How I Build My AI Agents 🚀

Every agent I run on my businesses is built the exact same way: Context, Connections, Workflows, Memory . Here’s the full structure with real examples from the.

AEO SUMMARY Quick Overview & Execution Blueprint

An Agent Is Not a Chatbot

A chatbot waits for a question and answers based on what it’s been trained on. An agent has a job. It has permanent context, connected data, repeatable processes, and memory that compounds. The difference shows up the first time you ask a chatbot a question that requires knowing your business and it gives you a generic answer that’s already in your last 50 LinkedIn ads.

My team of agents (a Meta media buyer, a Google Ads buyer, a Klaviyo strategist, a creative director, and a co-founder) all live in Claude Code. Each one is built with the same 4 parts. Once you see the structure, you can’t un-see it — and you can build your own.

SECTION

Context

Context is the set of files that teach the agent who you are, what your business sells, what matters, what benchmarks to use, and how decisions should be made. It’s not a one-line prompt. It’s a full reading list the agent goes through every time you work together.

IN MINE The 4 context files I give every agent

STEP 1Identity File

STEP 2Business Profile

STEP 3Benchmarks & Rules

STEP 4Decision Memory

— key calls we’ve made before and why. So when we revisit a similar situation, the agent already knows the precedent.

THE MISTAKE MOST PEOPLE MAKE

They write one giant prompt and call it a system. Context lives in files the agent re-reads every session — not a single message that scrolls out of view after a few exchanges. If the agent has to be reminded of your business every time, you don’t have an agent. You have a chatbot.

SETUP

Connections

Connections are the live data feeds the agent pulls from. APIs, exports, scrapers, MCP connectors — whatever it takes to get the agent past “based on training data” and into “based on what your account is doing right now.”

IN MINE What my agents are plugged into

Store data: Shopify (revenue, orders, AOV by SKU, inventory).

Email: Klaviyo (revenue per recipient, flow performance, list growth).

Ads: Meta Ads (now via Claude’s native connector), Google Ads, plus Apify for scraping competitor ad libraries.

Customer voice: support tickets, reviews, Reddit and Twitter scrapes for category sentiment.

Industry signals: a curated list of expert accounts on X / Twitter that the agent scrapes weekly so I never miss an algorithm shift or a tactic worth testing.

WHY THIS IS THE HARDEST PART

Most non-developers stop here because connections feel scary. They’re not. Most platforms have free or low-cost APIs, and Claude Code can write the integration code for you. The first agent I built took a weekend; every one after that took a few hours because the patterns repeat.

WORKFLOW

Workflows

Workflows are the agent’s repeatable processes. The exact reports it builds. The exact audits it runs. The exact decision trees it walks through when something looks off.

DAILY Morning brief

Every agent has a morning routine. Pull yesterday’s data. Compare to the trailing 7 and 30 days. Flag anything outside expected ranges. Surface the top 3 actions with the reason for each. Done in one structured output.

WEEKLY Account audit + creative brief

Once a week the agent runs a full account audit (winners ready to scale, losers ready to kill, frequency creep, conversion drift) and turns it into a brief my team can shoot from — specific hooks, specific angles, specific test hypotheses.

MONTHLY Strategy review

A bigger pull-back: budget allocation across channels, what worked vs. what underperformed, what to test next month. The kind of work that used to require a strategist or an agency.

WORKFLOWS = REPEATABILITY

A workflow isn’t just “a prompt I send sometimes.” It’s a written-down, named process the agent runs the same way every time. That’s what turns AI from a tool you reach for into a teammate you can trust to deliver on a schedule.

SECTION

Memory

Memory is the part that makes the agent compound. Without it, every session starts from zero. With it, every session builds on the last one.

WHAT GETS SAVED Decisions, outcomes, patterns, and feedback

Decisions: “On May 3, we killed the gym creative because frequency was 8.2 and CPA was 3.1x target.” The agent remembers, so when we see similar conditions, it doesn’t need to be re-walked through the logic.

Outcomes: “The static testimonial creative we tested in April hit 4.8 ROAS for 14 days, then dropped.” Pattern recognition for the next test cycle.

Feedback: when I push back on an agent’s recommendation, that pushback gets saved with the reason. Next time, the agent reasons differently. The behavior compounds.

WHY THIS IS THE DIFFERENTIATOR

Most AI tools you’ve used forget you the second the chat closes. An agent with memory gets smarter every week because every session deposits something. After a few months, you’re working with something that knows your business better than most contractors you’ve hired.

SECTION

Claude Code + OpenClaw

All four parts get built inside Claude Code. That’s where the agent’s brain lives — the context files, the connection scripts, the workflow prompts, the memory directory. You can run an agent fully manually from there: open Claude Code, ask the agent to run its morning brief, get the output.

OpenClaw is the optional second layer. Once an agent works manually, OpenClaw lets it run on a schedule and report back to me automatically — usually through Telegram. So instead of me asking the media buyer to run the morning brief, the brief shows up at 7am every day. Same agent, same workflows, just on autopilot.

YOU DON’T NEED BOTH DAY ONE

Build the agent in Claude Code first. Run it manually for a week or two so you trust the outputs. Then, if it’s saving you real time, plug it into OpenClaw to run on a schedule. Don’t automate something you don’t trust yet — that’s how agents drift.

SECTION

The Agents Already on My Roster

For reference — here’s the full team I’ve already built using this exact 4-part structure:

Meta Media Buyer

Watches my account daily. Flags ads to kill, ads to scale, and creative ready to refresh.

Google Ads Buyer

Audits intent, protects Brand Search, and finds wasted spend in non-brand campaigns.

Klaviyo Strategist

Reviews flows, subject lines, segments, deliverability. Finds revenue we’re leaving on the table.

Creative Director

Pulls top vs. bottom creatives, mines customer language, builds production-ready briefs.

Co-Founder Agent

My strategic partner. Knows our businesses deeply, pushes back on weak ideas, keeps me focused.

+ Whatever’s Next

Same 4-part recipe. Whatever role I keep manually doing, it becomes the next agent on the team.

THE REAL WIN

An agent isn’t magic and it doesn’t run your business alone. What it does is take the analysis and decision-prep work that used to require an analyst, an agency, or a strategist — and make it happen on a schedule, with your business context, every single day. That’s the leverage. Once you have one agent doing it, you’ll never go back.

GTM & POSITIONING NOTE Somya's Strategic Takeaway

In outbound marketing and career positioning, generic applications have near-zero conversion. Treat yourself as a high-ticket solution: identify the company's pressing operational pain points, build a mini-audit or work sample using AI before you apply, and bypass crowded channels by reaching out directly to the decision-maker with structured value.

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