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r/searchengines






Key Metrics Tripled After Switching to Nitro.



Which Search Engines/Crawlers do you use mostly? Which Search Engines/Crawlers do you use mostly?
Debate

Which Search Engine do you use and find the most useful to provide you the results that you expect?

For me:

I use most of the time Kagi, a paid meta search engine that combines the search results of Google, Mojeek and Yandex altogether (the best world of all three search engine crawlers).

But I am also using Yandex, Mojeek or Brave Search if I want to use their search crawler individually (to fetch unique queries).

What I am using most of the time:

  1. Kagi (The best for general use)

  2. Brave Search (good)

  3. Yandex (especially good for niche searches in tech topics or 🏴‍☠️🦜 or blocked topics on Google. Feeling like the old Google Search Engine almostly)

  4. Mojeek (uncensored unbiased sources [in my opinion])

  5. Google (a shopping search engine to find products to buy, nothing more)


Engine with a decent AI slop filter Engine with a decent AI slop filter
Question

I can't use duckduckgo anymore because every search I make seems to turn up a wall of AI slop. It was bad enough when it was just blog posts copying and pasting each other, but since the proliferation of LLM's it's getting impossible to get to legitimate resources through duckduckgo.

Are there any search engines out there with a decent AI filter? I don't care about the LLM summary response, that is easy to scroll past. I want to be able to filter AI blog posts out of my search results.



How do you monitor when search engines discover new backlinks? How do you monitor when search engines discover new backlinks?
Self-promotion

I’ve been digging into how search engines actually discover and process backlinks, and it made me curious how other people monitor that process.

When a new backlink goes live, a few different things are happening behind the scenes:

• The page linking to you needs to be crawled
• The link needs to be detected and associated with your site
• The change eventually gets reflected in search tools or indexes

What I’ve noticed is that the timing can vary a lot depending on the platform you’re looking at. Sometimes a backlink appears in search engine tools fairly quickly, and other times it takes days or even weeks.

Because of that, I started testing a few backlink monitoring tools just to see how quickly they detect link changes compared to what eventually shows up in search engine data.

One tool I’ve been experimenting with recently is Linkwatcher, which focuses specifically on monitoring when links appear, disappear, or change on a page. It got me thinking about how different tools approach link discovery versus how search engines actually crawl and update their indexes.

I’m curious how others here handle this.

Do you mainly rely on search engine tools themselves to monitor backlinks, or do you use separate monitoring tools to catch changes earlier?

Also interested to hear if people have noticed big differences in how quickly search engines pick up new links.



Search tool for truth and contradiction. Search tool for truth and contradiction.
Search tool for truth and contradiction.

CRITICAL INFORMATION CONTEXT REPORT Building Reddit & Play Store Search Apps with LLM Search Grounding March 2026 | Derived from Conversation with Claude

Executive Summary This report documents the critical technical and architectural lessons learned from building a successful Reddit search tool in Google AI Studio, the reasons why replication attempts failed, and the precise requirements for successfully building both a Reddit/Quora search app and a Play Store search app using any LLM with native search grounding capabilities.

The single most important insight from this conversation: CORS cannot be bypassed by prompting. It can only be avoided by choosing an LLM that has a server-side search tool built into its infrastructure. The architecture — not the prompt — is what makes these apps work or fail.

  1. Why the Original App Worked The original ReddiQuest app built in Google AI Studio succeeded for three specific reasons, none of which were obvious at the time.

1.1 Server-Side Search Grounding The fundamental problem with building a Reddit search tool in a browser is CORS — Cross-Origin Resource Sharing. Browsers block any direct fetch() request to reddit.com because Reddit's servers do not whitelist browser-based requests. This is not a Reddit API issue. It is a browser security rule that applies to every website without explicit CORS headers.

The working app used Gemini's Google Search Grounding tool. When this tool is enabled in an API call, Google's servers — not the user's browser — go out and retrieve web content. Google's API endpoint is fully CORS-compliant because it is designed to be called from browsers. The data flows:

Browser calls Gemini API (CORS compliant — works fine) Gemini's servers fetch Reddit content (server-to-server — no CORS) Results return to browser as part of the AI response

Key code: tools: [{ googleSearch: {} }] — this single line in the API config is the entire reason the app works. Every failed replication likely omitted this or used it incorrectly.

1.2 The System Prompt Did Heavy Lifting The original prompt that generated the working app was described as simple and made early in a long series of attempts. This is not coincidental. Vague, high-level prompts allow the model to default to its most natural tool — in Gemini's case, its own search grounding. More specific prompts that mentioned 'Reddit API', 'fetch Reddit data', or similar technical details pushed the model toward broken approaches such as direct fetches, OAuth flows, or CORS proxies.

The system instruction inside the working geminiService.ts was well-structured: it defined a 5-step workflow (scan, extract, cross-check, identify contradictions, synthesize) and enforced a strict Markdown output format. This structured prompt produced consistent, parseable output that the UI could render reliably.

1.3 Retry Logic with Exponential Backoff The callWithRetry function wrapped every API call with 3 retry attempts, doubling the wait time from 1 second on each failure (1s, 2s, 4s). This prevented single network hiccups or rate limit responses (HTTP 429, 500+) from causing the app to fail entirely. Most quick replications skipped this and experienced intermittent failures that appeared to be architectural problems but were actually just transient network issues.

2. Why Replication Attempts Failed Multiple attempts to replicate the working app in Google AI Studio and with other models all failed. The failures clustered around the same root causes.

The most common failure. Any code containing fetch('https://reddit.com/...') will be CORS-blocked in a browser, always, without exception. No amount of prompting changes this.Direct fetch to Reddit: Technically correct but massively complex — requires app registration, client credentials, OAuth token management, and compliance with Reddit's 2023 API pricing changes. Not viable for a lightweight tool.Reddit OAuth API: Unreliable, often blocked, add latency, and represent a dependency on a third-party service that can go down at any time.CORS proxy services: The working app used gemini-3-flash-preview with googleSearch enabled. Attempts using older model strings or models without search grounding had no mechanism to retrieve Reddit data at all.Wrong model or no search tool: Telling the model to 'use the Reddit API' or 'fetch Reddit posts' constrained it away from the elegant search grounding solution toward broken technical approaches.Overly specific prompts:

3. LLM Compatibility — Which Models Can Do This This architecture depends entirely on whether the chosen model has a server-side web retrieval tool. This is an infrastructure feature, not a prompting capability. The following is accurate as of early 2026:

Models with server-side search: Gemini (Google Search Grounding), ChatGPT Plus/API (Bing search tool enabled), Claude via claude.ai (Anthropic web search tool), Perplexity (built entirely around this concept).

Models that cannot do this regardless of prompting: Any raw base LLM called via API without tools enabled, including GPT-4 without tools, Llama, Mistral, and local models. They have no mechanism to reach the web.

GLM-5 (from Zhipu AI, released 2025/2026) has been noted as a capable model but its search grounding capabilities are less standardised than Gemini or Claude. Attempts to use it for Play Store search failed, likely because the generated code defaulted to direct fetch approaches rather than using GLM's native search tool. The prompt must explicitly forbid direct fetches and enforce the search-grounding-only architecture.

4. The Reddit + Quora Extension The upgraded version of the app extended Reddit search to include Quora as a second source. These two platforms complement each other in a structurally useful way:

Raw, unfiltered community opinion. Messy, contradictory, and often brutally honest about real-world product behaviour after purchase or install.Reddit: More structured, longer-form answers. Often from users with stated expertise or professional backgrounds. Better for technical or procedural questions.Quora: Reddit catches what official sources and Quora answers sanitise. Quora adds depth that Reddit threads often lack. Running both through the same search grounding pass costs only one extra search call.Combined:

Important caveat: Quora aggressively paywalled its content from 2023 onwards. Google can index questions and opening lines, but full answers are often blocked. Reddit results will generally be richer and more complete. Quora is most useful for niche technical topics where its expert-contributor model produces high-quality opening answers visible in search snippets.

5. Critical Technical Problems Solved

5.1 Speed — From 4-5 Minutes to Under 90 Seconds The original agentic loop ran an unlimited number of searches sequentially, each completing before the next began. This produced thorough results but took 4-5 minutes. The fix was to cap searches at exactly 2 (one Reddit, one Quora) and split the process into two explicit phases: a fast non-streamed search phase, then a streamed writing phase.

5.2 Streaming — Results Arriving Word by Word The original implementation waited for the entire API response before displaying anything, which produced the 'one block arrival' experience. The fix uses the Anthropic streaming API (stream: true) during the writing phase. The response is read chunk by chunk using a ReadableStream reader and displayed progressively as each text delta arrives. Users see the report build in real time.

5.3 CSS Artifacts — 'text white', 'flex items-center' in Results When the search tool scrapes Reddit or Quora pages, it sometimes captures raw HTML including Tailwind CSS class names that appear as text in the results. This was fixed in two places: the system prompt explicitly instructs the model to ignore any text resembling CSS class names or HTML structure, and a cleanCSSArtifacts() function strips common patterns (text-, bg-, flex, grid etc.) from the rendered output before display.

6. Play Store Search — Key Differences The Play Store search app shares the same foundational architecture as the Reddit tool but has one additional layer of complexity: it must not just find apps, it must score them honestly on how free they actually are.

Play Store listings are written by developers and routinely obscure or misrepresent their pricing model. 'Free' on the listing page often means 'free to download with aggressive in-app paywalls'. The scoring system must therefore go beyond the Play Store listing and verify against at least two additional sources.

The fallback chain — Play Store first, official pricing page second, Reddit third — is ordered deliberately. Reddit is treated as ground truth over official documentation because Reddit users report actual post-install behaviour, not marketing copy. The badge system (Tier 1 through 5, from completely free to barely functional free tier) ensures the most genuinely free apps surface first regardless of Play Store ranking or developer marketing.

7. What Any LLM Needs to Succeed at This Regardless of which LLM is used, the following conditions must all be met for either app to work:

Native server-side search tool enabled in the API call — not optional, not replaceable by prompting Explicit instruction to use only the search tool for data retrieval — 'do not fetch directly' must be stated Retry logic with exponential backoff — 3 retries, 1/2/4 second delays on 429 and 500 errors Streaming enabled for the writing phase — non-negotiable for good user experience CSS artifact stripping — both in the system prompt and in the rendering layer Search cap — maximum 2-3 searches per query to keep response time under 90 seconds Fresh API client initialisation per request — do not cache or reuse the client instance

Failure test for any generated code: if it contains a direct fetch() to reddit.com, quora.com, play.google.com, or any target website, the code is broken before it runs.

8. Complete Build Prompts

8.1 Reddit + Quora Search App Use this prompt verbatim with any LLM that has a native search grounding tool (Gemini, Claude, ChatGPT with Bing tool, GLM-5 with search enabled):

REDDIT + QUORA SEARCH PROMPT "Build a Reddit + Quora search and analysis tool. Follow this exact architecture or it will fail:

HOW IT WORKS — non-negotiable:

  1. Use your native search grounding tool only. Do NOT fetch Reddit or Quora directly. Do NOT use their APIs. Do NOT use a proxy. Your built-in search tool retrieves data server-side — CORS will block any direct browser fetch. This is the only method that works.

  2. Run exactly 2 searches: "site:reddit.com [keyword]" then "site:quora.com [keyword]". No more — speed matters.

  3. Filter grounding metadata: only surface reddit.com and quora.com URLs. Label every insight [Reddit] or [Quora].

  4. Wrap every API call in retry logic: 429 or 500 errors wait 1 second and retry up to 3 times, doubling the wait each time.

  5. Initialize the API client fresh on each search call.

SEARCH SEPARATION — two phases: Phase 1: Run both searches (non-streamed, fast). Phase 2: Write the report and STREAM IT — text must appear word by word as it is written. Do not wait for the full response before displaying. Users see results trickle in, not arrive in one block.

CSS ARTIFACT PREVENTION:

  • Strip any class names (text-white, flex, bg-gray-500 etc.) from scraped content before rendering.

  • Ignore HTML tags, navigation chrome, cookie notices, UI structure.

  • Only extract actual human-written discussion content.

CONTRADICTIONS — primary mission: Find where users flatly disagree. Point vs Counterpoint format. For every contradiction, issue a fact-backed verdict. If Reddit and Quora contradict each other, note it explicitly and resolve it. Trust Reddit over official sources when they conflict.

OUTPUT FORMAT — strict Markdown, streamed:

[Topic] — Reddit & Quora Intelligence Report

Cross-Platform Consensus

Contradictions & Resolutions

Contradiction: [topic]

  • Red: [Reddit/Quora]: "[quote]"

  • Blue: [Reddit/Quora]: "[quote]"

  • Resolution: [evidence-backed verdict]

Hidden Gems

Raw Quotes

Platform Verdict

FAILURE TEST: If generated code contains a direct fetch() to reddit.com or quora.com, it is broken. Search grounding is the only data method."

8.2 Play Store Search App Use this prompt verbatim. The ranking logic and fallback chain are the critical additions over a basic search tool:

PLAY STORE SEARCH PROMPT "Build a Play Store app search tool that ranks results by how free they actually are. Follow this exact architecture or it will fail:

HOW IT WORKS — non-negotiable:

  1. Use your native search grounding tool only. Do NOT fetch Google Play directly. Do NOT use their API. Do NOT use a proxy. Your built-in search tool retrieves data server-side — CORS blocks direct fetches.

  2. Search query format: site:play.google.com [keyword] app

  3. Filter grounding metadata to only surface play.google.com URLs.

  4. Retry logic: 429 or 500 errors wait 1 second, retry 3 times, doubling wait each time.

  5. Initialize API client fresh on each search call.

RANKING LOGIC — score BEFORE rendering:

  • Tier 1 (Green FREE): Completely free, no limits, no account needed

  • Tier 2 (Green FREE): Free, generous limits (50+ uses/day, no card)

  • Tier 3 (Yellow FREEMIUM): Moderate limits, requires account

  • Tier 4 (Yellow FREEMIUM): Restrictive trial, aggressive upsell

  • Tier 5 (Red PAYWALLED): Free tier barely functional

Tier 1 always surfaces first. Tier 5 always last.

FALLBACK CHAIN — run in this exact order when Play Store data is thin:

  1. Play Store listing: clearly states free limits? Score and continue.

  2. Official website: search "[app name] pricing site:[app].com". Read the actual pricing page.

  3. Reddit: search "site:reddit.com [app name] free tier paywall". Reddit users report what happens after install, not the marketing. If Reddit contradicts the official site, trust Reddit.

  4. All three fail: show the card anyway, badge as UNVERIFIED, write "Free tier limits unclear — check before downloading." Never skip a result because data is sparse.

PAGINATION:

  • Return exactly 5 results per page load.

  • Results flow Tier 1 to Tier 5 across pages.

  • "Next 5" button loads next batch.

  • Each page load must feel fast — 5 results max per call.

RESULT CARD FORMAT — every card must show:

  • App name + Play Store link

  • Badge: GREEN FREE / YELLOW FREEMIUM / RED PAYWALLED / GREY UNVERIFIED

  • What's free: one line, specific not vague

  • What costs money: one line, brutally honest — do not soften paywalls

  • Source: Play Store / Official Site / Reddit / Unverified

FAILURE TEST: If generated code contains a direct fetch() to any Google Play URL, it is broken. Search grounding is the only method."

9. Summary of Non-Negotiables

  1. Architecture over prompting. You cannot prompt your way around CORS. The model must have a server-side search tool or the app cannot work.2. Search grounding is the only data retrieval method. Any direct fetch() call is a failure, regardless of how it is framed.3. Streaming is not optional. Without it, users wait 4-5 minutes for a single block of text.4. Reddit is ground truth. For both contradiction detection and pricing verification, Reddit user reports outweigh official documentation and marketing copy.5. Score before render. In the Play Store app, every app must be tiered before it is displayed. Rendering then scoring produces inconsistent, unreliable ordering.

End of Report • Generated March 2026

1 upvote 3 comments


Any search ends with the functionality Google used to have? Any search ends with the functionality Google used to have?
Feedback appreciated

I've been searching since the old days. I used to use Google with quotes, commands, and Boolean operators until I got fewer than 200 results. sometimes to zero results, then back off. This allowed me to find extremely rare information.

Google is completely broken now. Does any search engine exist that would allow me to do all of this today? Or is the majority of the web now lost and inaccessible?


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Which search engine generates the most 'global' results? Which search engine generates the most 'global' results?
Advice

I'm probably either wording this badly, or maybe imaging something that doesn't exist.

I'm looking for a way of researching a couple of subjects and generating the most worldwide, rather than localised, mix of results.

I've seen reference to Google.com/ncr as a way of bypassing localised redirects, but I'm not clearly if that would generate globalised Google results, or just provide US focused results.

Are there any cool alternatives, crawlers, tricks that could help provide a mix of results not anchored to any particular country?

Thanks in advance if you made it this far!


Search engine accuracy/performance comparison? Search engine accuracy/performance comparison?
Question

As per the title, do you know of any solid, test case based comparison or study?

The three aspects that I'm interested in the most are:

  • accuracy (ideally with search operators honoured)

  • crawling depth or indexing coverage + neutrality (ie not flooding me with most popular hits; in other words, I don't care what the SE 'thinks' is the best result, I want it to bring me strictly what I define in my query, even if it's from 1996 personal page of Mr Smith from the outskirts of the internet)

  • privacy

The Wikipedia comparison doesn't cover that. I found a brief thread touching on the subject here, but it's rather inconclusive.

I don't want SE recommendations, I know everyone has their favourite (or should I say 'least hated', these days?), but I'd like to see some data to help make choices about where to get the results I want rather than what a few big players want to feed me.

TIA.


Are websites blocking AI tools without even knowing it? Are websites blocking AI tools without even knowing it?
Debate

We looked at a few thousand US/UK websites (mostly B2B SaaS) and found that around 1 in 4 were blocking at least one major AI crawler. Most of the time, it wasn’t done on purpose, it was caused by CDN settings, firewall rules, or bot protection.

Makes me wonder how many marketing teams are creating content right now while some AI tools can’t even access their site. Has anyone here checked this on their own website?


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Built a commerce-focused embedding model for search — looking for feedback from folks running retrieval at scale Built a commerce-focused embedding model for search — looking for feedback from folks running retrieval at scale
Self-promotion

I’ve been working on a retrieval problem that shows up a lot in commerce search and AI assistants: relevance often isn’t the main bottleneck — latency, infrastructure cost, and structured product understanding are.

Most embedding models treat products as plain text, which loses attribute structure (brand, color, size, etc.). I’ve been experimenting with a commerce-specific embedder that:

  • Preserves multi-field product structure during indexing

  • Targets interaction-grade latency (~30 ms p95) for real-time systems

  • Improves recall on low-intent and attribute-heavy queries

  • Runs efficiently with smaller vector dimensions

Curious how others here are approaching:

  • structured indexing vs raw text serialization

  • attribute binding in embeddings

  • latency vs relevance tradeoffs in production search

  • embedding model versioning / compatibility

Happy to share details or compare notes if useful.




What’s the most reliable visual search engine right now? What’s the most reliable visual search engine right now?
Advice

I’ve been experimenting with different visual search engines lately — mainly to identify random objects, places, screenshots, and things I come across online. Some tools work okay, but a lot of them either push shopping results or feel hit-or-miss with accuracy. I’m more interested in something that actually helps understand what’s in an image, not just show similar pictures. For those who’ve explored this space a bit: Which visual search engine have you found most reliable?

Do you use it for specific tasks (objects, landmarks, screenshots, etc.)?

Any websites you’d recommend checking out?

I’m just trying to explore a few solid options based on real user experiences rather than ads or rankings. Would appreciate any suggestions.


Why in gods name is Youtube not intregrating Ai search engines or whatever the teachnical term is. Why in gods name is Youtube not intregrating Ai search engines or whatever the teachnical term is.
Question
Why in gods name is Youtube not intregrating Ai search engines or whatever the teachnical term is.

it would make searching for random, rare, unique and specific videos soo much more feasible. sSoo many random videos i remember from the old days and i just cannot remember the title.

dude fire whoever is running youtube and get a better guy with ideas.






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Search Engines that actually let you disable AI? Search Engines that actually let you disable AI?
Advice

Today I learned that adding -ai to Google search does not in fact stop the environmental cost of creating the AI Overview. It just doesn't show it to you, but it still makes it. Or that's my understanding from doing some reading (including, ironically, from the AI Overview). From reading up on duckduckgo, it looked to me like the same story - you can request a view without the AI search results so you don't have to see them, but it still costs as much energy-wise as a search with it turned on. 99% of the time I search, I don't need or want AI results. I'm fine with manually hitting a toggle/button on the rare occasion I do and waiting a bit for it to come in. Are there alternative search engines that either don't have ai features or that let you actually disable them? Or am I wrong and one of those actually lets you disable it?




How to get real results on iOS How to get real results on iOS
Advice

Something I’ve been finding lately is that so many of the searches I do end up with nothing but best of lists, ai generated sites and maybe 1 or 2 genuine results. Also many of the results will just be repeated over and over. I’m using DDG on Safari on iOS. I have seen people say to go to the Brave browser but I haven’t been fond of how they’ve gone down the crypto route. Unless that can be completely isolated and shutdown I kinda don’t want to use that browser. But the thing is I can’t get Startpage (which I use on my Android tablet and my PC) on Safari so yeah


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Will every website need a Model Context Protocol (MCP) as AI browser agents become more common? Will every website need a Model Context Protocol (MCP) as AI browser agents become more common?
Idea
Will every website need a Model Context Protocol (MCP) as AI browser agents become more common?

With Anthropic's new "Piloting Claude for Chrome" research preview, we're seeing a glimpse of a future where AI agents can truly navigate the web. These aren't just chatbots; they can see what you see, click buttons, and perform complex, multi-step tasks on a user's behalf.

This brings up an important question for web developers: Will we need to start building websites with the Model Context Protocol (MCP)?

For those unfamiliar, MCP is an open-source standard created by Anthropic that provides a way for LLMs to securely and efficiently communicate with external services and data sources. It essentially gives AI a standardized "language" to interact with the web.

Instead of just creating a user-friendly interface for humans, will we now also need to create a machine-friendly interface for AI? What does this mean for website design, accessibility, and security?

What are your thoughts on this? Is this a new best practice for the future of web development, or a niche concern for a small number of sites?

18 upvotes 50 comments


What Is The Best Search Engine For Pictures In Your Opinion? What Is The Best Search Engine For Pictures In Your Opinion?
Help

I'm really trying to find a Search Engine that has really good and clear pictures. I was using Yahoo Image Search. But every since they updated the Android App they have completely ruined it by putting Text Captions under the Images and making the pictures a lot smaller too now. What Search Engine can I use where I can see Pictures that are big and that don't have Text Captions under them? I'm open to all kinds of suggestions for Search Engines. You can barely see any pictures on the Yahoo Search Mobile Android App because the Text Captions are covering more than half of it.



Review: Navo mobile search, combines Reddit, TikTok, and web results to escape SEO spam (looking for similar tools) Review: Navo mobile search, combines Reddit, TikTok, and web results to escape SEO spam (looking for similar tools)
Alternative

I've recently been using an app called Navo for mobile search. It lets you instantly see results from Reddit, TikTok, and LLMs, side-by-side, so you get different perspectives and actual user opinions, not just SEO-optimized sites and ads.
It’s been a serious time-saver, especially for things like product research or figuring out trending topics. One catch: after talking with the team, it sounds like Navo will be moving to a paid model because they’re running things with LLMs, similar to Perplexity but focused more on media/social content.
Has anyone else tried it? I’m also curious, what other tools or workflows are people using to surface community answers and avoid the usual junk sites or endless affiliate blogs?
Would love other suggestions (free or paid).



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Any new search engines? Any new search engines?
Any new search engines?

Since its been almost 3 decades since search engines came out , and since the last 15 years Google' search capabilities have significantly decreased , or in other words Google, 20 years ago was better despite the company today having 100x more money infrastructure and better algorithms now. They just used them to milk the cash cow they have created (all of the algorithmic capabilities and computing power are geared toward making them more money not improving their search. Now when we consider all the tech improvements in the last few years I am asking if there are any new search engines that have spectacular search? I am not asking about privacy concerns, only about search capabilities (yes duckduckgo, and bing suck just as bad as google at search right now)

8 upvotes 21 comments

Post ranking on Bing but not on Google Post ranking on Bing but not on Google
SEO

I have a few posts that rank well on Bing but not on Google. I know that they are weak in EEAT and, to be honest, they probably don’t deserve to rank on Google.

However, I am afraid those poor posts might be dragging down my site on Google, as Google also uses site-wide quality signals. I cannot update them much due to a lack of EEAT on those topics.

What is the best strategy here? Delete them or keep them? Deindex from Google?


Search engine with google results Search engine with google results

I’m using a VPN and I always end up getting captchas every time I search something on Google. I know there are extensions to bypass them but I’m using Brave on iOS so I can’t use them.

I’m looking for a new search engine that gives the same results as Google without captchas. Privacy is good but not that important to me tbh. Do you have any suggestions? I know a lot of search engines but usually I prefer google results, so the closest results the better.







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Web Search as If From the Command Line (!Bangs but better) – trovu.net Web Search as If From the Command Line (!Bangs but better) – trovu.net
Self-promotion

I've built trovu.net which allows you to do web search as from your command line. Examples:

You might know the idea as !bangs from DuckDuckGo but trovu's shortcuts take two or more arguments, and those arguments can even be typed. It also runs entirely in the browser, sending no query to my server, giving you maximum privacy.

Trovu also has built-in localization by organizing shortcuts into namespaces:

  • fr tree picks the French–German dictionary if your browser’s preferred language is German.

  • a shakespeare will search on Amazon.ca if your browser’s preferred language is en-CA.

  • w berlin searches Wikipedia in your language.

  • fr.w berlin searches the French Wikipedia, overriding your browser’s language.

You can also perform simpler searches:

  • g berlin searches Google for “berlin”

  • d berlin searches DuckDuckGo for “berlin”

  • gol pl, berlin searches Google for “berlin”, but only pages in Polish

There are 6,000+ curated shortcuts, maintained in a GitHub repo.

Other features include:

Feedback and suggestions are welcome.




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Google Indexing problem: Discovered, Currently not indexed Google Indexing problem: Discovered, Currently not indexed
SEO

I am working a website built over nextjs 16.

The problem is that google indexing all my page in minutes that has least content like homepage, /categories, /categories/ai these pages rarely have anything but got indexed.

But not indexing the actual post. Shows Discovered: Currently not indexed.

What could be the problem?

robots.txt is good, sitemap is proper.


TODAY: JavaScript SEO AMA with Sam Torres. Post your questions now! TODAY: JavaScript SEO AMA with Sam Torres. Post your questions now!
JavaScript SEO AMA with Sam Torres!

Confused about JavaScript rendering? Got questions about what search engines and LLMs can "see" and what they can't? Need help with a particular JS issue? Listen up! JavaScript SEO expert, Sam Torres u/samstorres , will be here in r/javascriptseo_ to answer your questions: Thurs 29 Jan, 4pm GMT (11am ET). You can post your questions ahead of time and/or join LIVE for the Q&A.

Thank you to everyone for participating in our first AMA! If you still have questions, post them in the main subreddit - thanks!

6 upvotes 35 comments

Help finding obscure article my beloved boss was in? Help finding obscure article my beloved boss was in?
Feedback appreciated

I have searched everywhere I could think of, so I’m coming to the experts… My director recently retired and stunned us all before he did by revealing to us that he posed in a magazine in a Speedo. For context, we’re all oncology researchers. He’s a buttoned up Yale graduate. Used to be a professor. Lovely guy, but exactly how you’d imagine a scientist who graduated from Yale to be. So while playing an innocent game of 2 truths and a lie for his retirement party, he seemingly made it obvious which statement was a lie - he sang a cappella in college, he’d been to Japan, and he posed in a Speedo for National Geographic. Of course after we all made our very wrong guess that our nerdy boss lied about posing half naked in a magazine, he immediately came back and said, “how could you all think I would sing a cappella?” He did this as part of a study for exercise physiology in the 90s or early 2000s. He was covered in electrodes and on a treadmill. His name is Richard Kennan. Those are the only details he was willing to spare. I have searched the internet and libraries but to no avail. So have my colleagues. (It is not lost on us that we can’t find this given our profession). I would love to give this photo to my coworkers as a Christmas gift. Rich is and will always be beloved. Having this photo in our office will be a treasure. If you can help, you will also be a treasure. Thanks in advance.







Quick question about a push mower engine Quick question about a push mower engine
Quick question about a push mower engine

So i have a push mower engine that i would use in a home made go kart but for some reason whenever i start it the engine low revs for about a second then starts going in very high revs which im scared could over rev it.

I do not know why it does that and i wish i could find some help here.

Thanks 🙏

1 upvote 8 comments

Does anyone else hate maintaining ETL pipelines for internal search? I built a tool to kill them. Does anyone else hate maintaining ETL pipelines for internal search? I built a tool to kill them.
Feedback appreciated
Does anyone else hate maintaining ETL pipelines for internal search? I built a tool to kill them.

Hey everyone,

I'm looking for some honest feedback on a project I'm working on called BlueCurve.

The Context:

In my last role, we spent more time writing scripts and a lot of messy code to clean data for ElasticSearch than we did actually using the search. And don't get me started on the security reviews every time we wanted to index something sensitive and the index security themselves

The Idea:

I’m building a search engine that treats isolation and ingestion as the primary features, not afterthoughts.

No Pre-processing: You throw raw documents (PDFs, Office docs, JSON blobs) at the API, and it handles the OCR and parsing automatically.

Security:

I use Firecracker microVMs to isolate the indexing process. If a malicious file tries to break out during parsing, it's trapped in a disposable VM that dies in milliseconds. For index security (actually what documents are visible to whom), i develop a custom DSL that describes the access using a google zanzibar style approch, i tested directory sync using keycloack and my zanzibar style approch. So, it is possible to control access easily.

My Question for you:

As DevOps/Sysadmins, is "Data Isolation" a major headache for you when deploying search tools? Or are standard ACLs (Access Control Lists) usually enough?

I’m trying to figure out if I should double down on the "Security" angle or the "No-ETL" angle.



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Clickbait fooled us, Al isn't buying it! Clickbait fooled us, Al isn't buying it!

The current web is filled with click-attracting headlines and high-level content that doesn't provide much value, and it's this way by design because the search engines money comes from the time people spend on them.

So, it's always a give or take on providing just good enough content to retain a user but not easily provide all information so they come back. Also, the attention span of all of us is low, so writers need to cut out relevant information to avoid getting the reader bored.

This led to many click-attracting experts writing content and topics that they barely understand, and along the way undervaluing writers who have done the research and put the time to write about complex topics.

With the rise of LLMs, now everyone can write "good" content because they were trained on that clickbait expert content, but foundational LLMs as well as people struggle to write something NEW because it's just hard to do it. To write something new and valuable, there needs to be human interaction or some way to collect information about changes in the physical world and transfer them to the web in an organized and descriptive manner.

My hope is that more and more people who are industry experts start creating relevant content with the use of LLMs! And then Al agents will navigate the web with clear goals and will bypass all the clickbait and find content that does provide value!

Only this valuable content will be picked up by agents doing online search!



Image search that allows specifying an exact size? Image search that allows specifying an exact size?

I saw a modified version of an image that would work well in photoshop layered on the version I already have, didn’t initially save it and now I can’t find it again. The one I have is a specific oddball size though. Does anybody know of an image search that lets you specify an exact image size? With that I could pretty much use general search terms and find it easily.

Thanks.


Are Ecosia and Duck Duck Go poorer search engine experiences even if they are better environmental choices than google? Or is it just me... Are Ecosia and Duck Duck Go poorer search engine experiences even if they are better environmental choices than google? Or is it just me...

I get way less results on both platforms compared to google. I certainly don’t want to support the big corporate giant, but I wonder why so many results aren't being shown on Duck Duck and Ecosia...




Looking for feature ideas for a search engine project Looking for feature ideas for a search engine project
Feedback appreciated

Hello everyone,
I am currently developing a new search engine and am interested in hearing suggestions for useful or innovative features to include. The project is still in its early stages, so any advice on features you would want in a search engine, including search functionality, user experience, or anything else that could improve the product, would be greatly appreciated.

Thanks!


At this point I’ve accepted that I’m not gonna hand-model anything. Meshy does it for me in like 2 minutes. Text in, model out. It’s like AI gacha for 3D devs. Code MESHYHALF if you’re also done pretending you’ll “learn it properly someday.”











お誕生日おめでとう🍰



I stumbled across a new search engine I stumbled across a new search engine

I found this "new" search engine called "Void" and I noticed it is cleaner, more customizable, and sleeker than Google. It is considered lesser-known

Although it claims to have privacy, it's not clear +

It has ads on the homepage but not in search results.

Here are the Pros

  • Cleaner, Minimal UI

  • Customizable Homepage

  • Integrations

  • AI integration

  • Ability to change the priorities of search results

And here are the Cons

  • Paywalled

  • Has ads

  • Proprietary / Closed Source

Non-referral link: https://askvoid.com/

I have heard it integrates with reward extensions

My rating: 7/10
It is great for beginners, but if you are serious about privacy, you might wanna use SearX/SearXNG (Free) or metaGer (Paid) instead.


User Agents and real-time searches for AI chats User Agents and real-time searches for AI chats
Comparison
User Agents and real-time searches for AI chats

We did a quick experiment on when and how the AI chats are searching web pages.

We recently published a webpage on our site that was not yet indexed by Google. We then asked different chats ChatGPT 4o & o3, Gemini, Perplexity & Claude sonnet to summarize the page (like this:

(I  kept blind-spot part of URL for fun as the rest is blurry).

We then checked our bot tracker to see what pages loaded. Here's what we found:

Model User-agent Result
Perplexity Sonar Pro Perplexity-User Loads the HTML only each time. No JS/images loaded
Gemini 2.5 Flash Google (user agent was "Google" lol) Loads the HTML only each time. No JS/images loaded
Claude 4.0 Sonnet Claude-User Loads the HMTL one time per URL. Will cache future times. No JS/images loaded
OpenAI 4o NA DOES NOT LOAD THE URL. Only relies on searching Google for the gist of the URl like "Rivalsee free prompt fix vibe coding SEO blind spot" Did not think page existed.
OpenAI o3 ChatGPT-User Loads the HTML only each time. No JS/images loaded

Some take-aways.
* All of the real-time searches are not loading JS. They are just grabbing content from the html
* OpenAI 4o is NOT actually searching the web. They are likely searching Google
* It appears that claude Sonnet is caching pages but the rest are not.

If there are other chats you think we should include, let us know and we can update this.

8 upvotes 20 comments


I lost my hopes for DDG I lost my hopes for DDG
I lost my hopes for DDG

So Meta uses Bing for their AI or for Metas Ai to search. I was searching on IG for a tag I know exists from someone I was friends with. IG meta kept giving me the run around and not letting me see it. So I hit the bing search button, popped in the tag with the hash and tried it with Instagram and IG before and after the tag. Each time pulling up 5 pages of 6 results.. Which the words in the tags would have brought up way more than that….. But never showed the actual tag I was searching for.

Drop into safari, DDG is my search engine for private and reg, do the exact same searches…. Get basically identical results.. still no match to the actual tag….

Tried google from safari, it was the third result…. Tried orion which I use startpage, second result…

Find out the person blocked me, which I had someone expected, but I wanted to test out how secure DDG was ever since they started binging…….



How much of your digital footprint do your photos reveal? How much of your digital footprint do your photos reveal?
Privacy

Unfortunately I’ve been thinking about how much of our online presence exists outside the platforms we actively use. Out of curiosity, I tried a face search tool (FaceFinderAI) with one of my public photos to see what might show up. The results weren’t extreme, but they did surface a few places I hadn’t really considered, which made me reflect on how long images can circulate once they’re online. It got me wondering how aware people are of their photo footprint. Have you ever looked into where your images appear online? Do you actively try to manage that, or is it something you don’t worry about much?