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, vercel2. 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, validation3. 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, styleAfter 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-ioMonth 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 requirementsNow 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 consistently —
architecture,coding-rules,anti-patterns,service-contextcover 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 Machine | With Agents Machine |
|---|---|
| Re-explain project every new chat | AI remembers everything from day 1 |
| Generic AI suggestions | Context-aware suggestions based on your rules |
| Manual code review checklist | Automated review with your specific standards |
| Context lost between sessions | Memory persists forever |
| One-size-fits-all AI | Specialized agents for each task |