LogMark for Developers - Use Cases

The Problem

You're deep in a debugging session when an idea hits - a better approach, a related bug, a refactor opportunity. Opening a note app breaks your mental model. Writing it down on paper means you'll never find it again. So you don't capture it. And it's gone.

The cost isn't just the lost idea. It's the pattern recognition that never happens - the connection between today's bug and last month's architecture decision that could have prevented it.

Why LogMark

LogMark automatically captures which application and window you're in. Your entries include context like 'captured from VS Code - auth.ts' so you can trace back to the exact moment. Git branch detection adds repository context automatically.

Workflows

Morning brain dump

t: review PR by EOD
i: cache invalidation might fix the flaky test
b: still stuck on rate limiting

Block capture during debugging

block: rate limiting fails silently when Redis is down

Decision logging

decision: using SQLite because we need offline support and the dataset is small

Idea capture during code review

+backend i: we could abstract this retry pattern into a decorator

Task extraction from code

+frontend t: refactor this component before the merge #debt

Notation Guide

+backend, +frontend, +infra - Project routing

#performance, #security, #debt - Cross-cutting themes

t:, b:, d:, i: - Quick entry types (task, block, decision, idea)

Example Day

9:00 AM

Morning standup prep. Brain dump everything on your mind.

t: review PR #423 t: update deployment docs i: we should add retry logic to the API client

10:30 AM

Deep in debugging, notice something odd.

+backend b: rate limiting silently fails when Redis connection drops

2:15 PM

Code review triggers an idea.

+backend i: this retry pattern could be a decorator -- DRY across all API calls

4:00 PM

Architecture discussion leads to a decision.

d: using SQLite for local cache -- dataset small, need offline support, team familiar

5:30 PM

End of day. Capture tomorrow's priorities.

t: deploy hotfix tomorrow AM t: follow up on Redis issue

AI Agent Integration

LogMark's MCP server gives your AI coding tools persistent memory. Claude Code or Cursor can query past decisions, create entries during work sessions, and track what they did. Your vault becomes shared context between you and your tools.

Agent: "What did we decide about the caching strategy?"
Vault: "d: using Redis with 5min TTL, falling back to in-memory for offline"

Coming Soon

Linear Integration

Block entries will be able to create Linear issues directly. Capture the frustration in the moment, triage it later.

GitHub Integration

Turn captures into GitHub issues with code context included automatically.