how to actually get started building ai agents (with zero knowledge)

@aashatwt
aasha@aashatwt
114 views Jul 12, 2026 ~3 min read
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if you feel like:

Media image

“everyone is building ai agents and i’m late”

you’re not

most people still don’t even understand what an ai agent is

you’re early

step 1: stop consuming. start building.

don’t fall into this trap:

  • watching 50 youtube videos
  • saving 100 threads
  • building nothing
  • instead:

    build something today

    even if it’s basic

    like:

  • a chatbot
  • a doc q&a bot
  • a simple automation
  • you won’t understand everything

    that’s normal

    you learn by building

    step 2: understand what you’re building (simple)

    an ai agent is just:

    model + tools + instructions

  • model → the brain (claude / openai)
  • tools → what it can use (search, email, database)
  • instructions → what it should do
  • that’s it

    don’t overcomplicate it

    step 3: pick your setup (don’t overthink this)

    you have 2 easy paths:

    option 1: you want something working fast

    use:

  • openclaw → ready-made agent system
  • just plug APIs + tools → done
  • good if you want to see results quickly

    option 2: you want to build your own

    use:

  • vercel ai sdk + next.js → easiest full stack
  • cursor or claude code → to generate code
  • claude / openai → for the model
  • this is best if you want to learn + build real apps

    step 4: give your agent real abilities

    this is where agents become useful

    connect tools (MCPs / skills):

    start with:

  • search (for real-time info)
  • database (store + retrieve data)
  • email (send/receive)
  • payments (advanced use case)
  • step 5: how to actually build (step-by-step)

    here’s the simplest flow:

  • define a simple task
  • example:
    “summarize youtube comments”

  • write a basic prompt
  • tell the agent:

  • what to do
  • how to do it
  • what output you want
  • connect a tool
  • example:

  • fetch comments
  • pass to model
  • run it locally
  • don’t worry about UI

    just make it work

  • improve it
  • add:

  • better prompts
  • memory
  • more tools
  • that’s literally how agents are built

    step 6: build multiple small projects

    don’t try to build something big first

    instead:

  • build small
  • ship fast
  • repeat
  • ideas:

  • chatbot with memory
  • document assistant
  • email automation agent
  • research agent
  • step 7: show your work (this is important)

    post everything you build

    on:

  • linkedin
  • twitter
  • even small projects

    because:

    people don’t care about your code

    they care:

    what it can do for them

    step 8: turn it into money

    once you have 2–3 projects:

  • approach small businesses
  • show what you built
  • explain how it saves time/money
  • example:

    “this agent can save you 10 hours/week”

    that’s what people pay for

    not the tech

    step 9: when things get bigger (important)

    once you build more agents

    you’ll hit problems:

  • too many agents
  • no structure
  • no clarity
  • this is where tools like paperclip help

    they organize agents into a company:

  • roles
  • goals
  • budgets
  • workflows
  • step 10: and when trust becomes important

    if your agents start:

  • handling money
  • making decisions
  • running workflows
  • you need verification

    because:

    you can’t just trust outputs

    this is where eigencompute comes in

    it lets you:

  • verify what agents did
  • prove outputs
  • track every action
  • so your system becomes:

    not just automated

    but trustable.

    free resources :

  • building agents with claude agent SDK : https://docs.anthropic.com/en/docs/agents
  • langraph multi agent workflows :
    https://langchain-ai.github.io/langgraph/

    3. Model Context Protocol (MCP) Documentation :
    https://modelcontextprotocol.io/

    4. n8n: Visual AI Workflow Automation :
    https://docs.n8n.io/
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