DEV Community: The Hidden Web

Cut Bright Data costs by up to 95%

The Hidden Web — Tue, 27 Jan 2026 01:13:09 +0000

Hi, I’m a professional working in web automation and business-flow automation for over 10 years.

If you use Bright Data, you know it can get really expensive fast.
A lot of what I do is to cut Bright Data costs for clients by up to 95%.

This is how I do it so you can reduce your BD cost now:

Understand what they are paying for
Create custom cookies to allow authentication
Create direct access between client and data

👾I will be focusing on the concepts here, because with AI nowadays, it handles most of the coding work.

Whether you’re hiring a developer or trying to DIY,** I’ve found that real understanding is far more valuable than technical details **

P.S. I use Cursor, which comes with AI. Very friendly interface.

1) Understand What You Are Paying For

Bright Data mostly sells proxies and data.
There are two types of data they sell:

** Dataset **– BrightData scraped the website and hosts a database. You pay a fee to access the data.
Web scraper tools – BrightData charges you for bypassing the websites.

The dataset option is already cheaper, but the biggest drawback is its low accuracy.

Most of my clients found the dataset not fresh enough to be used for real market products.

`This is what most people don’t understand — what the scraper tool is doing is handling bypassing for you.`

Requests

When you try to access a website, your software or website sends a request to the website.

When using software, it is often blocked.

BrightData’s scraper tool is charging you to bypass this block.

Once your request is allowed, you can obtain data.

In other words, if you can handle the bypassing, you will no longer need BD.

2) Create custom cookies to allow authentication

Websites evaluate your cookies to determine whether to allow your requests.

🍪Cookies are small browser-stored values that control session state and access.

If a website is an event, a cookie is like the ticket to enter the event.

Since websites typically will block your request, most of the work is simulating cookies.

To create the cookies:

Find out the minimum cookies you need(they come is sets)
Generate or bulk-collect them

You can reverse engineer and create the cookies yourself. Or, collect them from user browsers.

It might sound a little complicated, but for a lot of websites, it is much easier than you think.

Once you've done that you'll have functional cookies.

3) Create direct access between client and data

Now all you have to do is to** inject cookies into your requests.**

That’s basically attaching them to the request headers.(You can always give AI the cookies, and tell it to handle the rest)

Once you have functional requests, instead of sending a request to BD, you send it directly to the website.

Example: Let’s say I am using BD’s Amazon Scraper Tool “Collect By URL.” What I would do here is send a request directly to Amazon using the URL as my input.

🎉Voila! At this point, all of the cost** spent on data **from BD is eliminated!

Proxies

I will then switch to cheaper proxy services to cut costs further.
BD has really high-quality proxies, but does your project need them?

I ususally tried a lot of cheaper proxies.

There is a bit of mix-and-matching going on.

But the goal here is to find a service that is just pricey enough for your use case.

This is how I eliminate the cost of data from BD and lower the cost of the proxies.
And for most of my clients, this leads to a 70–95% price reduction.

The more data you are getting from BD, the more effective this method would be.

P.S. I made a video applying this same method to get Amazon data.It's a very fun watch haha 🔥➜Here

Why Automation Fails for Most Businesses & How to Appoach it like a Pro

The Hidden Web — Mon, 12 Jan 2026 20:03:24 +0000

With AI and new tech tools emerging, more businesses than ever are rushing to automate.

In my experience, about 70% of them waste time and money one way or another.

I’m a professional working in web automation and** business-flow automation** for over 10 years.

Here’s what I see:

Most automation projects don’t fail because of code.

They fail because of how the project is approached.

A lot of business owners don’t really know anything about automation. And that is a serious problem.

It’s like buying a car based only on what the salesperson tells you.

Understanding automation even at a basic level can save you massive amounts of money (whether you build it yourself or hire someone).

So I’m going to share how experienced automation teams approach this.

This always comes up: is automation illegal?

It depends on what your software is doing.

Scraping is often against a site’s terms. That does not mean illegal. Courts have ruled differently.

Facebook vs. Power Ventures (2008–2016) → ruled unauthorized.
hiQ vs. LinkedIn (2017–2022) → scraping was ruled allowed.

So it mostly comes down to how you access data and the scale of your operation.

That said, a lot of businesses get cold feet over legality, when in reality most blocking and enforcement is behavioral.

If you’re legitimate and not harming users, legality usually isn’t a major concern.

Use the Simplest Solution That Works

Complex systems look impressive during development, but they fail in production.

This is often an understanding gap between developers and business owners.

As a business owner, what you want is something that works and gets you results.

Sometimes developers are showing you how impressive the solution looks to them.

Many business problems already have solutions out there (unless you are a tech business).

Some automation projects are inherently challenging.

When choosing a proposed solution, go with the one most likely to work, and ignore how “new” or “trendy” it sounds.

🤖 Example: AI is a big trend right now. But just because a solution has “AI” in it doesn’t mean it’s better.

Always start with a minimum working process

Many patterns don’t appear in the first few runs.

This is why a lot of software fails with more traffic.

Start with something that works, even if it still has bugs and issues.

Once you have a working process, run a large number of tests.

When you run scripts many times, that’s when you discover popups, signup forms, captchas, and edge cases.

Instead of building a fully automated process from the start, use this loop:

partly manual → automate a little → test → adjust → repeat

Continue until the process is fully automated.

Production adds many moving parts, making problems harder to debug. Catch issues early and only scale when stable.

The Importance of MVP

Automation systems can get expensive.

Too many business owners end up with nightmare experiences — spending thousands of dollars on automation projects that never deliver real returns.

To avoid this, start with an MVP(with as low as 10% of the full cost) — a minimum working system that lets you test real usage and demand before committing to a full build.

MVP gives you a much clearer sense of market demand.

P.S. This also gives developers real-time insight into where the real problems and bugs can be.

Browser-Based vs Requests-Based Automation(⚙️ Little technical here)

Automation is used for many tasks, but it generally comes down to two types: browser-based and requests-based.

Browser-based automation = controlling a real browser (like Chrome or Firefox) to act like a human on a website.

Browsers automatically manage cookies, sessions, sequencing, and dynamic site values. In another word, it helps with bypass captcha or hidden keys.

Requests-based automation = sending direct HTTP requests to a website without opening a In another word, faster, lower infrastructure, and hosting costs.

🤖 Use-case rule of thumb

Large scale + clear request logic → use requests
Smaller scale + complex site behavior → use browsers

How to Save Money

When automation fails, the reason is rarely clear.

Some basic things to check are IP behavior, cookies, timing, and session flow.

Making automation work comes with experience. When hiring a developer, I don’t recommend hiring the cheapest option.

The math usually looks like this:

One inexperienced developer working 100 hours at $10/hour = $1,000
One experienced developer working 10 hours at $150/hour = $1,500

But after those 100 hours, you might not have anything that works 😮. And then you’re back to starting from scratch with negative $1000.

If you want to save money, a💵 better approach is to hire an experienced person for a few hours to consult or guide the project, and let a more junior developer handle the simpler parts.

Have a plan for after solution is devlieer

Think about what happens after the solution is built:

Who will handle updates?
If your developer handles updates, are they consistent? (switching developers often adds cost)
How often will updates be needed?

Finally,
When used right, automation can save a lot of time and money.

😊 I hope this was helpful. I also created a video that goes more in depth here:
https://youtu.be/pVbx1whCr_I?si=ZX8SVEbVsuxexrIm

How I Started Botting Pokémon Center in 6.5 Hours

The Hidden Web — Tue, 06 Jan 2026 17:08:53 +0000

Don’t know if anyone here is a big Pokémon fan 👀
With the new year, I got nostalgic and revisited some childhood hobbies.

When I couldn’t find anything in stores, I decided to turn it into a project.

So I built a Pokémon Center monitorϞ(๑⚈ ․̫ ⚈๑)⋆

This wasn’t about building the perfect system. The goal was to get something running ASAP.

Whether this is a hobby project or a minimal MVP - time can be limited and results mattered.

This is how created a working monitor in about 6.5 hours:

Establish stable site access (run many short tests)
Extract product data (test in console first before using script)
Scale runtime using an 80/20 approach
Add support functions

Final Result
The script visits target products and checks availability, price, and product URL.

If anything becomes available, I receive an email notification.

Avoids hard blocks like Error 15 / Access Denied,
Bypasses hCaptcha without solving it,
Logs runtime, failures, and last successful actions.

Step 1: Establish Stable Site Access
What I tested → what I got:

Standard Selenium → Error 15 / Access Denied ( no captcha, just a hard block)
Firefox → mixed results
Modified Chrome → slightly better than Firefox
End result:** Modified Chrome** worked best.

VPNs, Proxies, and the Real Discovery

What I tested & what I got:

ExpressVPN → helped on longer runs, no immediate difference
2Captcha proxies → helped on longer runs, no immediate difference

Cookies is probably the key.

Why Cookies Matter More Than You Think
Most sites use score-based detection, not simple allow/block rules.

That’s why blocking feels random: blocked 1 out of 10 times, or 7 out of 10 times.

Captchas usually appear when your score drops below a threshold. Raising that score works better than solving captchas.

❓What is cookies: Cookies are small data files used to maintain session context and behavior signals.

Even with rotating IPs, unchanged cookies can identify you.

A browser with no cookies often looks more suspicious than one with normal history.

Quick Way to Test Cookies: Manual Collection
I used software to open a modified Chrome browser.
I manually collected cookies by:

1.I visited YouTube.

2.I visited Walmart.

3.I searched for Pokémon Center instead of navigating directly.

This reduced captchas to less than 1 out of 10 visits.

Automate your Cookies Collection Process
After that, I wrote a short script that

opens random high trafficed sites,
saves cookies to files,
and injects them to future browsers.

Step 2: Extract Product Data
Many sites render content in JavaScript, so I started with JavaScript.

📌One speedy tip to avoid back and forth: Test and confirm selectors in the console before moving anything into Python.

Inspected the page in DevTools, tested selectors in the console, and confirmed the selector counts matched the products shown on the page.

After that worked, I moved the logic into Python for in-browser JavaScript execution

Step 3: Scale Runtime Using an 80/20 Approach
The script initially ran for 10–15 minutes.
I scaled gradually: 15 minutes, 1 hour, a few hours, 24 hours, then multiple days.

Each increase revealed new issues.

To complete the scaling, I

added more cookie variety,
adding stable proxy connections,
error notifications,
and error-handling.

🧱 Watch out: don’t let scripts keep running while getting heavily blocked. That can burn your IPs and triggers stronger defenses.

Step 4: Add Minimal but Effective Support Systems (hCaptcha)
Cookies removed about 9/10 hCaptcha cases in the first hour. After 5–7 hours, that dropped to 2–3/10.

Rotating proxies prevented performance degradation.

For the remaining cases, I used PyAutoGUI😂. It clicks the same hCaptcha location every time.

This pushed success to ~99% without external solvers.

P.S For scalable systems, use a Python built-in click methods, not PyAutoGui.

Takeaway
Don’t rush to solve captchas. If real users aren’t seeing them, check

cookies,

IPs,

browser,

and rate limits first.

P.P.S Wacth me do it here -