# - What problem does this solve?
# - Why was this approach chosen?
# - Any important context or trade-offs?
# Footer: Issue references, breaking changes, etc.
After a few weeks, the habit becomes automatic. You start thinking in terms of the story you're telling, not just the code you're writing.
The Compound Effect
Six months of journaling commits creates a detailed record of your growth as a developer.
You can see how your problem-solving evolved, what patterns you learned to recognize, and how your understanding of the codebase deepened. It's a professional development log that happens naturally as part of your workflow.
More importantly, you become a better developer because you're forced to think critically about every change. You can't hide behind vague commit messages when you have to explain your reasoning in detail.
The Investment
Yes, writing detailed commit messages takes more time upfront. Maybe an extra 30 seconds per commit.
But that 30 seconds saves hours during debugging sessions, code reviews, and knowledge transfer. It transforms your Git history from a timeline of changes into a knowledge base of decisions.
Your future self will thank you. Your teammates will thank you. And when production breaks at 2 AM, you'll have the context you need to fix it quickly instead of playing archaeological detective with your own code.
The question isn't whether you have time to write detailed commits.
The question is whether you have time not to.
-ROHIT V.
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