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- I felt dumb about AI agents for way too long
I felt dumb about AI agents for way too long
No code. No API keys. No terminal. Just Claude and 30 minutes.
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Hey
I am going to admit something a little embarrassing.
For the longest time, I had no idea what an AI agent actually was.
I would see people on X posting screenshots. "My agent just researched 40 sources and wrote the whole report while I slept." And I would sit there nodding like I understood, while quietly thinking, what is this person even talking about and why can I not do that.
I assumed agents were for engineers. People who write code. People who know what an API key is and where to put it. I am not that. I am someone building a newsletter and trying to get more done in a day than the day allows.
So I avoided the whole topic. For months.
That was dumb. And I am telling you this because I think a lot of you are exactly where I was. You keep hearing the word "agent" thrown around like everyone got a memo you missed.
You did not miss anything. The truth is almost nobody explains it simply, because the people who understand it are too deep in the technical side to remember what confusion felt like.
So let me be the person who remembers.
By the end of this email you will know what an agent actually is, and you will have built one. No code. No API keys. No terminal. Just Claude, clear instructions, and about 30 minutes.
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What An AI Agent Actually Is (In Plain Words)
Forget every definition you have read. Here is the only one that matters.
An AI agent is Claude doing multiple steps automatically, instead of you doing them one at a time.
Think about how you normally use Claude. You ask it to research something. You read the result. You ask it to write an outline. You check it. You ask it to write the full piece. You edit it. You ask it to format it. You copy it out.
That is four separate tasks. Each one needs you to read, approve, and type the next instruction by hand.
An agent does all four in a row, on its own. You say "research this topic, build an outline, write the full article, and format it for publishing." Claude runs all four steps back to back and hands you the finished result.
That is the entire difference. A normal chatbot does one thing and waits for you. An agent does a sequence of things and delivers a finished output.
Once that clicked for me, I felt silly for being scared of it for so long.
You Do Not Need The Technical Stuff
This is the part that kept me stuck, so I want to kill it early.
You do not need the API. You do not need an Agent SDK. You do not need to write a single line of code.
You can build three kinds of agents using only the tools already sitting inside Claude:
The first is a Chat Agent, built inside Claude Projects. You write a system prompt that defines a full workflow, and every time you give it a task, it runs that whole sequence automatically.
The second is a File Agent, built inside Claude Cowork. It reads a folder on your computer, processes each file, and creates organized outputs from one instruction.
The third is a Scheduled Agent, also in Cowork. It runs on its own on a schedule. It wakes up at 7am, does a job, and saves the result before you even open your laptop.
We are going to build all three. Starting with the easiest.
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Build 1: The Research-To-Article Agent (15 Minutes)
This is a Chat Agent. You give it a topic, it gives you a finished article. One input, one output.
Step 1: Create a new Claude Project. Open Claude. Click Projects. Click "Create Project." Name it "Article Agent."
Step 2: Write the system prompt. This is the brain of the agent. Paste this into the project's system prompt field:
You are an autonomous article production agent. When the user gives you a topic, you execute the following workflow automatically without stopping for approval between steps:
STEP 1 - RESEARCH. Search the web for the latest information on this topic. Find 5 to 7 relevant sources. Extract the key insights, statistics, and expert perspectives.
STEP 2 - ANGLE. Based on your research, identify the most interesting angle. What does the reader already believe about this topic? How can we challenge or expand that belief? Choose the angle that would generate the most engagement.
STEP 3 - OUTLINE. Create a detailed outline: an opening hook that contrasts common belief with reality, 5 to 7 main sections with bold subheadings, specific data points for each section, and a closing CTA.
STEP 4 - WRITE. Write the complete article. 2000 to 3000 words. Short paragraphs, three sentences max. Bold the key insight in every section. Specific numbers over vague claims. Direct, conversational tone. Zero filler.
STEP 5 - REVIEW. Review the article against these criteria: Does every section add new information? Are all claims supported by specific numbers or examples? Would a busy person stop reading anywhere? If yes, fix those sections. Is the opening hook genuinely compelling?
Output the final article with a recommended title at the top. Execute all 5 steps in one response. Do not ask for approval between steps.
Step 3: Test it. Open a new conversation inside your Article Agent project. Type one thing: "AI agents for beginners."
Claude runs all five steps. Research, angle, outline, full draft, quality check. You get a complete, polished article from a three-word input.
That is your first agent. It took 15 minutes to set up, and it replaces two to three hours of manual work every single time you use it.
The first time I watched it run all five steps without me touching anything, I actually laughed out loud. That was the moment the fear disappeared.
Build 2: The File Processing Agent (15 Minutes)
This one is a Cowork Agent. It chews through a whole folder of files for you.
Step 1: Open Claude Desktop and go to the Cowork tab. Grant Cowork access to the folder you want to process.
Step 2: Give it a batch instruction like this:
Go to my Downloads folder. For every PDF file in there: read the document, extract a summary of 5 bullet points max, identify the 3 most important action items, and save a summary file in a Summaries folder using the same filename with a .md extension.
After processing all files, create a master file called "all-summaries.md" that combines everything in one document, sorted by date. Process all files. Do not stop between files.
Claude reads every PDF in the folder. Summarizes each one. Creates individual files. Then builds the master document.
One instruction. Entire folder handled. If you have 20 PDFs sitting there, this just saved you an afternoon of reading and note taking.
Build 3: The Scheduled Morning Agent (15 Minutes)
This is the one that genuinely feels like magic. It runs on its own, every morning, before you wake up.
Step 1: Open Cowork.
Step 2: Type /schedule.
Step 3: Configure the recurring task:
Every weekday at 7:00am: Check my Gmail for emails received since 5pm yesterday. Categorise each one as ACTION REQUIRED, FYI ONLY, or CAN IGNORE. For each ACTION REQUIRED email, draft a suggested response. Check my Google Calendar for today's meetings and note who is attending and the topic. Save everything to a file called "morning-brief-[today's date].md" in my Daily folder.
Set the schedule. Every weekday at 7am.
From now on you wake up to a full daily briefing. Emails sorted. Replies drafted. Calendar laid out. The agent did the work while you were asleep.
How To Make Your Agents Better Over Time
Your first version of any agent will be good. Not perfect. Here is how you sharpen them.
The Correction Rule. Every time an output needs fixing, turn that fix into a rule in the system prompt. "The summaries are too long" becomes "Each summary must be under 100 words." After ten corrections, your agent is dramatically more precise.
The Example Rule. Upload examples of great output into your Project knowledge files. Tell it "match this standard." Agents with examples beat agents with only instructions, every time.
The Feedback Loop. Once a week, review the past 7 days of output. What worked. What needed fixing. Update the instructions. An agent that gets weekly refinement produces far better work after a month than one that never gets touched.
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5 Agents You Can Build This Week
Now that you know the three types, here are five ideas to steal:
One, the Content Repurposer. Feed it one long article, get back an X thread, a LinkedIn post, an Instagram caption, a newsletter teaser, and a YouTube outline. All in one response.
Two, the Weekly Competitor Tracker. Runs weekly, searches your top 3 competitors, finds new launches, pricing changes, and news, then saves a brief.
Three, the Client Onboarding Agent. Give it a client name and project, get back a welcome email, timeline, intake form, and asset request, all customized.
Four, the Meeting Debrief Agent. Feed it your messy meeting notes, get back a clean summary with decisions, action items, owners, and next steps.
Five, the Invoice Processor. A Cowork agent that scans your Receipts folder monthly, extracts the details, and builds a categorized spreadsheet with totals.
My Final Words On This
Here is what I wish someone had told me a year ago.
When you build these three agents, you are not just building three tools. You are learning the actual skill of building agents. And that skill compounds.
Every agent you make teaches you a pattern you can reuse. Your prompts get sharper. Your workflows get tighter. Your output gets better. Within a month you will look at every repetitive task in your life and think "I can agent that." And you will be right.
Because once you understand the pattern, which is define the steps, set the quality standard, automate the sequence, you can agent almost anything.
Most people will keep doing this work by hand while talking about how cool agents sound. The ones who build their first one today will have a small team of them running by the end of the month.
I was on the wrong side of that line for far too long. Do not make my mistake.
Pick Build 1. Do it today. It takes 15 minutes.
Stay curious, talk to you tomorrow.
CoolDeep AI
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