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Anyone can build AI agents from scratch.
Use this 10-step roadmap to go from idea to evaluation:
[ bookmark 🔖 this post for later ]
Step 1: Set the Agent’s Purpose and Result
• What will the agent do?
• Who will it support?
• What kind of output should it create?
→ Example: A content research agent that reviews articles and summarizes key points.
Step 2: Build Structured Input and Output
• Use Pydantic AI or JSON Schemas for inputs and outputs.
• Keep the format clean and API-like.
→ Tools: LangChain Output Parsers, Pydantic AI
Step 3: Shape and Tune the Agent’s Behavior
• Start with a clear role-based system prompt.
• Use Prefix Tuning or Prompt Tuning for consistent behavior.
→ Tools: Claude, GPT, Prompt Tuning
Step 4: Add Reasoning and Tool Access
• Use ReAct or Chain-of-Thought for reasoning steps.
• Enable tools like search, code, or document lookup.
→ Tools: OpenAI Tools, LangChain, ReAct Framework
Step 5: Organize Multi-Agent Roles (If Needed)
• Use orchestration frameworks to define each agent’s job.
• Create Planner, Researcher, and Writer agents with their own schemas.
→ Tools: LangGraph, CrewAI, OpenAI Swarm
Step 6: Add Memory and Extended Context (RAG)
• Decide if the agent needs context from earlier work.
• Use summary, conversational, or vector memory.
→ Tools: Chroma, Zep, LangChain Memory
Step 7: Add Speech or Vision Features (Optional)
• Use tools like Coqui or ElevenLabs for speech.
• Use vision models (GPT/LLaMA) for interpreting images.
→ This allows the agent to see and speak.
Step 8: Format and Deliver the Output
• Export results as Markdown, PDF, or JSON.
• Keep the output clean and predictable.
→ Tools: Pydantic AI, LangChain Output Parsers
Step 9: Embed in a UI or API Layer (Optional)
• Create a small UI or let the agent run through an API.
• Use Streamlit, Gradio, or FastAPI to make it accessible.
→ This turns the agent into a real product.
Step 10: Test, Review, and Improve
• Run test prompts to measure reliability.
• Use logs and benchmarks to improve performance.
→ Tools: Custom dashboards, MCP Logs, OpenAI Evaluation API
Building AI agents starts with structure, not code.
Get the sequence right to build AI agents quickly.
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You can earn $17,540/month with a faceless YouTube channel, if you have:
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There are 3 ways you can use AI in your workflows.
Non-Agentic (prompts), AI Agents and Agentic AI.
Each works differently and has specific use cases.
Here are the pros, cons and guidelines for using each.
[ bookmark 🔖 this post for later ]
💻 Non-Agentic AI
↳ Simple prompt-response AI with no memory or reasoning.
🛠️ How it works:
↳ User enters one prompt, system replies in isolation
↳ Output generated instantly without refinement
↳ Interaction ends with no context retained
🟢 Pros:
↳ Fast, cheap, and widely accessible
↳ No technical setup required
↳ Ideal for one-off, simple tasks
🛑 Cons:
↳ No reasoning or memory
↳ Quality depends on prompts
↳ Weak for multi-step work
📈 How to start using:
↳ Open ChatGPT, Claude, or Gemini
↳ Write clear, specific prompts
↳ Copy, edit, and reuse output
🤖 AI Agent
↳ Single-task AI worker built to automate one job.
🛠️ How it works:
↳ User defines one clear role (e.g., update CRM)
↳ Agent pulls inputs and uses integrated tools
↳ Executes and outputs without supervision
🟢 Pros:
↳ Automates repetitive tasks
↳ Specialized and very capable
↳ Easy to refine within roles
🛑 Cons:
↳ Limited scope, rigid use
↳ Breaks if inputs are unclear
↳ Needs coordination to work with other agents
📈 How to start using:
↳ Select one repetitive task
↳ Connect LLM via Zapier, LangChain, or API
↳ Link inputs/outputs and test
🚀 Agentic AI
↳ Self-managing AI that plans, executes, and improves.
🛠️ How it works:
↳ Goal broken into smaller sub-tasks
↳ Connects to tools, APIs, and data sources
↳ Refines results with memory and feedback
🟢 Pros:
↳ Handles complex, multi-step projects
↳ Integrates with tools and databases
↳ Produces consistent outcomes
🛑 Cons:
↳ Slower and more expensive
↳ More complex and resource-intensive
↳ Difficult to configure, needs regular maintenance
📈 How to start using:
↳ Use LangChain, CrewAI, or AutoGen
↳ Assign roles (Planner, Executor, Critic)
↳ Add memory and feedback loops
In short:
Non-Agentic AI = prompts
AI Agents = Automate one task
Agentic AI = Run complex workflows
Start with prompts. Then try AI Agents or Agentic AI.
Use all three to get the most out of AI.
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ChatGPT is making us lazy thinkers.
We depend on replies instead of reasoning.
Here are 12 prompts that turn ChatGPT into your thinking coach (copy & paste to use):
(🔖 bookmark this thread for later)
Stop using AI to get simple answers.
Start using it to challenge how you think.
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Credit: Manoj Desai on Medium
My AI side hustle makes me $4,921/week.
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ChatGPT’s Deep Research mode is a goldmine. It turns basic questions into expert insights.
With Deep Research, ChatGPT can think, compare, and analyze market trends in minutes.
Here are 10 powerful use-cases (prompts included ⬇️).
[ 🔖 bookmark this thread for later ]
You can earn $25,000 per month if you have:
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AI is replacing people without the right skills.
Build AI skills to future-proof your career.
Knowing AI tools isn’t enough. It’s critical to learn the right AI skills.
These 9 skills outline how professionals work with AI, from basic interaction to system-level execution.
Building a few of them will expand your career options and opportunities.
Here’s the full breakdown of each skill:
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1️⃣ Prompt Engineering
Write clear instructions that produce consistent, useful AI results.
Most people type one prompt and fix the output later. Professionals structured prompts that deliver repeatable outcomes across tools and tasks.
Tools: Claude, ChatGPT
2️⃣ Workflow Automation
Link platforms together to let AI handle your repetitive work.
This is how teams eliminate manual handoffs and turn routine processes into background systems.
Tools: n8n, Zapier
3️⃣ AI Image Generation
Produce professional-grade visuals for ads and products via text.
Instead of waiting on designers or stock assets, teams generate visuals on demand and iterate instantly.
Tools: NanoBanana (Gemini), Recraft
4️⃣ Vibe Coding
Ship working prototypes rapidly without deep manual code knowledge.
The technical wall is gone; founders are now launching functional products by describing their ideas instead of hiring expensive developers.
Tools: Lovable, Replit
5️⃣ Custom GPTs
Create tailored AI assistants for specific tasks without code.
This turns AI from a general tool into a system that understands your workflows, tone, and use cases.
Tools: OpenAI GPT Builder, Poe
6️⃣ AI Video Generation
Turn concepts into cinematic video content without editing expertise.
Scale video marketing and training at lower costs by generating polished scenes from text scripts.
Tools: Synthesia, Runway
7️⃣ AI-Assisted Development
Write and debug code faster using real-time AI guidance.
Developers focus on logic and architecture while AI handles syntax, errors, and refactoring.
Tools: Cursor, Google Antigravity
8️⃣ Agentic Coding
Assign full coding tasks to AI agents that strategize and execute.
Instead of guiding every step, you define goals and let agents plan and complete the work.
Tools: OpenAI Codex, Claude Code
9️⃣ RAG Systems
Link AI to your internal data for relevant, business-specific responses.
This replaces generic outputs with answers grounded in your documents, systems, and knowledge base.
Tools: LangChain, Haystack
AI tools aren’t enough. It’s critical to build AI skills.
Use this roadmap to:
➟ Identify which AI skills support your role or team
➟ Start with one skill and apply it in real work
➟ Expand only after you see results
That’s how AI becomes a long-term asset, not a distraction.
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AI skills will be crucial for years to come.
Knowing how to use ChatGPT isn’t enough.
Learn these AI skills to future-proof your career:
(remember to 🔖 bookmark for later)
1. Prompt Engineering:
Write better instructions to help AI tools give you exactly what you need.
2. AI Workflow Automation:
Link different apps together to help you complete tasks automatically.
3. AI Agents:
Use AI systems that act like teammates to handle tasks together.
4. Retrieval Augmented Generation (RAG):
Link AI chatbots to your private files for more accurate answers.
5. Multimodal AI:
Use AI that understands pictures, sounds, and text all at once.
6. Fine-Tuning and AI Assistants:
Build custom AI models or assistants tailored to your needs.
7. Voice AI and Avatars:
Make realistic AI voices and avatars for videos and presentations.
8. AI Tool Stacking:
Use tools like Notion, Zapier, and ChatGPT together to work faster.
9. AI Video Content Generation:
Turn your ideas or blog posts into professional videos using AI.
10. SaaS Development:
Build small AI-powered apps using no-code tools.
11. LLM Management:
Keep track of how well your AI tools are working and their costs.
12. Stay Updated:
Follow top AI news sites to keep up with trends and new tools.
AI won’t replace you.
But someone with AI skills might.
📌 Learn 30 free AI tools in 30 days: https://t.co/7MJCwAPtaQ
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RIP McKinsey. Here are 10 prompts to replace expensive business consultants:
[ 🔖 bookmark this post for later ]
➤ SWOT Analysis
Act as a business strategist. Generate a SWOT analysis for [INSERT BUSINESS] in the [INSERT INDUSTRY], using competitive market data and internal insights.
➤ Growth Levers
Find out 5 scalable growth levers for a [TYPE OF BUSINESS], focusing on revenue expansion, operational efficiency, and brand reach.
➤ 30-60-90 Plan
Create a 30-60-90 day action plan for a new [INSERT ROLE] at [COMPANY], including onboarding objectives, performance metrics, and quick wins.
➤ Revenue Model Projection
Develop a lean revenue model for a business providing [PRODUCT/SERVICE], covering optimal pricing, CAC, LTV, and monthly recurring revenue forecasts.
➤ Churn Reduction
Suggest 3 data-driven strategies to minimize churn for a SaaS product targeting [TARGET CUSTOMER], leveraging user behavior data and feedback loops.
➤ KPI Dashboard Framework
Outline the 7 critical KPIs for a [BUSINESS TYPE] to monitor across customer acquisition, retention, product engagement, and financial performance.
➤ Pricing Strategy
Act as a pricing advisor. Propose 3 pricing approaches for [OFFER] aimed at [SEGMENT], utilizing value-based pricing, tier structures, and market positioning.
➤ Go-to-Market Plan
Design a go-to-market plan for introducing [PRODUCT] to [TARGET MARKET], addressing positioning, distribution channels, customer acquisition, and success metrics.
➤ Value Proposition
Draft a persuasive value proposition for [BRAND or PRODUCT] that addresses customer challenges, presents the solution, and emphasizes unique advantages.
➤ Pivot Directions
Recommend 3 strategic pivot options for a startup facing [SPECIFIC PROBLEM], including alternative customer segments, applications, or product approaches.
→ Use these prompts to think, plan, and execute like a top business advisor.
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ChatGPT is a free employee. You can easily earn $9000/month using it.
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