Chapter 5: Tools and Workflows
People ask me which AI tool is best. Wrong question. The right question is: which tool is best for what?
In this chapter, you'll learn:
- How to divide tools by task type (not by "best overall")
- A research workflow that feeds results into working tools
- The coding workflow with context management
- Which tools combine well and which don't
5.1 Choosing the Right Tool
I use three main AI tools daily:
- Perplexity — roughly 90% of my searches
- Zed + Claude — programming and technical things
- ChatGPT — non-technical things, household, garden
This division isn't random. It developed naturally based on what worked best for me where.
The Specialization Principle
Each tool has strengths. Instead of finding "the best," find what's best for each task type:
| Task Type | Best Tool | Why | |-----------|-----------|-----| | Research, information gathering | Perplexity | Quick summaries with sources, easy to extract key parts | | Programming, technical work | Claude (via Zed) | Better at code, can manage file context, edit prompts mid-work | | Writing, home projects, kids | ChatGPT | Great at conversational tasks, explanation, brainstorming | | Complex analysis | Claude | Handles nuance, longer context, technical depth |
Why Not Just Pick One?
You could use ChatGPT for everything. Or Claude. Many people do.
But you'll hit friction:
- ChatGPT for research means you miss Perplexity's source links and quick summaries
- Claude for home projects works but isn't optimized for conversational Q&A
- Perplexity for coding doesn't have the context management you need
Specialization eliminates friction. Each tool does exactly what it's best at.
What About Alternatives?
GitHub Copilot, Cursor, and similar tools exist. I've tried them. They work differently—more autocomplete-focused or with different context philosophies. The principles in this guide apply regardless of tool. If Cursor works better for you, use Cursor. The context engineering matters more than the specific tool.
5.2 Research Workflow
Most of my research starts with Perplexity. Here's the workflow:
Step 1: Short Question with Context (5-10 seconds)
Don't overthink it. Quick question, relevant constraints.
"Best TypeScript ORM 2024, supports PostgreSQL, active development"
Step 2: Get Summary + Links
Perplexity returns a summary with source links. Scan it.
Step 3: Verify Dates and Primary Sources
Important: Perplexity sometimes:
- Lacks latest data (training cutoff)
- "Invents" sources that don't actually exist
- Gives superficial answers on technical topics
Click through to verify critical claims. If something seems off, check the source.
Step 4: Take Only Relevant Parts
Don't copy the entire response. Extract what matters for your next step:
- Key facts
- Specific recommendations
- Source links you verified
Step 5: Insert as Context into Next Tool
Take your extracted research and feed it into Claude or ChatGPT for the actual work.
"I researched TypeScript ORMs. Best options for PostgreSQL in 2024 are Prisma, Drizzle, and TypeORM. [Paste relevant comparison]. I need to add database layer to my NestJS app. Which would you recommend given [my constraints]?"
Why This Two-Step Process?
Perplexity is excellent at gathering and summarizing. Claude and ChatGPT are excellent at working with that information. Using each for what it's best at produces better results than forcing one tool to do both.
Perplexity Limitations
Know these going in:
- Often lacks latest data — verify dates for anything time-sensitive
- Sometimes invents sources — always click through for important claims
- Superficial on deep technical topics — good for overview, use Claude for depth
Perplexity is a starting point, not an authority.
5.3 Coding Workflow
For technical work, I use Zed + Claude. The combination matters because of how Zed handles context.
Why Zed + Claude?
Zed's advantages:
- Excellent UX for context management
- Can edit prompts during execution (not just send corrections)
- Easy to add/remove files from context
- Claude model is "intelligent"—can find relevant files on its own
This means I can:
- Describe a task
- Let Claude find relevant files
- See it working with correct context
- Edit my prompt mid-work if I realize I forgot something
Typical Coding Session
- Task from Linear/Jira: "Fix: user can't save profile form"
- Give to Claude: Describe issue, attach relevant files (or let Claude find them)
- Claude analyzes: May reveal things I didn't know (e.g., "there are 2 form implementations")
- Edit prompt: Add the new information without sending a correction message
- Get solution: Claude works with complete context from the start
When Claude Fails
Even with good context management, Claude struggles with:
- Files with similar names in different directories — be explicit about which file
- Too much context (more than 3-4 files) — reduce scope, focus on relevant files
- Unknown library versions — specify version if behavior differs between versions
When I see these patterns, I don't fight it. I reduce scope or be more explicit.
Alternative Setups
If you don't use Zed:
- VS Code + Claude extension — works but different context model
- Claude web interface — paste files manually, less seamless
- API directly — maximum control, more setup required
The principles stay the same: good context management, ability to adjust mid-work, file relevance.
5.4 Tool Combinations
Some tools work together. Others don't.
What Works
Perplexity + ChatGPT
- Research via Perplexity (summaries, links)
- Processing and writing via ChatGPT
- Use case: Researching topic for article, then writing it
Perplexity + Claude
- API documentation via Perplexity (quick lookup)
- Implementation via Claude (actual code)
- Use case: Learning new library, then implementing
What Doesn't Make Sense
ChatGPT + Claude together
They solve the same problems differently. Using both for one task:
- Doubles effort
- Creates conflicting approaches
- No clear benefit
Pick one for each task type. Don't mix for the same task.
The Extraction Pattern
The common thread in good combinations: extraction.
- Tool A gathers or creates something
- You extract the relevant parts
- Tool B works with those parts
You're the filter. You decide what transfers between tools. This prevents context bloat and ensures each tool works with focused, relevant information.
5.5 Tool Selection Advice
If you're just starting with AI tools, here's what I've learned:
1. Start with One
Don't subscribe to everything at once. Pick one tool based on your main task type:
- Lots of research? Start with Perplexity
- Mostly coding? Start with Claude or Copilot
- General productivity? Start with ChatGPT
2. Give It a Month
You need time to develop habits. A week isn't enough to find workflow patterns. A month lets you discover what works and what doesn't.
3. Look for Fit
Not every tool suits everyone. If ChatGPT feels awkward after a month of genuine use, try Claude. If Perplexity doesn't match how you research, try traditional search with ChatGPT for synthesis. There's no wrong answer.
4. Don't Pay Immediately
Most tools have free tiers or trials. Use them first. Only pay when you hit limits that actually matter for your work.
5. Specialize
Once you have multiple tools, give each a purpose. "This tool for this, that tool for that." Specialization creates muscle memory. You stop thinking about which tool to use.
5.6 Cost Reality
Here's what I actually pay:
| Tool | Cost | How I Use It | |------|------|--------------| | Perplexity Pro | Free (via Revolut Premium package) | 90% of my searches | | Zed Pro | ~$50-100/month (usage-based) | All technical work | | ChatGPT Plus | $20/month | Non-technical, home, kids | | Total | $70-120/month | |
Is It Worth It?
The ROI is huge. I save hours weekly. Not "I feel more productive" hours—actual measurable time:
- Research that took 45 minutes now takes 10
- Boilerplate code I used to write manually now takes seconds
- Documentation I dreaded now flows quickly
$100/month to save 10+ hours/week? Easy decision.
Your Mileage May Vary
If you code occasionally, you might not need Zed Pro. If you don't research much, free Perplexity might be enough. Start free, pay when you hit real limits.
Chapter Summary
Key Takeaways:
- No single "best" tool—specialize each for different task types
- Research workflow: Perplexity → extract relevant → feed into working tool
- Coding workflow: Claude/Zed with context management, edit prompts mid-work
- Good combinations: Perplexity + ChatGPT, Perplexity + Claude; never ChatGPT + Claude for same task
- Start with one tool, give it a month, find your fit before adding more
Try This: For your next research task, try the two-step flow: Perplexity for initial research and summary, then extract the relevant parts and feed into ChatGPT or Claude for the actual work. Notice how separating "gather" from "work" improves both steps.
Next: Now that you have the tools and techniques, let's see context engineering in action with detailed real-world examples.