WordCamp Sofia 2026

Events SciSEO Team

Hi, i am Oleg Petrov, co-founder of sciSEO.

If you scanned the QR code at the end of my closing talk at WordCamp Sofia 2026, welcome. Thank you for staying until the very end.

On stage I had about 30 minutes. Here you get everything I mentioned: every tool, every source and every example, with links, plus a few notes I didn't have time to say out loud. Read it in order the first time. After that, use it as a reference.

Get the slides: download the full deck.

One honest note before we start: I'm the co-founder of sciSEO, and I also built DiveWP, one of the plugins below. I'll say so where it matters. Everything else on this page I recommend because it's useful, not because anyone asked me to.

Start with strategy, not with a tool

AI has made building things cheap. That changes where the expensive mistake is. It's no longer building something badly. It's building the wrong thing.

So before any tool, any agent or any prompt, do three things.

1. List your data points

Your store talks to customers all day. It just can't remember. The knowledge is already there, spread over a few places:

  • Orders: who buys what, when and how often

  • Products and reviews: what people praise and what they send back

  • Support tickets: the questions you answer every single week

  • Email and chat: promises, complaints, special deals

  • Social media and marketing: posts, comments and campaigns, and which ones land

  • Knowledge docs: policies, supplier sheets, shipping rules

  • You: everything nobody ever wrote down

Later, two more appear: what your AI agents learn, and what your AI team reports back. Both become data points too.

Most answers your customers need are already in your store. They just live in different places, and nobody connected them.

2. Pick one goal and the number that measures it

A list of data points isn't a strategy yet. It becomes one when you tie it to one thing you want to change, and one number that tells you whether it changed.

Data pointOne goalThe number you watchSupport ticketsFewer repeat questionsTickets per 100 ordersOrdersMore repeat buyers% of customers who order again within 90 daysReviews and returnsFewer returnsReturn rate per product

Data points get more valuable when you combine them. Orders tell you which products sell. Reviews tell you what buyers say about them. Together they tell you what to write in your marketing and on your product pages, in your customers' own words. You measure that with the conversion rate of the products you promote.

Pick one goal. Write down today's number. Everything below is a way to move it.

3. Know which data is personal

Under GDPR, personal data is any information about a person who can be identified (GDPR, Article 4). In a store that means names, emails, phone numbers, addresses, a customer's order history, and every chat and email message. Products, prices, stock, policies and totals that name no one are much lower risk.

You don't need to become a lawyer. You need to know which of your data points are personal, because that decides what you may give to an AI and how. The practical rules are at the end of this article. I'm not a lawyer, so check your own setup with one.

"Technical" isn't what it used to be

Do you need to be a writer to write articles? No. The same is now true for code. You can build tools and small apps without writing code yourself, which means people who understand the business now have the advantage.

A word for the developers reading this: the best developer in 2026 is a translator. AI writes the code. You decide what it's for, and you turn a business need into a working product.

What still needs care is security and data. Building got easy. Keeping it safe didn't.

Three steps from strategy to results

  1. A second brain: your data, organised so an AI can read it

  2. Connectors: your tools plugged in, so the AI sees more and can act on it

  3. AI employees: agents that work for you, on their own

The order matters. Most people jump straight to AI employees because that's the exciting part. It fails, because the agent has nothing true to work from.

Step 1: Build a second brain

Research your tech stack first

The question isn't which tool is famous. It's which tool moves your number. Four ways that work:

  1. Ask an AI. Give it your goal and your data points, and ask it to compare tools for that job, popular and not.

  2. Use "awesome" lists. On GitHub, community-curated lists collect the best tools for one topic. Start from the awesome list of awesome lists.

  3. Look at what others run. BuiltWith and Wappalyzer show which tools a store, or a competitor, uses.

  4. Ask people. The WordPress community and Reddit communities like r/woocommerce and r/ecommerce tell you what owners really use, and what they complain about.

Popular isn't the same as right for you. Your goal decides.

GitHub is the plugin directory for code

Most of you know the WordPress plugin directory. GitHub is the same idea, for code. According to GitHub's Octoverse 2025 report, there are about 395 million public and open-source projects there and more than 180 million developers. Today an AI agent can read a GitHub project for you, explain it and install it. Before you pay someone to build something, check whether it already exists.

Three checks before you use anything:

  • License. MIT or GPL means you may use it. No license means you may not, even if the code is public.

  • Recent updates. Like WordPress's "not tested with the latest versions" warning: abandoned code doesn't get security fixes.

  • Stars and users. A popularity signal, not a safety check.

One big difference from WordPress.org: every new plugin there is reviewed before it's listed. On GitHub, nobody reviews anything before it's published.

Use the agent you already like

There are several good AI agents, and each has its own strengths. None of them locks you in.

  • Claude Code (Anthropic): a good fit if you want it in the terminal, the desktop app or the browser, with skills and connectors.

  • Codex (OpenAI): a good fit if your team already pays for ChatGPT and works there every day.

  • Cursor: a good fit if you work in an editor. Since 12 October 2026 it's bundled with Grok and Grok Bot in the X Subscription. Check which plan includes what before you buy.

  • Antigravity (Google): a good fit if you want to start free with a Google account. In June 2026 Google moved Gemini CLI users over to the Antigravity CLI.

Your rules live in a plain text file: CLAUDE.md for Claude Code, AGENTS.md for Codex and Cursor. Your data and rules stay in your folder, so you can switch agents any time.

What a second brain is, in Andrej Karpathy's words

In April 2026, Andrej Karpathy, a founding member of OpenAI and former Director of AI at Tesla, published a short note called LLM Wiki. This is the line I quoted on stage:

"The human's job is to curate sources, direct the analysis, ask good questions, and think about what it all means. The LLM's job is everything else."

In practice it works in three parts:

  • raw/: your exports. Never edited.

  • wiki/: the AI writes and links the pages. One page per product, topic or customer segment.

  • Answers: when you ask a good question, the good answers are saved back as new pages.

One plain-text file, CLAUDE.md, holds the rules.

A store brain is just a folder

No database, no server. This is what it looks like on disk:

store-brain/├── CLAUDE.md├── raw/│ ├── orders-2026-q3.csv│ ├── tickets-helpdesk.json│ ├── reviews.csv│ └── supplier-sheets/└── wiki/├── products/├── customers/segments.md├── policies/returns.md└── faq.md

  • CLAUDE.md: plain-language rules. Who you are, your tone, what the AI must never do. Write it the way you'd brief a new employee.

  • raw/: drop your exports here: WooCommerce, your help desk, reviews, supplier PDFs. The AI reads them and never changes them.

  • wiki/: the AI writes and links these pages.

To browse it like a website, open the folder in Obsidian, a free notes app. Its graph view draws the links between pages as a map. Follow one product, say a linen shirt, and you'll see it link to its supplier, the size guide, a review that says "runs small", a ticket about a wrong size, the returns policy and a competitor selling the same shirt 10% cheaper. In a spreadsheet those are six tabs. On the map they're one cluster, and the fix is obvious.

Because it's all plain text files, you own it, you can back it up, and you can switch AI tools whenever you want.

Step 2: Connect your tools

A connector plugs one of your tools into the AI. Two things happen: the AI gets more data points, and it can work on them for you. Don't think in tools, think in jobs. Use whichever tool you already have for each job. One per job is enough.

You'll find most of these in Claude's connector directory and in ChatGPT's apps. Some also offer their own official MCP server.

JobExamplesWhat you getYour storeShopify · Wix · WebflowOrders, products, inventory and discountsPayments and accountingStripe · PayPal · Square · QuickBooksSales, payouts, refunds and invoices, without dashboard huntingEmail and CRMKlaviyo · HubSpotCampaign results, contacts, a draft of the next campaignAdsGoogle Ads · Meta Ads · TikTok Ads · Amazon AdsSpend and results in one question (Google Ads is read-only)Analytics and SEOGoogle Analytics · Ahrefs · SemrushWhich products get traffic but no sales, and whyDesignCanva · FigmaOn-brand graphics and product visuals from a chatCustomer supportIntercom · GorgiasWhat customers ask, in their own wordsTeam and projectsNotion · Trello · Asana · JiraUse whichever you already haveFiles and emailGoogle Workspace · Microsoft 365Drive, Gmail and Calendar, or their Microsoft equivalentsAutomationZapier · Make · n8nReach thousands of other apps without codeSite healthDiveWPPerformance, security, database, logs and cron, readable by an AI agent

Full disclosure on DiveWP: I built it. It's a free plugin on WordPress.org that checks performance, security, the database, logs and scheduled tasks. Its 14 abilities let an AI agent read those reports. More at divewp.com.

The simplest setup is one sentence to your agent: "Every night, pull what changed in these tools and file it in store-brain/raw/."

WordPress and WooCommerce with MCP

Exports are a snapshot. For live data you use MCP, the Model Context Protocol. Think of it as a standard plug that lets an agent read and act inside another app.

  • WooCommerce MCP: first shipped as a beta in WooCommerce 10.3 and stable through 10.7, still labelled a developer preview. Agents can list, read, create and update products and orders. It uses your REST API keys and their permissions, so a read-only key means a read-only agent.

  • WordPress MCP Adapter: official, from the WordPress AI team. It turns WordPress abilities into tools an agent can call. The Abilities API has been in core since WordPress 6.9, and the adapter already has 50,000+ active installs.

  • WordPress.com MCP: since 20 March 2026, on all paid plans, Claude, ChatGPT, Cursor and OpenClaw can draft, publish and edit posts and pages and manage comments. It's off by default, and you confirm each change.

  • AI Engine by Meow Apps: one of the most popular AI plugins for WordPress. Its free MCP module edits content, blocks and media.

Step 3: Put AI employees to work

An AI employee is an agent that works when you don't: on its own, inside the chat app you already use, and with memory. A few of them together make your own AI team.

Two kinds of AI employees

Run it yourself (full control, but securing it is your job):

  • OpenClaw: open source, runs on your own machine, and you talk to it in Telegram, WhatsApp or Slack. Around 390,000 GitHub stars as of October 2026.

  • Hermes Agent by Nous Research: open source (MIT), with a built-in scheduler and long-term memory. It writes new skills from experience.

Built into an app you already pay for (convenient, but your logins and data live in their cloud):

  • Grok Bot (xAI, 11 August 2026): works 24/7 on its own cloud computer. Part of the X Subscription.

  • ChatGPT dots (OpenAI, 29 September 2026): always on in ChatGPT, Slack and Teams, for ChatGPT Pro and Business Premium. It asks before it changes anything.

  • Meta Muse (Meta, 8 September 2026): a personal agent in its own secure virtual machine, on macOS, iOS and Android.

OpenClawHermes AgentGrok BotChatGPT dotsMeta MuseMade byOpen sourceNous ResearchxAIOpenAIMetaRuns onYour computer or serverYour PC, a VM or serverlessxAI's cloud computerOpenAI's cloudIts own secure VMTalk to it inTelegram, WhatsApp, SlackTelegram, Slack, WhatsAppDesktop and iOS apps, CursorChatGPT, Slack, TeamsmacOS, iOS, Android appsWorks aloneCron jobs, 30-min heartbeatBuilt-in schedulerAlways on, 24/7Always on, multi-day tasksBackground tasks in its VMCostFree + AI model costsFree (MIT) + model costsPaid X Subscription plansChatGPT Pro, Business PremiumNot announcedWatch outUnvetted skills, weak defaultsSecuring it is your jobYour logins live in its cloudNew since Sept 2026New since Sept 2026

dots and Muse are only weeks old, so re-check every detail before you buy. Point any of these agents at your second brain and they know your store. Point them at nothing and they improvise.

Example 1: a support agent that answers "Where is my order?"

Between 30 and 50% of e-commerce support tickets ask one question: "Where is my order?" In peak season it's 50 to 80%. That's an industry benchmark from ClickPost, a shipping-tracking company, not a peer-reviewed study. The point isn't the exact number. The point is that the answer already exists in two of your data points, the order status and the courier's tracking. Nobody connected them.

Connect an AI employee to your store and your courier, and this happens (a scenario for illustration, not a real store):

  1. At 23:04 a customer asks where order #4821 is.

  2. The agent reads the order in your store and checks the courier's live tracking.

  3. It replies in seconds with the status and the tracking link.

  4. The next morning, when the parcel moves, it writes again on its own.

That last step is what makes it an employee and not a chatbot: nobody asked it to send the second message. Refunds, complaints and anything unusual still go to a person.

Example 2: your own competitor radar

Every Monday, on its own, the agent checks five competitors:

  1. Watches their pages with Firecrawl MCP: prices, new products, promotions. Firecrawl's free plan gives you 1,000 credits a month.

  2. Reads their search data through Semrush's official MCP: keywords, backlinks and traffic, in plain questions. You need a Semrush plan with API units.

  3. Compares it with yours: your sales, reviews and Search Console data are already in the second brain. That's what turns their data into a decision.

Then it writes what changed into your second brain and sends you one suggested action on Telegram. Every finding becomes a new data point. Only use public pages, and respect each site's terms and robots.txt.

Example 3: from your second brain to published articles (how we do it at sciSEO)

This one is ours. sciSEO researches, writes and publishes SEO articles, and it starts from search data, not guesses:

  1. Your data: Google Search Console, with your queries, impressions and average position.

  2. Demand: Google Ads Keyword Planner, with volume, competition and cost per click. It also flags when two articles would compete for the same keyword.

  3. You choose: sciSEO suggests data-backed keywords and headlines, and a person picks. The AI does the heavy work. You decide.

  4. Draft: research, outline and a full first draft in your brand voice, from your site's own context.

  5. Publish: to WordPress, WooCommerce or Shopify, as a draft, live or scheduled.

You can run all of it from the AI chat you already use: sciSEO works inside Claude, ChatGPT, Gemini, Claude Code, Cursor and Codex.

An agent that can act can be tricked

This is the part nobody puts in the demo. An agent that can send emails and change orders can also be tricked into doing it. Three real problems, all reported about OpenClaw:

  • Poisoned skills: Cisco's security team found third-party skills that sent data out without review.

  • Prompt injection: a hidden line in an email, a review or a web page can give the agent new orders.

  • Weak defaults: The Register criticised OpenClaw 2.0 for storing secrets unencrypted with the sandbox off by default.

This doesn't mean "don't use agents". It means treat them like a new employee: small permissions first.

Automate the answers, keep a human in reach

The most famous AI customer service story is Klarna's. In February 2024, Klarna said its AI assistant did the work of 700 agents and handled 2.3 million chats in its first month. In May 2025 Klarna started hiring people again: the CEO said cost had weighed too much, and that customers must always be able to reach a person. At the same time, Gartner forecasts that by 2029 AI agents will solve 80% of common service issues on their own.

Both are true. Aim for the 80%, and design the handoff for the rest.

Seven rules before an agent touches your store

If you remember one part of this article, make it this one.

  1. Read-only first. Add write access one action at a time.

  2. Its own user and keys. Give the agent a separate WordPress user and separate API keys with the fewest rights, so you can switch it off fast without touching anything else.

  3. Know what leaves your folder. Raw data stays with you. Check what goes to the AI.

  4. Sign a DPA. Under GDPR you need a data processing agreement (Article 28) when customer data goes to an AI provider.

  5. A person approves money. Refunds, price changes and outgoing emails.

  6. Only skills you've read. From sources you trust. Read them before installing.

  7. Tell customers it's an AI. The EU AI Act's transparency rule, Article 50, applies since 2 August 2026: if a customer talks to an AI, they must be told, unless it's obvious.

I'm not a lawyer. Check your specific setup with one.

What comes next: your next customer won't visit your store

Their agent will. People already ask an AI to find and compare products for them, and soon to buy for them. If your store doesn't work for those agents, you don't exist for those customers.

Two standards are competing:

A reality check: ChatGPT's Instant Checkout launched in September 2025, and by March 2026 OpenAI was pulling back from it. People used AI to research products, not to buy inside the chat. So don't rebuild your checkout yet. Do the cheap things that help in every scenario: complete product data, a synced Google Merchant Center feed, and a clear decision about which AI crawlers may read your store.

Everything is connected

Here is the whole picture. Your goal sits in the middle. Your data points go into a second brain. Connectors plug in the tools you already use. Your AI team works on all of it and writes what it learns back in as new data points. The system gets better every week, as long as it serves one goal.

The tools will change by next WordCamp. Your data and your second brain will still be yours. So start with the problem, not the tool.

Questions? Write to me at [email protected], or see what we're building at sciseo.com.

- Oleg

The event and the deck

Strategy and data

Research your stack

AI agents and the second brain

Connectors

WordPress and WooCommerce with MCP

AI employees

Examples

Risks and lessons

Agentic commerce

All links and facts checked in October 2026. AI tools change fast, so re-check prices and plans before you buy.