Agents Machine

Solo Developer Workflow

How to use Agents Machine as a solo developer to build a personal AI memory and automate your workflow.

As a solo developer, you juggle multiple projects, switch contexts constantly, and lose time re-explaining your codebase to AI every session. Agents Machine fixes this by giving your AI persistent memory that grows smarter over time.

Day 1: Set Up Your AI Memory

1. Store Your Architecture

After installing and connecting your IDE, start by teaching the AI about your project:

Store in memory: Our project is a SaaS dashboard built with Next.js 14,
Tailwind CSS, Prisma with PostgreSQL, and deployed on Vercel.
Authentication uses NextAuth with Google OAuth.
Category: architecture, Tags: stack, nextjs, prisma, vercel

2. Store Your Coding Rules

Store in memory: We use functional components only, no classes.
All API routes return { success: boolean, data?: T, error?: string }.
We use zod for all input validation.
Category: coding-rules, Tags: react, api, validation

3. Store Anti-Patterns

Store in memory: Never use any type. Never use inline styles.
Never use console.log in production code — use our logger utility.
Category: anti-patterns, Tags: typescript, style

After these 3 steps, your AI will remember your entire project context in every future session. No more re-explaining.

Week 1: Daily Workflow

Morning: Quick Context Refresh

Query memory for recent architecture decisions and coding rules.

The AI instantly retrieves all your stored context — no re-explaining needed.

During Development: Specialized Agents

Instead of asking one AI to do everything, spawn specialized agents:

Spawn the analyst agent to analyze the impact of adding
real-time notifications to our dashboard.
Spawn the architect agent to design the WebSocket
integration for real-time updates.
Spawn the developer agent to implement the notification
service based on the architect's design.

Code Review: Before Every Commit

Spawn the reviewer agent to review the changes in
src/services/notifications/ for security and performance.

End of Day: Store What You Learned

Store in memory: Implemented WebSocket notifications using Socket.io.
The NotificationService in src/services/notifications/service.ts
handles connection management. Events are typed in src/types/events.ts.
Category: service-context, Tags: websocket, notifications, socket-io

Month 1: Skills & Automation

Create Reusable Skills

After a few weeks, patterns emerge. Turn them into skills:

Create a skill called "pr-checklist" that reviews code against:
1. Our TypeScript coding rules (query memory for coding-rules)
2. Security best practices
3. Performance considerations
4. Test coverage requirements

Now invoke it anytime:

Invoke the pr-checklist skill on the auth middleware changes.

Set Up Pipelines

Automate repetitive workflows:

Create a pipeline called "morning-briefing":
1. Trigger (schedule, cron: "0 9 * * 1-5")
2. Agent (manager) — summarize kanban tasks in progress
3. Memory Search — find recent architecture decisions
4. Transform — combine into a morning brief
5. Output (log)

Pro Tips for Solo Developers

  • Store decisions, not just code — "We chose PostgreSQL over MongoDB because of complex relational queries" is more valuable than storing code snippets
  • Use categories consistentlyarchitecture, coding-rules, anti-patterns, service-context cover 90% of needs
  • Create skills for repeated tasks — If you do it more than 3 times, make it a skill
  • Use the kanban — Even solo, tracking tasks with P0–P3 priorities keeps you focused
  • Review your memory monthly — Clean up outdated decisions, update architecture changes

Before & After

Without Agents MachineWith Agents Machine
Re-explain project every new chatAI remembers everything from day 1
Generic AI suggestionsContext-aware suggestions based on your rules
Manual code review checklistAutomated review with your specific standards
Context lost between sessionsMemory persists forever
One-size-fits-all AISpecialized agents for each task

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