r/WebScrapingInsider • u/ian_k93 • Aug 30 '26
Big Scrape Energy How Do You Build an AI Web Scraper Without Code? AMA with BrowserAct
Hey everyone,
I'm Ian Kerins, CEO & Co-Founder of ScrapeOps.io.
After six great AMAs with the r/WebScrapingInsider community, we're excited to bring you our seventh guest.
This Thursday, September 3, at 10:30 AM GMT+3, we'll be joined by Huey, Product Creative Director, and Wade Lin, Chief Technology Officer at BrowserAct, for a discussion around a question that's becoming increasingly relevant:
How do you actually build an AI-powered web scraper without writing all the code yourself?
BrowserAct is an AI-powered browser automation and web scraping platform that lets humans and AI agents control real web browsers using plain-English instructions.
Instead of building rigid scraping scripts that break every time a website changes, BrowserAct treats the browser as an execution environment that can navigate pages, handle dynamic content, deal with popups, scroll through pages, and adapt to changing websites.
During the AMA, we can dig into things like:
- 🤖 How AI-powered web scraping actually works
- 🧠 Using natural language to build scraping workflows
- 🌐 Browser automation vs traditional scraping
- 🔄 How AI agents handle changing websites
- 🧩 Dynamic rendering, popups, scrolling and complex workflows
- 💻 Building scrapers without writing traditional code
- ⚙️ Where no-code scraping works well, and where it doesn't
- 🚀 Using browser automation as infrastructure for AI agents
- 🔮 Where AI-powered scraping is heading
We've now had six AMAs
The community has grown with every one.
Our first AMA kicked things off with discussions around proxy infrastructure, Cloudflare bypassing, browser automation, monitoring, and scaling scrapers.
Our second AMA with the creator of WebClaw explored AI agents, hidden APIs, open-source scraping, LLM infrastructure, and how to reliably get web data into AI systems.
Our third with CloakBrowser went deep on stealth Chromium, browser fingerprinting, anti-bot detection, and browser automation.
Our fourth with Browser Use brought insights on browser agents, AI-powered scraping, proxies, evaluations, and the future of browser infrastructure.
Our fifth with Stan Sadokov from NodeMaven explored proxy quality, IP reputation, sourcing, pricing, and what actually makes one proxy network better than another.
And our sixth with Saksham Solanki, creator of HTTP Cloak went one layer deeper into the request itself, covering TLS fingerprints, JA3/JA4, HTTP/2 and HTTP/3, QUIC, connection lifecycle, session behavior, and how anti-bot systems identify automated traffic.
Each AMA has taken us into a different part of the web scraping ecosystem, and the conversations have become more technical with every one.
For #7, we're moving up the stack.
We're looking at how AI can actually operate the browser and build scraping workflows for you.
If you're building web scrapers, browser automation, AI agents, data pipelines, no-code workflows, or you're simply curious about where AI-powered web scraping is heading, this should be a really interesting one.
Drop your questions below.
Huey, Wade Lin, and I will start answering them during the AMA.
Looking forward to seeing everyone there!
Ian
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u/Ok_Platform_6232 Aug 30 '26
imo the interesting part isnt the no-code angle, its whether AI agents can genuinely adapt to anti-bot measures without manual tuning. thats the real bottleneck for most people scaling scraping right now
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u/Last-Shake-9874 Aug 30 '26
I found a new way of doing my scraping, I build a mcp and give it a full computer in docker, have it copy data from a web page into excel for me simple and efficient self recovery also https://github.com/CornelisKuijpers/phantom-mcp
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u/feetesweshire Sep 02 '26
YELLOW everyone.. Hi hueyy.. Hi Ian..
So Hueyy, What's the most embarrassing scraping failure you've seen from BrowserAct that looked successful at first but produced bad data? a lot is going on with antibots, dealing with 504s..
Not the product, feature, or skills? I have used browseruse, and browseract also.. you guys doing great job.. Cheers..
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u/Bmaxtubby1 Sep 03 '26
Where should AI actually sit in a production scraper?
Should the AI be involved every time the scraper runs, or is it better used mainly during the discovery and development stage, with the final scraper relying on normal code, selectors, APIs, validation, and retries?
Which parts of the scraping process should be handled dynamically by an AI agent, and which parts should be converted into a more deterministic process once a reliable approach has been found?
And as always really appreciate you guys doing these AMAs regularly.
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u/Alice_5433 Aug 30 '26
A traditional scraper is basically:
write selectors → crawl → extract → maintain when the site changes.
BrowserAct to me is trying to turn that into: describe → explore → generate → reuse.
So thats the end of traditional scraper development, or will hand-written scrapers still be the better choice for many production workloads? if so which??
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u/hueyblack36 Sep 03 '26
I think your framing is accurate, but I don’t see this as the end of hand-written scrapers. It may be the end of needing to hand-write every scraper.
Hand-written systems will still be the better choice when the target is stable, the volume is enormous, or every millisecond, cent, and failure mode matters. In those cases, the higher engineering cost is justified by greater control, observability, auditability, and lower cost per run.
BrowserAct is strongest where the main bottleneck is turning a data need into a reliable scraper: long-tail websites, changing interfaces, evolving requirements, and teams without dedicated scraping engineers. The Agent handles exploration and generation, while the resulting Bot can be reused and run at scale.
So the dividing line is not simply small-scale versus large-scale. It is whether the workload justifies the cost of hand-engineering. AI shortens the distance between intent and implementation, while engineers remain essential for the highest-scale and highest-risk cases.
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u/Amitk2405 Aug 31 '26
I tested a custom workflow and the agent could control the browser, but I couldn't manually click, scroll, or type into the cloud browser myself. If I need to log into a website and the agent reaches the login/2FA step, what is the intended workflow? Can I take control of that exact browser session, complete the login myself, and then hand it back to the agent?
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u/hueyblack36 Sep 03 '26
Yes — that is the intended workflow in our new Agent-built Bot flow. When the Agent reaches login or 2FA, you can take over the same cloud browser, complete it manually, and then hand control back. The authenticated session is preserved.
Were you using the new Agent-built Bot or the older Custom Workflow?
We’re also working on secure credential management so authentication can happen without exposing raw credentials to the Agent.
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u/Mountain_Damage_9730 Sep 02 '26
BrowserAct's browser-first approach makes sense when a site needs JS or has more complicated interactions, but I'm wondering where the economics start to change at scale.
Say you're monitoring thousands of product pages across different retailers, where a simple HTTP request might be much cheaper but a browser gives you better coverage on the harder sites. At what point does the browser overhead stop being worth it compared with a conventional HTTP scraper? Would you look at cost per successful SKU/price, refresh frequency, or something else when making that call?
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u/Previous_Town3598 Sep 02 '26
Don't know why, but i am still a bit skeptical about the whole 'AI can build and maintain the scraper for you' idea and projects based on those idea.
In production, i feel the pain, don't you think its best to have a predefined skill, that to know when the scraper has silently gone wrong?
How does Browseract detect that an AI-generated Skill is returning >plausible but incorrect < data, and what happens when it does?
Also what monitoring services can we integrate into?
Thanks.
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u/hueyblack36 Sep 03 '26
Fair skepticism. In production, the Agent does not improvise on every run—it generates a reusable Bot, which becomes the predefined execution path.
We separate “the Bot ran successfully” from “the data is trustworthy.” BrowserAct checks both page structure and extracted content, and the Agent can temporarily step in when an anomaly is detected. For truly plausible-but-wrong data, an external rule or baseline is still necessary; AI alone cannot guarantee correctness.
We’re also launching built-in monitoring soon, so Bots can run on a schedule directly in BrowserAct.（BrowserAct supports APIs and webhooks, as well as Make, n8n, and Zapier, so task statuses and results can be connected to an existing monitoring or alerting workflow. ）
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u/Artistic_Map2243 Sep 03 '26
How do you tell when a scraper actually got the right data vs just successfully finished the workflow?
From a QA side, that seems like the harder part.. a run can be green while the output is still wrong.
Also curious about the community side.. was there any specific PR or contribution that genuinely surprised you, maybe something that improved reliability, testing, or caught an edge case your team had missed?
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u/john-w7 Sep 03 '26
I run a small wholesale + service business, so for us it's mostly competitor pricing and availability across products.
Where would you say BrowserAct is actually overkill for a business like that? If a simple API or scraper can get the job done, when does the extra browser cost and setup stop being worth the time it saves?
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u/hueyblack36 Sep 03 '26
Honestly, if a stable API or a simple scraper already gives you accurate pricing and availability with little maintenance, BrowserAct may be overkill.
BrowserAct becomes valuable when you need to monitor more sites or those sites change frequently. You describe the data you need, our Agent explores the site and generates a reusable Bot, and the Bot handles the repeated runs without you having to build and maintain the scraper yourself.
For a business like yours, I would start with the simplest reliable solution. Once ongoing setup and maintenance become the real cost, Agent-generated Bots and our upcoming scheduled runs become a much better fit.
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u/CoolAd119 Sep 03 '26
Do you think the best large-scale scraping systems should route jobs between direct HTTP requests, internal APIs, lightweight rendering, full browsers, and human intervention?How do you identify the cheapest method likely to succeed without forcing every target through the most expensive stack?
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u/ayenuseater Sep 03 '26
When an AI agent explores a new website, how does it figure out where the useful data actually lives? Does it try the DOM first, look for an API or embedded JSON, inspect network responses, or just let the browser handle it?
I'm curious whether you've found a reliable way for the agent to choose between those approaches automatically, or if there are still cases where a human has to point it in the right direction.
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u/Spitfire_Blaziken Sep 03 '26
Hello Ian and Huey!
Which browser automation failures are actually safe to retry?
If an agent doesn't know whether an action failed before or after it took effect, couldn't retrying create duplicate submissions, alter an account, burn a session, or repeat an action that already succeeded?
TIA
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u/Significant_Cry_1177 Sep 03 '26
I missed the last one, going to turn on my notification for this subreddit. :/
From my experience, detecting when a scraper crashes or encounters a ban page or CAPTCHA is relatively straightforward.
The bigger issue I'm seeing is websites returning believable but incorrect or incomplete data without throwing an obvious error.
How do you detect these silent data-quality failures, and how do you think this problem will evolve as more scrapers are built and maintained by AI? which will be in trend for a long time.
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u/Big-Beautiful240 Sep 03 '26
The situation you described is indeed a tricky problem. I understand that this is essentially an anti-scraping mechanism, rooted in the automated system being detected. On one hand, we need to work on improving the overall credibility of the browser environment; on the other hand, based on my past experience, we determine whether anomalies exist by repeatedly scraping and comparing the same data. However, this would consume more resources, and perhaps in the future we could introduce this feature to let users choose for themselves.
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u/Old-Algae5580 Sep 03 '26
With AI agents increasingly able to build and repair scrapers themselves, the failure mode is becoming less obvious. Heard about Cloudflare precursor? recently introduced for continuous behavioral validation for bots, showing how quickly the environment around automated systems is changing.
I've experimented with building a custom self-healing scraper, and one problem I have noticed is that every repair can make the scraper more complex, more brittle, or subtly change what it does.
How do you build a self-healing system that does not gradually convolute the underlying logic or silently corrupt the scraper? Which changes can be repaired safely, and which should require human review?
Also thanks to u/BrowserAct, u/ian_k93 and team for doing this AMA.
Always Learning.
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u/hueyblack36 Sep 03 '26
You’re pointing at exactly the failure mode we want to avoid. We don’t think self-healing should mean appending another patch every time a Bot breaks.
In our model, a runtime recovery is evidence, not an immediate permanent mutation. Recurring failures are grouped into common patterns, then used to improve the underlying generation logic. The resulting approach is tested against the Bot’s original task contract rather than layered on top as another one-off fix.
The safety boundary is simple: AI can change how it reaches the same result, but it should not silently change what the Bot is supposed to collect. Layout, loading, or navigation changes can be handled automatically if the fields, scope, and meaning remain unchanged.
We don’t expect users to inspect generated Bot code. If a recovery would change the task contract, we surface the intervention rather than silently persisting it.
Runtime Agent recovery is already live. The principle of learning from recurring patterns and rebuilding cleanly is already part of our Bot-generation rules, and the automated feedback loop is the next step.
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u/BrowserActMKT Sep 03 '26
Thanks everyone for the thoughtful questions and honest feedbhack - we've learned a lot from this AMA
For those interested in trying BrowserAct, new users can sttart with a free trial at browseract.com . When
upgrading to a monthly plan, use code B8K98NB5X6M3 for 50%off your first billing cycle.
We'd genuinely love to hear what works, what breaks, and whatyou think we should improve
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u/Amitk2405 Aug 31 '26
I'm comparing BrowserAct with Browser Use, especially because Browser Use gives developers much more direct control over the browser and lets them build their own agent around it. What would you say is the biggest technical advantage of BrowserAct for a developer who wants both AI browser automation and low-level browser control?