Logical Dottech - Innovating the Future of Technology

Logical Dottech - Innovating the Future of Technology Logical Dottech is the fastest growing digital marketing company that offers social media marketing,

Logical Dottech is a Business Process & IT Consulting firm offering a vast range of Business Processing Responsive Web Design, Mobile Application Development, Internet Marketing, Custom Shopping Cart Solutions, IT Consultancy and other Value Added Service

21/08/2026

Anyone can read your JWT. That's not a bug - that's the design.

A JWT is three chunks split by dots. That middle chunk, the payload, isn't encrypted. It's base64. No key, no cracking, one function call and your user ID and role are sitting there in plain text.

So why is it safe? The third chunk. The server takes the header and payload, adds a secret key that never leaves the server, and hashes it. That's the signature. Change one character of the payload and the signature stops matching.

Which is why editing your role from user to admin doesn't work. The server recomputes the signature from what you sent, it won't match, and you get a 401.

Two catches nobody mentions: never put secrets in the payload, because it's readable. And you can't un-issue a token early, so keep the expiry short.

Comment "JWT" for the auth checklist.



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21/08/2026

You've seen that padlock a thousand times today. Most people think it means encryption got switched on. It doesn't.

The padlock is proof that a handshake already finished. Before any data moves, your browser and the server run four steps: hello (which ciphers do you speak), certificate (here's my ID, signed by an authority you already trust), key exchange (agree a secret neither side ever sent across the wire), then both switch to that key.

Skip HTTPS and every hop in between reads your password in clear text. The cafe wifi, the router, the ISP. With it, the same wire carries noise.

The certificate is the part that stops impostors. Anyone can claim to be your bank. Only your bank has one signed by a CA your browser trusts.

Comment "TLS" for the handshake cheat sheet.



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21/08/2026

You paste a giant, ugly link and out comes a tiny one, just seven characters. Click it and you land on the exact same page. How?

The short link is not a compressed version of the long one. The system saves the long URL in a database and hands back a brand-new short key. That key is just the next id number written in base 62 (0-9, a-z, A-Z). When you hit the short link, the server looks up that key, finds the long URL, and sends back a redirect. Your browser jumps in milliseconds. One tiny row per link, so a lookup stays instant even at billions of links.

Save the long URL, hand out a short key, redirect on click. That is a URL shortener.

Comment LINK and I will send you a minimal build. 👇

20/08/2026

You click buy and the site says "done" instantly. But the email, invoice and shipping label have not happened yet. So how is it already done?

The app does not do the work right away. It drops each task into a message queue and replies instantly. Separate workers pull tasks off the line and finish them in the background. If a worker crashes mid-task, the message is not deleted until it is done, so another worker just picks it up. Nothing is ever lost.

Reply fast, work later, never drop a task. That is a message queue.

Comment MQ and I will send you a simple starter setup. 👇

19/08/2026

How does an app handle millions of users without falling over? It doesn't rely on one giant server — it uses many, with a load balancer in front.

The load balancer spreads incoming requests across all your servers (round-robin is the classic method), constantly health-checks them, and if one server dies it instantly reroutes traffic to the healthy ones. Users never notice. That's how you scale horizontally.

Which would you reach for first under heavy traffic — add more servers (scale out) or a bigger server (scale up)?



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19/08/2026

Ever wondered how a chat app shows a message the instant it's sent — without you refreshing?

That's WebSockets. Instead of the browser constantly asking the server "anything new? anything new?" (HTTP polling), a WebSocket opens ONE connection that stays open, so the server can push data to you the moment it happens. Real-time, low latency, way less overhead.

What's the first thing you'd build with real-time data — a chat app, live scores, or a trading dashboard?



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18/08/2026

Ranking #1 and not appearing in the AI Overview used to be unusual. It's now the normal case.

Ahrefs studied 1.9 million citations in July 2025 and found 76% of cited pages ranked in the organic top 10, median position 4. By February 2026 that figure was 38%. BrightEdge, using a different method, measured it at around 17%.

So where are citations coming from? Roughly two in three now come from pages a user searching that keyword would never see on page one. Most overlap sits at positions 21 to 100.

And the finding nobody predicted: among citations that didn't rank in the top 100 at all, over 18% were YouTube URLs. YouTube is now the most-cited domain in AI Overviews, up 34% in six months.

The likely mechanism is fan-out. Gemini 3 became the default for AI Overviews in late January. Two caveats: the studies use different methods, and top-10 ranking is still the strongest predictor of citation. It just stopped being close to sufficient.

Comment "AIO" for the visibility audit.



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17/08/2026

Try this now: ask ChatGPT what your company does, when it was founded, and where it is based.

The largest study on this ran over 13,000 queries across ChatGPT, Perplexity and Gemini. 93% of companies had at least one basic fact wrong or missing. Roughly half of small businesses got at least one outright fabricated fact, compared to 32% of large companies. And AI confuses small business names with other companies about five times more often than large ones.

The details it gets wrong most, company size, contact details, founding year, are exactly the ones a customer acts on.

Here is the part people do not expect: usually nothing is being invented. The model is reading a stale source faithfully. An old directory listing, an abandoned company page, a review site carrying your pricing from two years ago. Your own website is only a small share of what a model reads about you.

So the fix is not on your site. Update the stale sources, directories, LinkedIn, review profiles, Google Business Profile, until the company name, founding year and services match everywhere. Then check your robots.txt. If you are blocking GPTBot, ClaudeBot and PerplexityBot, the model cannot read your side of it at all.

And run it again in a few months. Models retrain, and a fact you fixed can come back if the sources weaken.

Comment what it got wrong about you 👇

17/08/2026

I connected an AI assistant directly to my live WordPress site. Not a plugin with an AI feature. An actual connection where the assistant can read the site and act on it.

In the video: 40 published posts missing meta descriptions, found and written in under three minutes. By hand that is an afternoon of opening posts, scrolling to the SEO box, typing, saving, repeat.

The mechanism is Model Context Protocol, the open standard Anthropic released and OpenAI adopted. Your site exposes a set of tools, the assistant calls them. Because it is a standard, the same connection works from Claude or from ChatGPT. You are not locked into one assistant.

The part demos usually skip: this is not autonomous. It has admin access to a live site, so destructive actions sit behind approval and nothing publishes without review. I do not run it unsupervised on client sites and I would not suggest you do either.

Same connection handles orphan page detection, internal linking, schema, alt text, broken links and publishing, across WordPress, WooCommerce and Shopify.

It is called WP Taskify. Link in bio. Try it on a staging site first.

16/08/2026

The Stack Overflow survey asked 49,000 developers two questions. Do you use AI coding tools? 84% said yes. Do you highly trust the output? 3% said yes.

Adoption has climbed every year. Trust has fallen every year. That gap is the actual story of AI-assisted development in 2026.

The cost shows up in one place. 66% of developers say their biggest frustration is code that is almost right but not quite, and 45% say debugging AI code takes longer than writing it themselves. A separate survey of 200 senior SRE and DevOps leaders found 43% of AI code changes still needed manual debugging in production, after passing QA and staging.

The uncomfortable part: cleanly formatted, well-commented code gets less scrutiny in review, not more. Looking correct and being correct came apart.

Generating code stopped being the hard part. Verifying it is the job now.

Comment "AI" for the review checklist we use.

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