![\"\"](\"https:\/\/starosta-agency.com\/wp-content\/uploads\/2026\/03\/web_dev_blog-3-3-1024x576.png\")
<\/figure>\n\n\n\nWhy it matters right now<\/h2>\n\n\n\n
It matters because LLMs have reached a point where they can reliably produce correct boilerplate, CRUD modules, tests, and documentation, cutting “time to first prototype” several times over. The developer’s focus shifts from typing lines of code to product logic, architecture, security, and integrations.<\/p>\n\n\n\n
How vibe coding works: the cycle, step by step<\/h2>\n\n\n\n
The essence of the cycle is that you set the direction (the “vibe”), the AI generates artifacts, and you validate and narrow things down to the result you actually need.<\/p>\n\n\n\n
Step 1. Frame the task as a prompt<\/h3>\n\n\n\n
You start with a short, specific prompt: what’s needed, why, in which environment, and under what constraints.<\/p>\n\n\n\n
Example prompt:<\/strong><\/p>\n\n\n\n “Build a REST API for managing orders with Flask + SQLAlchemy. Fields: id, user_id, total, status. Add JWT auth, pagination, a Swagger spec, a Dockerfile. Explain the deployment steps on Ubuntu.”<\/p>\n<\/blockquote>\n\n\n\n The model generates files, modules, tests, and a README. You immediately get a working “skeleton” of the solution.<\/p>\n\n\n\n You run the project, write unit tests, and ask the AI: “optimize this,” “rewrite it for FastAPI,” “add a Redis cache,” “move the config into .env.”<\/p>\n\n\n\n The AI prepares a docker-compose file, CI\/CD instructions, and baseline security policies; you approve them, measure metrics (performance, test coverage), and run a retro on the prompts you used.<\/p>\n\n\n\n To get consistent quality, a basic understanding of how the model “thinks” is enough.<\/p>\n\n\n\n Modern LLMs are transformers that operate on a context window: everything you pass in the prompt (requirements, code snippets, errors) becomes the model’s “field of view.” Curate the context carefully and include only what’s relevant.<\/p>\n\n\n\n Models trained on code hold syntax and patterns more reliably. Combine them with tooling: static analysis, formatters (Black\/Prettier), linters, API schema generators.<\/p>\n\n\n\n Retrieval-augmented generation (RAG) lets you feed the model your private documentation: style guides, architecture decisions, API contracts. This reduces hallucinations and improves fit with your stack.<\/p>\n\n\n\n A well-formed prompt saves hours of rework and review.<\/p>\n\n\n\n Quality doesn’t come from generation itself \u2014 it comes from your control perimeter around it.<\/p>\n\n\n\n Require the AI to handle: input validation, parameterized SQL queries, correct CORS\/CSRF, secret encryption, and least-privilege access.<\/p>\n\n\n\n A team process removes chaos and adds repeatability.<\/p>\n\n\n\n Feature branches, mandatory PRs, automated linting, tests, security scans. An “AI PR” goes through the same gates as a human one.<\/p>\n\n\n\n The biggest ROI is on boilerplate and routine work.<\/p>\n\n\n\n Critical security modules, cryptography, complex financial algorithms, and high-load parts with non-trivial optimizations all need human design and thorough review.<\/p>\n\n\n\n Example WP-CLI command (LLM-generated skeleton):<\/strong><\/p>\n\n\n\n Will vibe coding replace developers?<\/strong> No; it changes the role: from typing code to design, review, security, and integrations. Vibe coding<\/strong> is a new level of abstraction in development: the AI writes the code<\/strong>, and the engineer sets the direction and guarantees quality. With a well-organized process, you cut the time to prototype, raise test coverage, and free up the team’s time for architecture, security, and product work. For a business, that means faster releases and lower TCO; for developers, it’s a shift from “coder” to architect and technical lead.<\/p>\n","protected":false},"excerpt":{"rendered":" A practical guide to vibe coding: how developers pair with LLMs to generate code, tests, and docs, and where human review still matters most.<\/p>\n","protected":false},"author":1,"featured_media":2399,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[28,29],"tags":[],"class_list":["post-3429","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-newinit","category-webdevcategory"],"acf":[],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n
Step 2. Code generation (LLM programming)<\/h3>\n\n\n\n
Step 3. Validation and refinement<\/h3>\n\n\n\n
Step 4. Integration, deployment, retro<\/h3>\n\n\n\n
LLM architecture: what a developer should know<\/h2>\n\n\n\n
Transformers and context<\/h3>\n\n\n\n
Code-oriented models and tooling<\/h3>\n\n\n\n
RAG and “context from the repo”<\/h3>\n\n\n\n
Prompt engineering for vibe coding<\/h2>\n\n\n\n
A prompt template for functional modules<\/h3>\n\n\n\n
\n
Examples of follow-ups<\/h3>\n\n\n\n
\n
Technical examples: backend, frontend, SQL, infra<\/h2>\n\n\n\n
Flask + JWT + Swagger (abridged example)<\/h3>\n\n\n\n
# app.py\nfrom flask import Flask, request, jsonify\nfrom flask_jwt_extended import JWTManager, jwt_required, create_access_token\nfrom flasgger import Swagger\n\napp = Flask(__name__)\napp.config[\"JWT_SECRET_KEY\"] = \"change_me\"\njwt = JWTManager(app)\nswagger = Swagger(app)\n\nUSERS = {\"admin@example.com\": \"secret\"}\nORDERS = []\n\n@app.post(\"\/login\")\ndef login():\n data = request.get_json()\n if USERS.get(data.get(\"email\")) == data.get(\"password\"):\n return {\"access_token\": create_access_token(identity=data[\"email\"])}\n return {\"error\": \"invalid creds\"}, 401\n\n@app.post(\"\/orders\")\n@jwt_required()\ndef create_order():\n order = request.get_json()\n order[\"id\"] = len(ORDERS) + 1\n ORDERS.append(order)\n return order, 201\n\n@app.get(\"\/orders\")\n@jwt_required()\ndef list_orders():\n page = int(request.args.get(\"page\", 1))\n size = int(request.args.get(\"size\", 10))\n start = (page - 1) * size\n return jsonify(ORDERS[start:start+size])\n\nif __name__ == \"__main__\":\n app.run()\n<\/code><\/pre>\n\n\n\nUnit test with PyTest<\/h3>\n\n\n\n
import json\nfrom app import app\n\ndef test_auth_and_create_order():\n client = app.test_client()\n r = client.post(\"\/login\", json={\"email\":\"admin@example.com\",\"password\":\"secret\"})\n token = r.json[\"access_token\"]\n headers = {\"Authorization\": f\"Bearer {token}\"}\n r2 = client.post(\"\/orders\", headers=headers, json={\"total\": 1200, \"status\": \"new\"})\n assert r2.status_code == 201\n<\/code><\/pre>\n\n\n\nReact\/Next.js: a controlled form component with validation<\/h3>\n\n\n\n
import { useState } from \"react\";\n\nexport default function CheckoutForm() {\n const [data, setData] = useState({ email: \"\", total: 0 });\n const [errors, setErrors] = useState({});\n const onChange = e => setData({ ...data, [e.target.name]: e.target.value });\n const validate = () => {\n const e = {};\n if (!\/^[^s@]+@[^s@]+.[^s@]+$\/.test(data.email)) e.email = \"Invalid email\";\n if (Number(data.total) <= 0) e.total = \"Amount must be > 0\";\n setErrors(e);\n return !Object.keys(e).length;\n };\n const onSubmit = async e => {\n e.preventDefault();\n if (!validate()) return;\n await fetch(\"\/api\/orders\", { method: \"POST\", body: JSON.stringify(data) });\n };\n return (\n <form onSubmit={onSubmit}>\n <input name=\"email\" value={data.email} onChange={onChange} placeholder=\"Email\" \/>\n {errors.email && <small>{errors.email}<\/small>}\n <input name=\"total\" type=\"number\" value={data.total} onChange={onChange} placeholder=\"Amount\" \/>\n {errors.total && <small>{errors.total}<\/small>}\n <button type=\"submit\">Pay<\/button>\n <\/form>\n );\n}\n<\/code><\/pre>\n\n\n\nSQL: top customers by spend, with indexes<\/h3>\n\n\n\n
CREATE INDEX IF NOT EXISTS idx_orders_customer_date ON orders (customer_id, created_at DESC);\n\nSELECT customer_id, SUM(amount) AS total_spent\nFROM orders\nWHERE created_at >= NOW() - INTERVAL '90 days'\nGROUP BY customer_id\nORDER BY total_spent DESC\nLIMIT 10;\n<\/code><\/pre>\n\n\n\nIaC: a basic Terraform setup for a VPS deploy (excerpt)<\/h3>\n\n\n\n
provider \"aws\" { region = \"eu-central-1\" }\n\nresource \"aws_instance\" \"app\" {\n ami = \"ami-xxxxxxxx\"\n instance_type = \"t3.micro\"\n tags = { Name = \"vibe-app\" }\n user_data = file(\"bootstrap.sh\")\n}\n<\/code><\/pre>\n\n\n\nWordPress\/WooCommerce: an LLM-generated plugin skeleton<\/h3>\n\n\n\n
<?php\n\/*\nPlugin Name: WDS Vibe Example\n*\/\nadd_action('init', function () {\n register_post_type('wds_doc', [\n 'label' => 'Docs',\n 'public' => true,\n 'supports' => ['title','editor','custom-fields']\n ]);\n});\n\nadd_action('woocommerce_before_calculate_totals', function ($cart) {\n foreach ($cart->get_cart() as $item) {\n $product = $item['data'];\n $mult = (float) get_post_meta($product->get_id(), '_wds_multiplier', true);\n if ($mult > 0) $product->set_price($product->get_price() * $mult);\n }\n});\n<\/code><\/pre>\n\n\n\nQuality checks and security in vibe coding<\/h2>\n\n\n\n
Mandatory checks<\/h3>\n\n\n\n
\n
OWASP guardrails<\/h3>\n\n\n\n
Organizing a team around AI<\/h2>\n\n\n\n
Roles<\/h3>\n\n\n\n
\n
Git workflow<\/h3>\n\n\n\n
Where vibe coding saves the most<\/h2>\n\n\n\n
\n
Where you should stay careful or go manual<\/h2>\n\n\n\n
Advanced techniques and patterns<\/h2>\n\n\n\n
\n
In practice: zero to production in one day<\/h2>\n\n\n\n
\n
Metrics for vibe coding success<\/h2>\n\n\n\n
\n
WordPress\/WooCommerce integration (for practitioners)<\/h2>\n\n\n\n
\n
if (defined('WP_CLI') && WP_CLI) {\n WP_CLI::add_command('wds:fix-prices', function($args, $assoc_args) {\n $q = new WP_Query(['post_type' => 'product','posts_per_page'=>-1]);\n while($q->have_posts()){ $q->the_post();\n $id = get_the_ID();\n $mult = (float) get_post_meta($id, '_wds_multiplier', true);\n if ($mult>0) {\n $price = (float) get_post_meta($id, '_price', true);\n update_post_meta($id, '_price', $price*$mult);\n }\n }\n wp_reset_postdata();\n WP_CLI::success('Prices updated');\n });\n}\n<\/code><\/pre>\n\n\n\nRisks and compliance<\/h2>\n\n\n\n
\n
Vibe coding adoption checklist<\/h2>\n\n\n\n
\n
FAQ: quick answers<\/h2>\n\n\n\n
Can you rely on AI without review?<\/strong> No; always keep a human in the loop.
What about security?<\/strong> Put in place a secrets policy, SAST\/DAST, dependency audits, and mandatory tests.
Where do you start?<\/strong> Take a small service, write a spec, apply the prompt template, and wire up CI checks.<\/p>\n\n\n\nClosing thoughts<\/h2>\n\n\n\n