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How Do You Choose The Best Residential Proxy Provider? AMA with Stan Sadokov from NodeMaven
▲ 25 r/thewebscrapingclub+3 crossposts

How Do You Choose The Best Residential Proxy Provider? AMA with Stan Sadokov from NodeMaven

Hey everyone,

I'm Ian Kerins, CEO & Co-Founder of ScrapeOps.io.

After four great AMAs with the r/WebScrapingInsider community, we're excited to bring you our fifth guest.

This Thursday, August 20, at 10:30 AM GMT+3, we'll be joined by Stan Sadokov from NodeMaven for a discussion around one of the questions almost every serious scraping operation eventually has to deal with:

How do you actually choose the right residential proxy provider?

NodeMaven is a proxy infrastructure provider focused on residential, mobile, and ISP IPs, with an emphasis on IP quality rather than simply advertising the biggest pool.

Instead of relying purely on massive raw IP counts, NodeMaven uses real-time quality filtering to identify and remove flagged or low-reputation IPs before they cause problems for customers.

WebScrapingInsider AMA #5 with NodeMaven

During the AMA, we can dig into topics like:

  • Residential proxy quality
  • How proxy providers measure IP reputation
  • Choosing between residential, mobile and ISP proxies
  • IP rotation vs. sticky sessions
  • Proxy success rates and why they vary by target
  • Detecting and removing bad IPs
  • Proxy performance for large-scale web scraping
  • How proxy pricing actually works
  • What to look for when evaluating a proxy provider
  • Where residential proxy infrastructure is heading

We've had some great discussions in the community so far:

Our first AMA covered proxy infrastructure, Cloudflare bypass, browser automation, and scaling scrapers.

Our second with WebClaw explored AI agents, hidden APIs, open source scraping, and LLMs.

Our third with CloakBrowser went deep on stealth Chromium, fingerprinting, anti-bot detection, and browser automation.

Our latest with Browser Use brought insights on browser agents, AI-powered scraping, proxies, evaluations, and browser infrastructure.

We're excited to keep the conversation going.

If you're building web scrapers, data pipelines, browser automation, account management systems, or proxy infrastructure, or you're simply trying to figure out why one proxy provider works better than another, this should be a good one.

Drop your questions below, and Stan Sadokov from NodeMaven and I will start answering them during the AMA.

Looking forward to seeing everyone there!

Ian

reddit.com
u/ian_k93 — 1 day ago
▲ 12 r/GrowthHacking+2 crossposts

We launched Proxy Tester by ScrapeOps on Product Hunt 🚀

And it's already Featured 😄

https://www.producthunt.com/products/proxy-benchmark-by-scrapeops

We’d love your support 👍

Proxy Tester is a free tool that benchmarks 20+ proxy providers against the URL you actually want to scrape.

Over the last few months we've been using it internally and sharing it with early users to help answer one of the most common questions in web scraping:

Which proxy provider should I use?

One thing we've learned is that there really isn't a universal answer.

A provider that performs brilliantly on one target can struggle on another.

A provider with the highest success rate might not be the most cost-effective.

And many "best proxy provider" rankings don't reflect the website you're actually trying to scrape.

That's why we built Proxy Tester to benchmark providers against real target URLs and compare:

✅ Success Rate

✅ Latency

✅ Estimated Cost

✅ Value Score

✅ Provider Rankings

The feedback so far has been really useful and has already influenced how we're thinking about future benchmark reports, provider coverage, and scoring methodologies.

Today we're taking the next step and launching it on Product Hunt.

If you'd like to support the launch, leave feedback, or tell us what we're missing, we'd genuinely appreciate it.

🚀 Product Hunt:
https://www.producthunt.com/products/proxy-benchmark-by-scrapeops

🔧 Proxy Tester:
https://scrapeops.io/proxy-providers/tester/

🎥 1-Minute Demo:
https://youtu.be/GR67AIWkPn0

One question for the community:

How are you currently evaluating proxy providers?

  • Trial accounts?
  • Internal benchmarks?
  • Recommendations?
  • Something else?

Would love to hear how others approach this problem.

u/Kabhishek92 — 11 days ago
▲ 4 r/WebScrapingInsider

Browser Use vs Playwright in 2026: When Should You Use an AI Browser Agent?

Browser Use and Playwright solve browser automation in fundamentally different ways.

Playwright executes deterministic scripts written in advance. Browser Use gives an AI agent a goal and lets it decide how to complete it.

So when should you use each?

We recently hosted an AMA with the Browser Use team covering Browser Use vs Playwright, direct CDP automation, model costs, reliability, stealth, evaluation and the future of browser agents.

Here are the main takeaways.

The Short Answer

Use Playwright when:

  • The workflow is known and stable
  • You repeatedly extract the same data
  • The website does not change frequently
  • Speed and determinism matter
  • You are running high-volume automation

Use Browser Use when:

  • The workflow is open-ended or difficult to define in advance
  • The website changes regularly
  • The agent must adapt to unexpected states
  • The task involves authentication, multiple websites or multiple steps
  • Development and maintenance time matter more than raw execution speed

But there is now a third approach emerging: coding agents that write browser code directly against Chrome’s DevTools Protocol.

Why Browser Use Moved Away From Playwright

Browser Use originally relied on Playwright underneath its agent layer.

The team eventually replaced it with its own browser layer built directly on Chrome DevTools Protocol.

The reason was control.

Removing Playwright gave them more freedom over browser functions, fewer abstraction layers and the ability to let agents write CDP code dynamically when they encounter unusual edge cases.

Their newer BrowserCode approach takes this further.

Instead of receiving a simplified page representation and selecting predefined actions, the agent explores the browser and writes the low-level code it needs.

According to the team, strong models now:

  • Rarely rely on screenshots
  • Inspect pages through code
  • Discover internal APIs
  • Execute JavaScript shortcuts
  • Extract only the information needed
  • Complete some tasks faster than a human could

Browser Use says it now uses BrowserCode for almost everything because it is cheaper, faster and more capable.

The exception is website QA. BrowserCode actively looks for shortcuts, while the original Browser Use agent is constrained to click, type and navigate more like a human. That makes the human-style agent better at finding interface bugs a real user would encounter.

Stateful Agents vs One-Shot Scripts

One simple AI automation approach is to ask an LLM to write a Playwright script, run it and return any errors for the model to fix.

That works well for predictable workflows.

The limitation is that the script must anticipate the whole task before it starts.

A stateful agent works differently:

  1. Inspect the current browser state
  2. Choose or write the next action
  3. Execute it
  4. Verify the result
  5. Recover or change direction if necessary
  6. Continue until the task is complete

This makes agents better suited to websites and workflows where the exact path cannot be known in advance.

However, Playwright still has a major advantage: speed.

If you already know exactly what should happen, a deterministic script can execute the same workflow far faster than an agent reasoning between every step.

Cost Is Becoming Less Important

Browser Use estimates that the cost of completing an agent task has fallen roughly 50x since it started 18 months ago.

Its current estimates include:

  • A typical ten-step task costs around $0.01 to $0.02 using a low-cost model
  • A successful agent run can be converted into a reusable script
  • Repeating the script can cost fractions of a cent
  • Scraping 15 Hacker News posts, comments and linked pages, then summarising them into a poster, costs around $0.05

These are Browser Use’s own numbers, but they point to an important change.

The cost gap between AI agents and conventional automation is shrinking. The bigger remaining disadvantage is latency.

The team believes current models are becoming reliable and cheap enough for production, but they are still slow to watch in real time.

The Best Production Stack May Be Hybrid

The most practical pattern may not be choosing Browser Use or Playwright for everything.

Instead:

  1. Give the agent a goal
  2. Let it discover and complete the workflow
  3. Have it save the successful process as reusable code
  4. Run the deterministic version for repeated tasks
  5. Bring the agent back when the workflow changes or fails

This gives you adaptability during discovery and speed during repetition.

The agent solves and maintains the workflow. The script executes the stable parts cheaply and quickly.

Persistent Browser Identity Still Matters

AI does not remove the usual browser-automation problems.

For authenticated sites and social platforms, Browser Use recommends treating each browser profile as one persistent identity containing:

  • One fingerprint
  • One cookie jar
  • Local storage
  • Login state
  • Ideally, one stable IP and location

Its cloud profiles preserve the same fingerprint, cookies and local storage between sessions. The default proxy IP, however, is not guaranteed to remain constant.

For sensitive accounts, the team recommends a dedicated, non-shared residential IP with a low fraud score.

Creating new social accounts is also considerably harder than automating existing, established accounts.

Evaluation Is Still Difficult

Live websites are noisy.

Pages change. Browsers crash. IP quality fluctuates. CAPTCHAs appear inconsistently. A single successful run tells you very little about whether an agent is genuinely reliable.

Browser Use evaluates agents by:

  • Running realistic tasks on live websites
  • Defining verified success rubrics
  • Using an LLM judge to assess results
  • Repeating thousands of tasks
  • Averaging out browser and website flakiness

Internally, it records model inputs, outputs, reasoning, latency, token usage, caching, browser actions, screenshots and infrastructure logs.

One particularly interesting research takeaway from the AMA was that better verifiers may be more important than better action generation.

If you cannot reliably determine whether an unpredictable browser task succeeded, it is difficult to train agents through reinforcement learning.

Security Should Be Designed First

Browser Use’s main recommendation for anyone building a browser agent from scratch was to begin with sandboxing.

Permanent LLM credentials should not be stored inside the worker where the agent executes browser code.

Instead:

  • Store permanent credentials on a separate control plane
  • Give the worker a short-lived key
  • Proxy all model calls through the control plane
  • Treat the worker as disposable and potentially hostile

This gives agents the freedom to execute code without exposing permanent API credentials.

Agents Still Struggle With Taste

Browser agents are already effective at quantifiable tasks:

  • Finding the cheapest flight
  • Comparing prices
  • Extracting structured information
  • Completing defined workflows

They remain much weaker at subjective decisions such as choosing the right restaurant, hotel or holiday for a particular person.

The agent can retrieve every option and still recommend something that feels obviously wrong to a human who understands the user.

Browser Use described this as poor taste and a weak understanding of the social world.

Bottom Line: Browser Use or Playwright?

There is no universal winner.

Playwright wins when the workflow is stable, repetitive and performance-sensitive.

Browser Use wins when the task is dynamic, open-ended or expensive to define and maintain manually.

Direct CDP coding agents may be the next step, giving models enough freedom to inspect the browser, write custom code, find shortcuts and recover from edge cases.

The emerging production stack looks less like agents replacing scripts and more like:

Agent discovers the workflow → code executes it repeatedly → agent repairs it when it breaks.

That may be the real answer to Browser Use vs Playwright.

👉 Read the full Browser Use AMA and all the answers here.

What are you using in production: Playwright, Browser Use, a hybrid stack or direct CDP?

u/ian_k93 — 13 days ago
▲ 1 r/microsaas

AMA for the Best Browser Agent Stack in 2026? With the Creators of Browser-Use

If you've been following the AI agent space, you've probably seen Browser-Use everywhere.

What started as an open source browser harness has quickly evolved into a complete platform for building and deploying browser agents with over 107k stars.

This Wednesday, August 5, at 7:30 PM PDT, we'll be joined by Alexander Yue (Physics & CS @ Stanford SLAC, Evals @ Browser Use) and Reagan Hsu (Founding Engineer @ Browser Use), the team behind Browser Use, one of the fastest-growing open source projects at the intersection of AI agents, browser automation, web scraping, and stealth browsers

https://preview.redd.it/g3odai7qmjhh1.png?width=1080&format=png&auto=webp&s=db4122aa54ccb939a72079ffcf4739119a2815bc

During the AMA, we'll discuss topics including:

  • AI browser agents
  • Browser automation
  • Web scraping
  • Stealth browsers & anti-detection
  • Hosted browser infrastructure
  • CAPTCHA solving
  • Open source developer tools
  • LLM-powered automation
  • The future of browser agents

Looking forward to seeing everyone there: https://www.reddit.com/r/WebScrapingInsider/comments/1vcuosp/what_is_the_best_browser_agent_stack_in_2026_with/

reddit.com
u/ian_k93 — 15 days ago
▲ 28 r/agenticAI+5 crossposts

What Is the Best Browser Agent Stack in 2026? With the Creators of Browser Use

Hey everyone,

I'm Ian Kerins, CEO & Co-Founder of ScrapeOps.io.

After three fantastic AMAs with the r/WebScrapingInsider, we're excited to bring you our fourth.

This Wednesday, August 5, at 7:30 PM PDT, we'll be joined by Alexander Yue (Physics & CS @ Stanford SLAC, Evals @ Browser Use) and Reagan Hsu (Founding Engineer @ Browser Use), the team behind Browser Use, one of the fastest-growing open source projects at the intersection of AI agents, browser automation, web scraping, and stealth browsers

If you've been following the AI agent space, you've probably seen Browser-Use everywhere.

What started as an open source browser harness has quickly evolved into a complete platform for building and deploying browser agents with over 107k stars.

https://preview.redd.it/2y2entav1tgh1.png?width=1536&format=png&auto=webp&s=bc8c17871dc78e3978abf0b3da1319f9d4e6a858

Their recently released Browser Use v4 introduces:

  • Real browsers with logged-in profiles, proxies, and a live browser view
  • Fully hosted browser agents with zero infrastructure setup
  • Persistent sandboxed workspaces that can upload files, download results, and reuse environments across runs
  • Conversations that continue, allowing agents to pick up exactly where they left off
  • Plain English automation instead of scripts and CSS selectors
  • Built-in stealth browsers, anti-detect, CAPTCHA solving, and residential proxies across 195+ countries

Whether you're building AI agents, automating repetitive workflows, or extracting data from the web, Browser Use represents a very different way of thinking about browser automation.

During the AMA, we'll discuss topics including:

  • AI browser agents
  • Browser automation
  • Web scraping
  • Stealth browsers & anti-detection
  • Hosted browser infrastructure
  • CAPTCHA solving
  • Open source developer tools
  • LLM-powered automation
  • The future of browser agents

Our community has been growing with every AMA.

Our first AMA generated 43 comments, covering proxy infrastructure, Cloudflare bypassing, browser automation, monitoring, startup lessons, and large-scale scraping.

Our second AMA with the creator of WebClaw, generated 62 comments and sparked great discussions around AI agents, browser automation, hidden APIs, open source scraping, and LLM infrastructure.

Our third AMA with CloakBrowser generated 73 comments, diving deep into browser fingerprinting, stealth Chromium, anti-bot detection, TLS fingerprints, browser internals, and large-scale automation.

We're hoping this AMA will be our biggest one yet.

If you're building AI agents, browser automation, web scrapers, developer tools, or autonomous workflows, this is one you won't want to miss.

Drop your questions below, and Alexander Yue, Reagan Hsu, and I will start answering them during the AMA.

Looking forward to seeing everyone there!

Ian

reddit.com
u/ian_k93 — 15 days ago
▲ 27 r/AntiDetectGuides+5 crossposts

AMA This Wednesday (6:00-8:00 PM ET) with CloakBrowser: Open-Source Stealth Chromium for Automation

Hey everyone,

I'm Ian Kerins, CEO & Co-Founder of ScrapeOps.io.

After two fantastic AMAs with the community, we're excited to bring you our third guest.

https://preview.redd.it/9o8q5xdvlbfh1.png?width=1536&format=png&auto=webp&s=40e1445f22c5580c708c9d5408fcd3cd96f93f81

This Wednesday, July 29, from 6:00 PM to 8:00 PM ET, we'll be joined by the team behind CloakBrowser, an open-source stealth Chromium browser built for developers who need reliable browser automation and web scraping.

CloakBrowser takes a very different approach to stealth browsers.

It's not a patched Playwright configuration.

It's not JavaScript fingerprint injection.

It's a real Chromium binary with browser fingerprints modified directly at the C++ source level, allowing anti-bot systems to see it as a normal browser because it actually is one.

Even better, it's designed as a drop-in replacement for Playwright and Puppeteer, supporting both Python and JavaScript with the same familiar APIs and workflows.

I know we have fans here in r/WebScrapingInsider.

During the AMA we can the discuss topics like:

  • Modern browser fingerprinting
  • Building stealth browsers
  • Browser automation at scale
  • Open-source scraping infrastructure
  • TLS, browser fingerprints, and detection signals
  • The future of browser automation
  • Building open-source developer tools

Our first AMA generated 43 comments, covering proxy infrastructure, Cloudflare bypassing, browser automation, monitoring, startup lessons, and large-scale scraping.

Our second AMA with 0xMassii, creator of WebClaw, generated 62 comments and sparked great discussions around AI agents, browser automation, hidden APIs, open-source scraping, LLM infrastructure, and the future of AI-powered web scraping.

We're hoping this AMA will be just as valuable.

If you're building web scrapers, browser automation, AI agents, testing infrastructure, or simply want to understand how modern anti-bot systems actually detect browsers, this is one you won't want to miss.

Drop your questions below + RSVP now, and the u/CloakBrowser and I will start answering them.

Looking forward to seeing everyone there!

Ian

reddit.com
u/ian_k93 — 23 days ago
▲ 31 r/AIDiscussion+3 crossposts

AMA This Tuesday (10:00 AM CEST). Intersection of WebScraping and AI.

Hey u/WebScrapingInsider,

I'm Ian Kerins, CEO & Co-Founder of ScrapeOps.io.

After the great response to our last AMA, we're back with another guest from the web scraping world.

This Tuesday at 10:00 AM CEST (Italy Time) we'll be joined by 0xMassii, creator of WebClaw, an open-source Rust toolkit focused on extracting clean, structured web data for AI applications.

Massii sits at a really interesting intersection of web scraping, browser automation, anti-bot systems, AI agents, and LLM infrastructure.

As more developers build AI agents that need access to real-world information, one challenge keeps showing up:

How do you reliably get clean web data into language models?

https://preview.redd.it/9jrr0umpqzch1.png?width=1536&format=png&auto=webp&s=0d839e678db7530dfc6b7f4e3a75c41edfdaea7f

That is exactly the problem we are trying to solve.

Our previous AMA generated over 40 comments and sparked discussions on everything from Cloudflare bypassing and proxy benchmarking to scraper monitoring, startup validation, and large-scale scraping infrastructure.

We're hoping this one will be just as interesting.

If you're building AI agents, RAG systems, browser automation tools, web scraping infrastructure, or just trying to understand where the industry is heading, this should be a fun discussion.

Drop your questions below, We will start answering them during the AMA.

Looking forward to seeing everyone there!

Ian

reddit.com
u/ian_k93 — 1 month ago
▲ 19 r/scrapy+4 crossposts

Web Scraping Insider #8 | "ethical" residential proxy reckoning, free residential proxy tester, browser rewrite wave (CloakBrowser / Obscura / Camoufox)

Posted the latest Web Scraping Insider #8 if anyone here wants the full breakdown:

👉 https://thewebscrapinginsider.beehiiv.com/p/the-web-scraping-insider-8

https://preview.redd.it/073298wqhdah1.png?width=1200&format=png&auto=webp&s=fb13515fdeee641c3e79b23be01e364a5bfdb7d5

Quick summary of what's inside:

⚖️ When "Ethical" Proxies Aren't Ethical

"Ethically sourced" has become the proxy industry's favourite marketing word. Almost no provider will show you which apps their residential IPs actually come from - no public partner list, no audit trail, no independent verification.

The last couple of weeks made that gap impossible to ignore:

  • Spur Intelligence scanned 6,038 LG webOS + Samsung Tizen apps - proxy SDKs in 2,058 of them (42.5% on LG, 26.9% on Samsung)
  • Bright Data's SDK enrolling always-on smart TVs as exit nodes, with consent buried in TV remote arrow-key navigation
  • SuperBox streaming boxes (sold at major US retailers) shipping with dormant Popanet proxy software - routing third-party traffic through home connections with no meaningful consent
  • FBI/IC3 now warning consumers that everyday devices are being silently turned into proxy nodes

None of those device owners meaningfully opted in. Yet those same residential IPs feed pools sold as "ethical."

Our take: "ethical" should be a claim you have to prove - published partner list, audit trail, who consented / in which app / when - not a landing-page adjective. My bet is the market moves there within the next year or two.

---

🔮 Proxy Tester: now benchmarks residential proxies too (free for you)

We expanded the ScrapeOps Proxy Tester beyond proxy APIs. It already benchmarks ~15 proxy-API-style providers against your exact target URL. Now it does the same for residential pools, so you can compare both side-by-side.

https://preview.redd.it/bcaokzhthdah1.png?width=1163&format=png&auto=webp&s=e0abb2f36866657f4a0814bf0554d9c95093f661

How it works: submit your URL → real requests through each provider → every config they expose gets tested → ranked by success rate + cost per successful request.

Residential is where marketing fluff runs deepest ("30M+ IPs", "99% success rates"). From what we've seen across billions of requests, CPM rarely correlates with performance on your actual target.

Try it: https://scrapeops.io/proxy-providers/tester/

---

🥊 The browser wars are back: people are rewriting Chromium itself

For a decade, scraping browser innovation meant automation libraries on top of Chrome (Selenium → Puppeteer → Playwright). The browser underneath was treated as a commodity.

That may be shifting. Two forces:

  1. Anti-bot reads deeper now - TLS, network stack, process behaviour - so runtime patches (playwright-stealth, undetected-chromedriver) break more often than they hold.
  2. Chrome is heavy at scale. Thousands of concurrent browser instances (or long-running AI agents) make a purpose-built engine attractive on cost + startup time.

Projects worth watching:

  • CloakBrowser - Chromium fingerprints patched at the C++ source level, not JS injection. Drop-in Playwright/Puppeteer replacement. Claims 30/30 on public bot-detection suites.
  • Obscura - Rust headless engine from scratch, CDP-compatible so Playwright still talks to it. Claims ~70 MB binary, ~30 MB RAM, near-instant startup vs Chrome's 200 MB+ / ~2s. (Self-reported, v0.1.0 - treat as experimental.)
  • Camoufox - modified Firefox with C++-level fingerprint spoofing. Strongest headless evasion in independent tests we've seen. Proves this isn't only a Chromium story.

Stealth is moving below the automation layer. Most of these are young and several lean on self-reported numbers - don't rip out your production stack overnight - but the direction is worth tracking.

Bottom line: the residential proxy supply chain is getting scrutinised from every angle (smart TVs, factory hardware, federal warnings), the browser layer is getting rebuilt from scratch, and the boring work still wins - benchmark on your targets, measure cost-per-validated-payload, not vendor adjectives.

Happy to discuss specifics here - especially if you've benchmarked

— Ian (ScrapeOps)

reddit.com
u/ian_k93 — 2 months ago
▲ 31 r/thewebscrapingclub+5 crossposts

AMA This Wednesday (09:30 AM GMT)

Most scraping advice online falls into one of two categories:

  1. Things that worked 3 years ago.
  2. Things that worked once and became a LinkedIn post.

The reality is that scraping today is an adversarial environment. Anti-bot systems are getting smarter, proxy costs are changing, AI is reshaping workflows, and a lot of common advice simply doesn't survive contact with production traffic.

So this Wednesday at 09:30 AM GMT, I'll be doing an AMA here on r/WebScrapingInsider.

Ask me anything about:

  • Web scraping
  • Proxies
  • Browser automation
  • Anti-bot systems
  • Scraping startups
  • AI and scraping
  • Infrastructure
  • Reliability
  • Monitoring
  • Scaling

Or anything else that's been causing pain in your stack.

I dont have all the answers, but I have spent the last few years benchmarking providers, testing tools, breaking things, fixing things, and trying to understand what actually works versus what people claim works.

My bias is simple:
Benchmark everything. Trust nothing.

If a technique improves success rates, lowers cost-per-success, reduces operational overhead, or makes a scraper more reliable, it's worth discussing.

If it's mostly hype, we can discuss that too.

Feel free to drop questions below ahead of time, or join live on Wednesday.

Looking forward to it.

- Ian
ScrapeOps

reddit.com
u/ian_k93 — 2 months ago
▲ 1 r/WebScrapingInsider

AMA This Wednesday (09:30 AM GMT)

Most scraping advice online falls into one of two categories:

  1. Things that worked 3 years ago.
  2. Things that worked once and became a LinkedIn post.

The reality is that scraping today is an adversarial environment. Anti-bot systems are getting smarter, proxy costs are changing, AI is reshaping workflows, and a lot of common advice simply doesn't survive contact with production traffic.

So this Wednesday at 09:30 AM GMT, I'll be doing an AMA here on r/WebScrapingInsider.

Ask me anything about:

  • Web scraping
  • Proxies
  • Browser automation
  • Anti-bot systems
  • Scraping startups
  • AI and scraping
  • Infrastructure
  • Reliability
  • Monitoring
  • Scaling

Or anything else that's been causing pain in your stack.

I dont have all the answers, but I have spent the last few years benchmarking providers, testing tools, breaking things, fixing things, and trying to understand what actually works versus what people claim works.

My bias is simple:
Benchmark everything. Trust nothing.

If a technique improves success rates, lowers cost-per-success, reduces operational overhead, or makes a scraper more reliable, it's worth discussing.

If it's mostly hype, we can discuss that too.

Feel free to drop questions below ahead of time, or join live on Wednesday.

Looking forward to it.

- Ian
Founder, ScrapeOps

reddit.com
u/ian_k93 — 2 months ago
▲ 25 r/WebScrapingInsider+4 crossposts

Built an eBay scraper in Claude Code without touching selectors

I spent years doing the usual scraping workflow:

Find elements → write parser → run → debug → fix selectors → repeat.

Recently tested our Claude Code plugin that takes a target URL, generates the scraper, validates the output, and exports structured JSON automatically.

The result eliminated a surprising amount of repetitive setup work.

What interested me most was the workflow:

  1. Provide URL
  2. Choose language (Python, JS, etc.)
  3. Choose framework (BeautifulSoup, Playwright, etc.)
  4. Generate scraper
  5. Run scraper against real pages

For production teams, I don't think AI replaces observability, retries, QA, or anti-bot handling.

But it might dramatically reduce the time spent scaffolding new parsers.

Curious if anyone here is already using AI-generated scrapers in production.

https://www.youtube.com/watch?v=qpuEUaTzDZU

youtube.com
u/ian_k93 — 3 months ago
▲ 0 r/thewebscrapingclub+1 crossposts

We launched ScrapeOps AI Scraper Generator today, built for production workflows, not demo videos

We launched ScrapeOps AI Scraper Generator on Product Hunt today.

A lot of AI scraping products are optimizing for the demo:

"Paste any URL and AI handles everything."

That usually falls apart the minute you hit:

  • DOM drift
  • JS rendering
  • selector regressions
  • anti-bot behavior
  • missing fields
  • outputs that look plausible but are quietly wrong

So we took a more constrained approach on purpose.

https://www.youtube.com/watch?v=ij7CqrBEi10

The workflow is:
Enter URL → schema selection in backedn → choose stack → generate scraper code → AI scores how correctly the scraper ran.

Current features:

  • Schema-based scraper generation
  • Python + Node.js stack options
  • Playwright / Puppeteer / BeautifulSoup / Selenium flows
  • Live generation progress
  • AI-generated output scoring breakdown
  • Prebuilt scraper examples
  • Generated code developers can inspect and modify

The scoring layer is the part I care about most right now.

Generating scraper code is useful, but production scraping fails silently all the time. We wanted a system where AI checks how correctly the generated scraper output ran and gives users a breakdown across:

  • data accuracy
  • critical fields
  • completeness
  • structure
  • data types

Not "trust us, it returned JSON."

We're also running a small Product Hunt launch bonus for anyone who wants to pressure-test the generator properly.

New accounts already get 20 free credits, and for launch day we're doubling that to 40 total.

In the ScrapeOps dashboard:
Click Upgrade on Left → enter ScrapeOpsPH20

The extra credits will be added.

Would genuinely love feedback from people here who've dealt with scraping in production.

What matters more to you in AI-generated scraping workflows:

  • speed?
  • inspectable code?
  • retries/reliability?
  • anti-bot handling?
  • output scoring?
  • maintenance overhead?

Product Hunt:
https://www.producthunt.com/products/ai-web-scraper-builder

u/ian_k93 — 3 months ago
▲ 2 r/WebScrapingInsider

Web Scraping Insider #7 | free Proxy API tester for your target, distributed browser networks, stealth browser + Cloudflare bypass benchmarks

Posted the latest Web Scraping Insider #7 if anyone here wants the full breakdown:

👉 https://thewebscrapinginsider.beehiiv.com/p/the-web-scraping-insider-7

Quick summary of what's inside:

https://preview.redd.it/oyzgun2j893h1.png?width=1200&format=png&auto=webp&s=25c0147e63abd54d8b57ed2728cec21757701968

🔮 Free Proxy API Tester (your URL, not generic demos) We opened our internal Proxy Tester publicly. You submit a target URL and we benchmark ~15 proxy-API-style providers against it, testing the configs each provider exposes (residential routing, JS rendering, anti-bot modes, etc.), then rank by real outcomes:

  • Success rates
  • Latency
  • Pricing
  • Cost per successful payload

The point: "works" and "works profitably" are not the same thing. Most proxy marketing still collapses when you ask what you actually pay per validated payload on your target.

Try it: https://scrapeops.io/proxy-providers/tester/

🌐 Distributed browser networks: the "residential proxy moment" for browsers? Interesting thesis from Driver.dev: instead of running stealth browsers in datacenters, distribute real browsers across real consumer devices.

Anti-bot is increasingly fingerprinting full environments (GPU, hardware entropy, OS quirks), not just IP reputation. If that holds, cloud stealth browsers may become the new datacenter proxies.. detectable by default.. and real-device browser infrastructure becomes the next moat.

💸 Stealth Browser API benchmark (April 2026) We re-ran our stealth browser fingerprint test across 7 providers. Top of the board:

  • Scrapeless Browser — 90.95
  • Bright Data Scraping Browser — 89.05
  • Oxylabs Headless Browser — 85.71 (rebuilt since our first test; went from ~33 → 85)

Then there's a cliff. Several providers still leak automation signals (including CDP/framework checks), and once that happens, proxy rotation doesn't save you.

Notable pattern: top performers mostly came from traditional scraping companies with years of production anti-bot experience, not newer agent/browser startups.

☁️ Cloudflare bypass in 2026: 8 popular methods, only 3 had broad coverage We tested 8 common approaches across 20 protected sites. Roughly 60% of the advice stack doesn't hold up at scale.

What actually had coverage:

  • Smart Proxy APIs — 100% domain coverage (20/20), ~97% avg success
  • TLS impersonation (curl_cffi) — 80% coverage, strong when fingerprinting is the main gate
  • Browser APIs — ~60% coverage combined, much lower avg success depending on provider

Solvers, fortified headless browsers, cached pages, and origin IP bypass mostly underperformed or failed outright.

Bottom line: there isn't one "best" Cloudflare bypass. Different domains use different protections. Benchmark on your targets, optimize for cost-per-validated-payload, and don't trust vendor adjectives over measured outcomes.

If you're choosing proxy APIs, stealth browsers, or bypass stacks without testing them on your actual URLs, you're probably overpaying for underperformance.

Happy to discuss specifics here.. especially if you've run your own comparisons on hard targets lately.

- Ian

reddit.com
u/ian_k93 — 3 months ago
▲ 3 r/WebScrapingInsider

We're launching ScrapeOps AI Scraper Generator on Product Hunt - built from 3,000+ beta scraper generations

Hey WebScrapingInsiders,

Quick update from the ScrapeOps side.

We're launching ScrapeOps AI Scraper Generator on Product Hunt on May 27, 2026.

This has been in beta with ScrapeOps users, and so far the AI Scraper Generator has generated 3,000+ scrapers.

https://preview.redd.it/a826ag5ve83h1.png?width=1458&format=png&auto=webp&s=931c693dce1810a622911716b48c2b9902bc2aef

That gave us a lot of useful signal on what actually matters:

  • which page types people want to scrape
  • where generated code needs to be cleaner
  • which stacks people prefer
  • where schema selection creates friction
  • how useful AI-powered output scoring is after the scraper runs

"AI scrapes any URL."? That pitch is too vague and usually breaks the minute you hit real scraping conditions: DOM drift, missing fields, dynamic rendering, selector regressions, and output that looks plausible but is quietly wrong.

The workflow we’re building around is more controlled:

Give a URL → choose your stack → generate scraper code → AI scores how correctly the scraper ran

The generated code is inspectable, and the AI scoring breakdown checks things like:

  • data accuracy
  • critical fields
  • data types
  • structure
  • completeness

The goal is to remove repetitive setup, generate a solid first version faster, and give developers a clearer signal on whether the output is actually usable.

We're launching it on Product Hunt here:
https://www.producthunt.com/p/ai-web-scraper-builder

Would appreciate feedback from this community, specifically because you'll spot the real problems faster than a general launch audience.

reddit.com
u/ian_k93 — 3 months ago
▲ 2 r/WebScrapingInsider

We opened up our internal proxy benchmarking tool.. because "best proxy provider" is mostly nonsense

We've just made one of our internal ScrapeOps tools public: a live proxy provider benchmarking dashboard for web scrapers.

The idea is simple: compare proxy providers against real target websites, side by side, using actual performance data.

Right now it tracks:

  • Success rates
  • Latency
  • Pricing
  • Provider-by-provider performance on specific domains

The reason we built this internally is because the proxy market is messy. A provider can look great on one domain and completely fall over on another. Another provider might be slower but far cheaper per successful response. Another might market itself as "premium" but lose badly once you measure cost-per-success instead of sticker price.

That's the bit most proxy comparisons miss.

Price per GB or price per request is not the real number. The real number is:

How much does it cost to get a usable response from the target you actually care about?

We originally built this to power the ScrapeOps Proxy Aggregator. For the last few years, it's been part of how we evaluate providers and route traffic across them in production.

Opening it up publicly felt useful because the community needs fewer generic "best proxy provider" lists and more domain-level performance data.

At launch, it supports Proxy APIs. Residential proxy network benchmarking is next.

Feedback welcome. Especially interested in what people would want added next:

  • More providers?
  • Historical performance charts?
  • Cost-per-success rankings?
  • Region/device-type filters?
  • Exportable benchmark data?

Link is in the comments.

https://preview.redd.it/1vsth5uz1o2h1.jpg?width=1280&format=pjpg&auto=webp&s=f48401a4d15ce122f3e0745e82cabdebecc414ad

https://preview.redd.it/7tzqizuz1o2h1.jpg?width=1280&format=pjpg&auto=webp&s=7a3f2d1e4be6a7b8a2137923ac920ff982f6b3c1

reddit.com
u/ian_k93 — 3 months ago
▲ 2 r/venturecapital

Scraping tooling is moving from "data extraction" to reliability infrastructure

We're launching ScrapeOps AI Scraper Generator on Product Hunt on Tuesday, May 27, 2026.

What I observed was that.. most scraping tools sell the happy path. The real cost is what happens after that.

Selectors drift. Targets ship new front ends. Anti-bot behavior changes overnight. Someone HAS to debug why yesterdays 96% success rate is now 41%.

We're building around a more production-focused workflow:

  • Schema-based scraper generation
  • Python / Node.js stack selection
  • Live generation progress
  • Output quality scoring
  • Prebuilt scraper examples
  • Developer-first workflows instead of black-box demos

I dont think AI replaces scraper engineers. I think it removes a chunk of repetitive setup and gives teams a faster path to code they can inspect, modify, and ship.

Would be interested in hearing from investors/operators watching the data infra space:

Does AI-generated code meaningfully change the scraping market, or does reliability remain the real moat?

Were collecting pre-launch discussion here: https://www.producthunt.com/p/ai-web-scraper-builder

u/ian_k93 — 3 months ago
▲ 12 r/WebScrapingInsider+1 crossposts

We built a Claude Code plugin that generates crawler + scraper projects from a URL

We just posted a quick demo from the ScrapeOps YouTube channel showing how our Claude Code plugin generates a working web scraping project from a prompt.

The example in the video builds a crawler + product scraper pipeline for a Walmart search page. It generates the project files, schemas, parsers, README, run commands, and JSON/JSONL output. The demo uses Python + BeautifulSoup, but the plugin also supports other languages and scraping libraries like Scrapy, Playwright, Puppeteer, etc.

The part I'm most interested in feedback on is the workflow: instead of using AI to just write a parser snippet, the goal is to generate the full scraping pipeline and then let devs inspect, run, modify, or fix it from there.

Video covers:

  • installing the Claude Code plugin
  • adding the ScrapeOps to it
  • using /generate-scraper, /fix-scraper, and /generate-crawler-scraper
  • choosing language + library
  • generating crawler and product parser files
  • running the scraper and checking the structured output

This is still aimed at developers, not "magic no-code scraping."

https://www.youtube.com/watch?v=qcE5sK0DDus

The generated code still should be reviewed, especially for ToS/robots considerations, and production monitoring. But it's been useful for cutting down the boring scaffold/debug loop.

Would be interested to hear what people here think: useful direction, or does AI-generated scraper code create more maintenance debt than it saves?

youtube.com
u/ian_k93 — 3 months ago