Plan First, Then Act: Strategic AI Development Workflow with Mnethos

One of the biggest mistakes developers make with AI coding tools is jumping straight into implementation. After analyzing thousands of successful AI-assisted development sessions, we've learned that the most productive workflow follows a simple pattern: Plan first, then act.

Mnethos makes this workflow smooth with two specialized agents designed to work together.

Meet Your AI Development Team

Architect Agent: Your Strategic Planner

Architect operates in read-only mode, making it perfect for analysis and planning without touching your code:

Analyzes your codebase and identifies potential issues
Creates detailed implementation plans
Explores different solution approaches
Reviews code for security, performance, and architecture concerns

When to use Architect:

Before making significant changes to critical systems
When you need to understand the scope and impact of a task
For architecture planning
When working in unfamiliar codebases

Smith Agent: Your Implementation Partner

Smith has full read-write access and handles the actual implementation:

Modifies files and creates new code
Executes commands and runs tests
Implements the solutions from your plan
Provides real-time feedback as changes are made

When to use Smith:

After reviewing and approving a plan from Architect
For routine tasks you're confident about
When you want hands-off implementation
For quick fixes with proper version control

The Plan-and-Act Workflow

Here's how successful developers use both agents together:

1. Start with Architect for Planning

Switch to Architect from your ZSH shell:

:architect

Ask Architect to create a detailed plan:

: Write a plan for adding rate limiting to our API. Include:
- Which endpoints need protection
- Storage mechanism for rate data
- Error responses and status codes
- Integration points with existing middleware
Now critique this plan. What did you miss?

2. Review and Refine the Plan

Architect will provide a structured plan and then critique it for gaps. Review this carefully - a good plan eliminates most of implementation confusion later.

3. Switch to Smith for Implementation

Switch back to Smith:

:smith

Reference the plan and start implementation:

: Following the $(@rate-limiting-plan.md) we discussed, implement the Redis-based rate limiter for the /api/auth endpoints first in $(@src/auth).

4. Iterate as Needed

Switch back to Architect if you encounter complex decisions, then return to Smith for continued implementation.

Why This Works

Planning prevents confusion: When AI understands the full scope upfront, it makes better implementation decisions and avoids getting lost halfway through.

Separation of concerns: Architect focuses purely on analysis without the pressure to implement, leading to better strategic thinking.

Safety first: Critical systems get proper review before any changes are made.

Faster iteration: Once you have a solid plan, Smith can implement quickly without constant back-and-forth.

Quick Tips for Success

Be specific in your planning requests - include edge cases, error handling, and integration points
Commit frequently - clean git state makes it easier to track AI changes
Review everything - treat AI output like a junior developer's code
Avoid frequent agent switching - it causes context thrashing, hurts cache performance, and creates confusing context handoffs

Remember: You're the lead, architect is your strategic advisor, and smith is your implementation partner. Use each for what they do best.