Don’t you think we all deserve a better search?
Lacey Miller
Apr 17, 2025
OVERVIEW
SUMMARY
This conversation explores a critique of traditional search engines, particularly Google, and presents an alternative called Perigon that aims to provide more precise and actionable intelligence for professionals. The key points discussed include: Search engines have prioritized speed and monetization over relevance, leading to results that are often skewed by advertisements rather than the most relevant information. Perigon is positioned as a fundamentally different approach that encourages users to ask more detailed, specific queries (around 15 words on average) and delivers results that are structured for analysis rather than just browsing. Perigon's "intelligence engine" utilizes advanced techniques like sentiment analysis, entity resolution, and content labeling to provide deeper insights and separate facts from opinions.
0:00/1:34
SUMMARY
This conversation explores a critique of traditional search engines, particularly Google, and presents an alternative called Perigon that aims to provide more precise and actionable intelligence for professionals. The key points discussed include: Search engines have prioritized speed and monetization over relevance, leading to results that are often skewed by advertisements rather than the most relevant information. Perigon is positioned as a fundamentally different approach that encourages users to ask more detailed, specific queries (around 15 words on average) and delivers results that are structured for analysis rather than just browsing. Perigon's "intelligence engine" utilizes advanced techniques like sentiment analysis, entity resolution, and content labeling to provide deeper insights and separate facts from opinions.
0:00/1:34
SUMMARY
This conversation explores a critique of traditional search engines, particularly Google, and presents an alternative called Perigon that aims to provide more precise and actionable intelligence for professionals. The key points discussed include: Search engines have prioritized speed and monetization over relevance, leading to results that are often skewed by advertisements rather than the most relevant information. Perigon is positioned as a fundamentally different approach that encourages users to ask more detailed, specific queries (around 15 words on average) and delivers results that are structured for analysis rather than just browsing. Perigon's "intelligence engine" utilizes advanced techniques like sentiment analysis, entity resolution, and content labeling to provide deeper insights and separate facts from opinions.
0:00/1:34
What is the fundamental difference in the approach to search between traditional engines and Perigon?
What is the fundamental difference in the approach to search between traditional engines and Perigon?
What is the fundamental difference in the approach to search between traditional engines and Perigon?
How does Perigon enrich its search results beyond simply indexing the open web?
How does Perigon enrich its search results beyond simply indexing the open web?
How does Perigon enrich its search results beyond simply indexing the open web?
What type of user or use case is Perigon designed for, and why is the traditional search model insufficient for them?
What type of user or use case is Perigon designed for, and why is the traditional search model insufficient for them?
What type of user or use case is Perigon designed for, and why is the traditional search model insufficient for them?
TRANSCRIPT (FOR THE ROBOTS)
Aimee: Welcome to the deep dive. You're here because, well, you want to get smart on what matters fast and cut through all the noise. We love those aha moments, but without feeling totally overwhelmed.
Craig: Exactly.
Aimee: So today we're diving into something we literally do every day searching for information online. We'll look at how it's changed, maybe not always for the better and explore a pretty fascinating alternative.
Craig: And the source we're drawing from is this piece: “Don't you think we all deserve a better search?”
Aimee: Yeah.
Craig: It really lays out a strong case.
Aimee: It does
Craig: A critique of current search and this vision for something quite different. So our mission today really is to unpack that, figure out what it means for professionals who need accuracy and understand this potential alternative.
Aimee: Okay. Let’s get into it. Then the article, it doesn't pull any punches, does it? Starts right off with a big claim. That search, especially Google has lost its way.
Craig: It suggests the priorities have shifted away from just finding the best information.
Aimee: Right. And a key point seems to be that relevance isn't really driving things anymore. Is that the idea?
Craig: That's the core argument, and what's interesting is they suggest this wasn't just like an accident. The argument is that search engines have sort of trained us.
Aimee: Trained us how?
Craig: To use these really short queries, like three words, maybe four. Think about how often we do that.
Aimee: That's true.
Craig: Guilty is charged, but that kind of brevity, it naturally limits how precise you can be. Right? It's almost like we've been conditioned to ask for less
Aimee: And the article connects that directly to how these platforms make money.
Craig: Exactly. Those short queries, they lead you to results. Where the top spots aren't always the most relevant answer. Often they're ads.
Aimee: The line that jumped out at me was, page one isn't relevant. It's a marketplace.
Craig: That sums it up pretty well, doesn't it?
Aimee: It really does. It makes you question, okay, is this top result the best information or just the one that well paid the most,
Craig: Which leads to a really critical point. The article raises who does this system actually serve?
Aimee: Right.
Craig: Maybe it's fine if you're just looking for, I don't know, a pizza place nearby. Quick and easy.
Aimee: Sure.
Craig: But for professionals, people doing serious market research, product development, financial analysis, relying on results, potentially skewed by ads. The article calls it intellectual malpractice. Pretty strong words.
Aimee: Wow. Yeah, intellectual malpractice. That definitely sets the stage for talking about this alternative Perigon. Their core idea, and I kind of like this, is you're smarter than Google thinks you are.
Craig: It's a direct pushback, isn't it?
Aimee: Yeah. Against that idea that we should just stick to these super simple searches. So how do they actually put that into practice? What's different?
Craig: Well, one really telling stat they mention is the average length of a user query on their platform. It's around 15 words,
Aimee: 15, compared to our usual three or four.
Craig: Exactly. That immediately signals something fundamentally different is happening. Users are encouraged, expected even to be much more specific to add context.
Aimee: It's about demanding more precise results, I guess.
Craig: Precisely. You're giving the system more to work with.
Aimee: The article had that great comparison, like the typical search crypto market trend. Very broad.
Craig: Yeah. You can just imagine the results, right? General news, maybe some sponsored stuff. SEO heavy content…
Aimee: Probably lots of ads. Then they contrast it with the Perigon style negative sentiment indicators for cryptocurrency adoption in institutional banking sector Q1 2025. Whoa.
Craig: Okay. That's specific,
Aimee: Right? The difference in precision is huge
Craig: And so are the expected results. The short query gives you surface level stuff, the long one that's designed to pull out what they call “actionable intelligence”.
Aimee: Actionable intelligence…meaning
Craig: Meaning detailed context, rich information that a professional analyst or strategist can actually use to make informed decisions, not just read a headline.
Aimee: Okay, so Perigon isn't just a slightly better search bar. It's built differently from the ground up. This “intelligence engine” they talk about.
Craig: Yeah, it sounds like it goes way beyond just indexing webpages like traditional search.
Aimee: So what's under the hood? What makes this engine different?
Craig: Well, they talk about these layers of intelligence. One is full sentiment vectors,
Aimee: Sentiment vectors sounds complex.
Craig: Think of it like understanding not just if something is positive or negative, but the nuance and intensity. Is it mildly critical or strongly disapproving? Is there sarcasm? It goes beyond simple keyword spotting.
Aimee: Okay, so deeper emotional understanding of the text. What else?
Craig: Then there's entity resolution. This is really smart. It's about the system understanding that say Elon Musk, the CEO of Tesla and the guy behind SpaceX are all referring to the same person.
Aimee: Ah. Connecting the dots between different names and titles for the same thing or person.
Craig: Exactly. Even if those specific phrases aren't used together in the text, it builds a much richer context.
Aimee: That's definitely more sophisticated than just matching keywords. And there was more too, right? Something about tagging and labeling,
Craig: Right? Topic tagging—that's more nuanced than basic keywords and content labeling. This tells you what you're looking at. Is it an opinion piece? Is it a fact-check article? Is it original report?
Aimee: So it helps you sort the information by its nature, not just its topic. That sounds incredibly useful.
Craig: It does. It gives you a much clearer picture. Then there are the AI-generated insight capsules.
Aimee: Insight capsules…
Craig: Yeah. Basically AI summaries that distill complex information. Maybe identify key themes or trends across multiple documents for you. Saves a ton of reading time potentially.
Aimee: So the articles claim that this is search reimagined from the ground up. It sounds like they might have a point. It's not just a tweak.
Craig: It really seems like a fundamental rethink. The whole goal appears different.
Aimee: Which brings us back to that contrast. Traditional search seems geared towards the fastest answer or an answer quickly.
Craig: Get something in front of you fast…
Aimee: Whereas Perigon seems focused on the right answer, the most relevant answer, even if it requires a bit more thought in the query upfront.
Craig: Exactly. It's a shift from prioritizing speed to prioritizing accuracy and depth, which makes sense for professionals, right?
Aimee: Absolutely. Because the questions they need answers to are rarely simple.
Craig: They go beyond just what are people saying. That's maybe step one. The real value comes from asking, okay, who is actually driving this narrative? Or how has this sentiment on this specific issue changed over the last quarter?
Aimee: Or even what part of this information is actual fact? What's just knee jerk reaction and what's basically recycled content?
Craig: Those are the questions that give you real competitive intelligence, understanding the dynamics underneath the surface noise.
Aimee: That's crucial in so many fields. Staying ahead, understanding the market.
Craig: So the article gives this concrete example query. Let's say you need info on negatively reported cyber attacks, targeting infrastructure specifically in the energy sector. And crucially, you want to exclude opinion pieces.
Aimee: Okay, that's a complex need. How would you normally even try that? Lots of keyword attempts, maybe using minus signs.
Craig: Probably and a lot of manual filtering afterwards. But the Perigon example query looks like code almost cyber attack and infrastructure and category energy and sentiment negative and labels opinion.
Aimee: Wow. Okay. You can immediately see how much more targeted that is. You're telling it exactly what you want and what you don't want.
Craig: Exactly. And the key is what this delivers. It's not just a list of links that happen to contain those words.
Aimee: Right? What's different about the output?
Craig: They say the results are clustered by narrative coherence. So documents telling a similar story are grouped together and facts are clearly separated from opinions because of that labeling.
Aimee: So it's structured for analysis, not just browsing.
Craig: That's the idea. It's designed to give you that actional intelligence. We talked about directly addressing your specific complex question.
Aimee: So boiling it down, the core argument we've been exploring is that traditional search as it stands might actually be insufficient, maybe even harmful for serious decision-making
Craig: If accuracy and nuance are critical. Yeah. Relying on a system potentially optimized for ads over relevance could lead you astray. That's the warning.
Aimee: And Perigon is positioned as this alternative that well respects your intelligence, gives you the tools for precision.
Craig: It's framed almost like a declaration of independence from a broken model. That's pretty bold framing.
Aimee: Yeah. Search that serves you not the other way around.
Craig: And that final line from the article really sticks with you from manipulation to revelation, one intelligent query at a time.
Aimee: It sums up that whole proposed shift from maybe being passively fed results to actively seeking understanding.
Craig: So just to recap quickly, we've unpacked this critique of mainstream search. The idea that monetization might've nudged, relevance aside, maybe even trained us for simpler searches.
Aimee: The marketplace idea.
Craig: And then we contrasted that with Perigon's approach, emphasizing precision, longer queries context.
Aimee: And using that intelligence engine with things like sentiment analysis, entity resolution, content labeling
Craig: To deliver deeper insights. That actionable intelligence, especially for professionals who need more than just surface level answers. It's about empowering the user.
Aimee: It definitely leaves you thinking differently about hitting that search button doesn't?
Craig: It does.
Aimee: In this absolute flood of information we live in, what does it actually mean to search intelligently? Maybe our expectations need to shift.
Craig: Maybe we need to demand more from our search tools.
Aimee: Yeah. Moving beyond just wanting the quickest answer to seeking the most insightful one. It's certainly food for thought. How could a more deliberate, maybe more demanding approach to finding information change how you work or how you understand what's going on in the world. Something to mull over.
TRANSCRIPT (FOR THE ROBOTS)
Aimee: Welcome to the deep dive. You're here because, well, you want to get smart on what matters fast and cut through all the noise. We love those aha moments, but without feeling totally overwhelmed.
Craig: Exactly.
Aimee: So today we're diving into something we literally do every day searching for information online. We'll look at how it's changed, maybe not always for the better and explore a pretty fascinating alternative.
Craig: And the source we're drawing from is this piece: “Don't you think we all deserve a better search?”
Aimee: Yeah.
Craig: It really lays out a strong case.
Aimee: It does
Craig: A critique of current search and this vision for something quite different. So our mission today really is to unpack that, figure out what it means for professionals who need accuracy and understand this potential alternative.
Aimee: Okay. Let’s get into it. Then the article, it doesn't pull any punches, does it? Starts right off with a big claim. That search, especially Google has lost its way.
Craig: It suggests the priorities have shifted away from just finding the best information.
Aimee: Right. And a key point seems to be that relevance isn't really driving things anymore. Is that the idea?
Craig: That's the core argument, and what's interesting is they suggest this wasn't just like an accident. The argument is that search engines have sort of trained us.
Aimee: Trained us how?
Craig: To use these really short queries, like three words, maybe four. Think about how often we do that.
Aimee: That's true.
Craig: Guilty is charged, but that kind of brevity, it naturally limits how precise you can be. Right? It's almost like we've been conditioned to ask for less
Aimee: And the article connects that directly to how these platforms make money.
Craig: Exactly. Those short queries, they lead you to results. Where the top spots aren't always the most relevant answer. Often they're ads.
Aimee: The line that jumped out at me was, page one isn't relevant. It's a marketplace.
Craig: That sums it up pretty well, doesn't it?
Aimee: It really does. It makes you question, okay, is this top result the best information or just the one that well paid the most,
Craig: Which leads to a really critical point. The article raises who does this system actually serve?
Aimee: Right.
Craig: Maybe it's fine if you're just looking for, I don't know, a pizza place nearby. Quick and easy.
Aimee: Sure.
Craig: But for professionals, people doing serious market research, product development, financial analysis, relying on results, potentially skewed by ads. The article calls it intellectual malpractice. Pretty strong words.
Aimee: Wow. Yeah, intellectual malpractice. That definitely sets the stage for talking about this alternative Perigon. Their core idea, and I kind of like this, is you're smarter than Google thinks you are.
Craig: It's a direct pushback, isn't it?
Aimee: Yeah. Against that idea that we should just stick to these super simple searches. So how do they actually put that into practice? What's different?
Craig: Well, one really telling stat they mention is the average length of a user query on their platform. It's around 15 words,
Aimee: 15, compared to our usual three or four.
Craig: Exactly. That immediately signals something fundamentally different is happening. Users are encouraged, expected even to be much more specific to add context.
Aimee: It's about demanding more precise results, I guess.
Craig: Precisely. You're giving the system more to work with.
Aimee: The article had that great comparison, like the typical search crypto market trend. Very broad.
Craig: Yeah. You can just imagine the results, right? General news, maybe some sponsored stuff. SEO heavy content…
Aimee: Probably lots of ads. Then they contrast it with the Perigon style negative sentiment indicators for cryptocurrency adoption in institutional banking sector Q1 2025. Whoa.
Craig: Okay. That's specific,
Aimee: Right? The difference in precision is huge
Craig: And so are the expected results. The short query gives you surface level stuff, the long one that's designed to pull out what they call “actionable intelligence”.
Aimee: Actionable intelligence…meaning
Craig: Meaning detailed context, rich information that a professional analyst or strategist can actually use to make informed decisions, not just read a headline.
Aimee: Okay, so Perigon isn't just a slightly better search bar. It's built differently from the ground up. This “intelligence engine” they talk about.
Craig: Yeah, it sounds like it goes way beyond just indexing webpages like traditional search.
Aimee: So what's under the hood? What makes this engine different?
Craig: Well, they talk about these layers of intelligence. One is full sentiment vectors,
Aimee: Sentiment vectors sounds complex.
Craig: Think of it like understanding not just if something is positive or negative, but the nuance and intensity. Is it mildly critical or strongly disapproving? Is there sarcasm? It goes beyond simple keyword spotting.
Aimee: Okay, so deeper emotional understanding of the text. What else?
Craig: Then there's entity resolution. This is really smart. It's about the system understanding that say Elon Musk, the CEO of Tesla and the guy behind SpaceX are all referring to the same person.
Aimee: Ah. Connecting the dots between different names and titles for the same thing or person.
Craig: Exactly. Even if those specific phrases aren't used together in the text, it builds a much richer context.
Aimee: That's definitely more sophisticated than just matching keywords. And there was more too, right? Something about tagging and labeling,
Craig: Right? Topic tagging—that's more nuanced than basic keywords and content labeling. This tells you what you're looking at. Is it an opinion piece? Is it a fact-check article? Is it original report?
Aimee: So it helps you sort the information by its nature, not just its topic. That sounds incredibly useful.
Craig: It does. It gives you a much clearer picture. Then there are the AI-generated insight capsules.
Aimee: Insight capsules…
Craig: Yeah. Basically AI summaries that distill complex information. Maybe identify key themes or trends across multiple documents for you. Saves a ton of reading time potentially.
Aimee: So the articles claim that this is search reimagined from the ground up. It sounds like they might have a point. It's not just a tweak.
Craig: It really seems like a fundamental rethink. The whole goal appears different.
Aimee: Which brings us back to that contrast. Traditional search seems geared towards the fastest answer or an answer quickly.
Craig: Get something in front of you fast…
Aimee: Whereas Perigon seems focused on the right answer, the most relevant answer, even if it requires a bit more thought in the query upfront.
Craig: Exactly. It's a shift from prioritizing speed to prioritizing accuracy and depth, which makes sense for professionals, right?
Aimee: Absolutely. Because the questions they need answers to are rarely simple.
Craig: They go beyond just what are people saying. That's maybe step one. The real value comes from asking, okay, who is actually driving this narrative? Or how has this sentiment on this specific issue changed over the last quarter?
Aimee: Or even what part of this information is actual fact? What's just knee jerk reaction and what's basically recycled content?
Craig: Those are the questions that give you real competitive intelligence, understanding the dynamics underneath the surface noise.
Aimee: That's crucial in so many fields. Staying ahead, understanding the market.
Craig: So the article gives this concrete example query. Let's say you need info on negatively reported cyber attacks, targeting infrastructure specifically in the energy sector. And crucially, you want to exclude opinion pieces.
Aimee: Okay, that's a complex need. How would you normally even try that? Lots of keyword attempts, maybe using minus signs.
Craig: Probably and a lot of manual filtering afterwards. But the Perigon example query looks like code almost cyber attack and infrastructure and category energy and sentiment negative and labels opinion.
Aimee: Wow. Okay. You can immediately see how much more targeted that is. You're telling it exactly what you want and what you don't want.
Craig: Exactly. And the key is what this delivers. It's not just a list of links that happen to contain those words.
Aimee: Right? What's different about the output?
Craig: They say the results are clustered by narrative coherence. So documents telling a similar story are grouped together and facts are clearly separated from opinions because of that labeling.
Aimee: So it's structured for analysis, not just browsing.
Craig: That's the idea. It's designed to give you that actional intelligence. We talked about directly addressing your specific complex question.
Aimee: So boiling it down, the core argument we've been exploring is that traditional search as it stands might actually be insufficient, maybe even harmful for serious decision-making
Craig: If accuracy and nuance are critical. Yeah. Relying on a system potentially optimized for ads over relevance could lead you astray. That's the warning.
Aimee: And Perigon is positioned as this alternative that well respects your intelligence, gives you the tools for precision.
Craig: It's framed almost like a declaration of independence from a broken model. That's pretty bold framing.
Aimee: Yeah. Search that serves you not the other way around.
Craig: And that final line from the article really sticks with you from manipulation to revelation, one intelligent query at a time.
Aimee: It sums up that whole proposed shift from maybe being passively fed results to actively seeking understanding.
Craig: So just to recap quickly, we've unpacked this critique of mainstream search. The idea that monetization might've nudged, relevance aside, maybe even trained us for simpler searches.
Aimee: The marketplace idea.
Craig: And then we contrasted that with Perigon's approach, emphasizing precision, longer queries context.
Aimee: And using that intelligence engine with things like sentiment analysis, entity resolution, content labeling
Craig: To deliver deeper insights. That actionable intelligence, especially for professionals who need more than just surface level answers. It's about empowering the user.
Aimee: It definitely leaves you thinking differently about hitting that search button doesn't?
Craig: It does.
Aimee: In this absolute flood of information we live in, what does it actually mean to search intelligently? Maybe our expectations need to shift.
Craig: Maybe we need to demand more from our search tools.
Aimee: Yeah. Moving beyond just wanting the quickest answer to seeking the most insightful one. It's certainly food for thought. How could a more deliberate, maybe more demanding approach to finding information change how you work or how you understand what's going on in the world. Something to mull over.
TRANSCRIPT (FOR THE ROBOTS)
Aimee: Welcome to the deep dive. You're here because, well, you want to get smart on what matters fast and cut through all the noise. We love those aha moments, but without feeling totally overwhelmed.
Craig: Exactly.
Aimee: So today we're diving into something we literally do every day searching for information online. We'll look at how it's changed, maybe not always for the better and explore a pretty fascinating alternative.
Craig: And the source we're drawing from is this piece: “Don't you think we all deserve a better search?”
Aimee: Yeah.
Craig: It really lays out a strong case.
Aimee: It does
Craig: A critique of current search and this vision for something quite different. So our mission today really is to unpack that, figure out what it means for professionals who need accuracy and understand this potential alternative.
Aimee: Okay. Let’s get into it. Then the article, it doesn't pull any punches, does it? Starts right off with a big claim. That search, especially Google has lost its way.
Craig: It suggests the priorities have shifted away from just finding the best information.
Aimee: Right. And a key point seems to be that relevance isn't really driving things anymore. Is that the idea?
Craig: That's the core argument, and what's interesting is they suggest this wasn't just like an accident. The argument is that search engines have sort of trained us.
Aimee: Trained us how?
Craig: To use these really short queries, like three words, maybe four. Think about how often we do that.
Aimee: That's true.
Craig: Guilty is charged, but that kind of brevity, it naturally limits how precise you can be. Right? It's almost like we've been conditioned to ask for less
Aimee: And the article connects that directly to how these platforms make money.
Craig: Exactly. Those short queries, they lead you to results. Where the top spots aren't always the most relevant answer. Often they're ads.
Aimee: The line that jumped out at me was, page one isn't relevant. It's a marketplace.
Craig: That sums it up pretty well, doesn't it?
Aimee: It really does. It makes you question, okay, is this top result the best information or just the one that well paid the most,
Craig: Which leads to a really critical point. The article raises who does this system actually serve?
Aimee: Right.
Craig: Maybe it's fine if you're just looking for, I don't know, a pizza place nearby. Quick and easy.
Aimee: Sure.
Craig: But for professionals, people doing serious market research, product development, financial analysis, relying on results, potentially skewed by ads. The article calls it intellectual malpractice. Pretty strong words.
Aimee: Wow. Yeah, intellectual malpractice. That definitely sets the stage for talking about this alternative Perigon. Their core idea, and I kind of like this, is you're smarter than Google thinks you are.
Craig: It's a direct pushback, isn't it?
Aimee: Yeah. Against that idea that we should just stick to these super simple searches. So how do they actually put that into practice? What's different?
Craig: Well, one really telling stat they mention is the average length of a user query on their platform. It's around 15 words,
Aimee: 15, compared to our usual three or four.
Craig: Exactly. That immediately signals something fundamentally different is happening. Users are encouraged, expected even to be much more specific to add context.
Aimee: It's about demanding more precise results, I guess.
Craig: Precisely. You're giving the system more to work with.
Aimee: The article had that great comparison, like the typical search crypto market trend. Very broad.
Craig: Yeah. You can just imagine the results, right? General news, maybe some sponsored stuff. SEO heavy content…
Aimee: Probably lots of ads. Then they contrast it with the Perigon style negative sentiment indicators for cryptocurrency adoption in institutional banking sector Q1 2025. Whoa.
Craig: Okay. That's specific,
Aimee: Right? The difference in precision is huge
Craig: And so are the expected results. The short query gives you surface level stuff, the long one that's designed to pull out what they call “actionable intelligence”.
Aimee: Actionable intelligence…meaning
Craig: Meaning detailed context, rich information that a professional analyst or strategist can actually use to make informed decisions, not just read a headline.
Aimee: Okay, so Perigon isn't just a slightly better search bar. It's built differently from the ground up. This “intelligence engine” they talk about.
Craig: Yeah, it sounds like it goes way beyond just indexing webpages like traditional search.
Aimee: So what's under the hood? What makes this engine different?
Craig: Well, they talk about these layers of intelligence. One is full sentiment vectors,
Aimee: Sentiment vectors sounds complex.
Craig: Think of it like understanding not just if something is positive or negative, but the nuance and intensity. Is it mildly critical or strongly disapproving? Is there sarcasm? It goes beyond simple keyword spotting.
Aimee: Okay, so deeper emotional understanding of the text. What else?
Craig: Then there's entity resolution. This is really smart. It's about the system understanding that say Elon Musk, the CEO of Tesla and the guy behind SpaceX are all referring to the same person.
Aimee: Ah. Connecting the dots between different names and titles for the same thing or person.
Craig: Exactly. Even if those specific phrases aren't used together in the text, it builds a much richer context.
Aimee: That's definitely more sophisticated than just matching keywords. And there was more too, right? Something about tagging and labeling,
Craig: Right? Topic tagging—that's more nuanced than basic keywords and content labeling. This tells you what you're looking at. Is it an opinion piece? Is it a fact-check article? Is it original report?
Aimee: So it helps you sort the information by its nature, not just its topic. That sounds incredibly useful.
Craig: It does. It gives you a much clearer picture. Then there are the AI-generated insight capsules.
Aimee: Insight capsules…
Craig: Yeah. Basically AI summaries that distill complex information. Maybe identify key themes or trends across multiple documents for you. Saves a ton of reading time potentially.
Aimee: So the articles claim that this is search reimagined from the ground up. It sounds like they might have a point. It's not just a tweak.
Craig: It really seems like a fundamental rethink. The whole goal appears different.
Aimee: Which brings us back to that contrast. Traditional search seems geared towards the fastest answer or an answer quickly.
Craig: Get something in front of you fast…
Aimee: Whereas Perigon seems focused on the right answer, the most relevant answer, even if it requires a bit more thought in the query upfront.
Craig: Exactly. It's a shift from prioritizing speed to prioritizing accuracy and depth, which makes sense for professionals, right?
Aimee: Absolutely. Because the questions they need answers to are rarely simple.
Craig: They go beyond just what are people saying. That's maybe step one. The real value comes from asking, okay, who is actually driving this narrative? Or how has this sentiment on this specific issue changed over the last quarter?
Aimee: Or even what part of this information is actual fact? What's just knee jerk reaction and what's basically recycled content?
Craig: Those are the questions that give you real competitive intelligence, understanding the dynamics underneath the surface noise.
Aimee: That's crucial in so many fields. Staying ahead, understanding the market.
Craig: So the article gives this concrete example query. Let's say you need info on negatively reported cyber attacks, targeting infrastructure specifically in the energy sector. And crucially, you want to exclude opinion pieces.
Aimee: Okay, that's a complex need. How would you normally even try that? Lots of keyword attempts, maybe using minus signs.
Craig: Probably and a lot of manual filtering afterwards. But the Perigon example query looks like code almost cyber attack and infrastructure and category energy and sentiment negative and labels opinion.
Aimee: Wow. Okay. You can immediately see how much more targeted that is. You're telling it exactly what you want and what you don't want.
Craig: Exactly. And the key is what this delivers. It's not just a list of links that happen to contain those words.
Aimee: Right? What's different about the output?
Craig: They say the results are clustered by narrative coherence. So documents telling a similar story are grouped together and facts are clearly separated from opinions because of that labeling.
Aimee: So it's structured for analysis, not just browsing.
Craig: That's the idea. It's designed to give you that actional intelligence. We talked about directly addressing your specific complex question.
Aimee: So boiling it down, the core argument we've been exploring is that traditional search as it stands might actually be insufficient, maybe even harmful for serious decision-making
Craig: If accuracy and nuance are critical. Yeah. Relying on a system potentially optimized for ads over relevance could lead you astray. That's the warning.
Aimee: And Perigon is positioned as this alternative that well respects your intelligence, gives you the tools for precision.
Craig: It's framed almost like a declaration of independence from a broken model. That's pretty bold framing.
Aimee: Yeah. Search that serves you not the other way around.
Craig: And that final line from the article really sticks with you from manipulation to revelation, one intelligent query at a time.
Aimee: It sums up that whole proposed shift from maybe being passively fed results to actively seeking understanding.
Craig: So just to recap quickly, we've unpacked this critique of mainstream search. The idea that monetization might've nudged, relevance aside, maybe even trained us for simpler searches.
Aimee: The marketplace idea.
Craig: And then we contrasted that with Perigon's approach, emphasizing precision, longer queries context.
Aimee: And using that intelligence engine with things like sentiment analysis, entity resolution, content labeling
Craig: To deliver deeper insights. That actionable intelligence, especially for professionals who need more than just surface level answers. It's about empowering the user.
Aimee: It definitely leaves you thinking differently about hitting that search button doesn't?
Craig: It does.
Aimee: In this absolute flood of information we live in, what does it actually mean to search intelligently? Maybe our expectations need to shift.
Craig: Maybe we need to demand more from our search tools.
Aimee: Yeah. Moving beyond just wanting the quickest answer to seeking the most insightful one. It's certainly food for thought. How could a more deliberate, maybe more demanding approach to finding information change how you work or how you understand what's going on in the world. Something to mull over.
Let's be honest about what happened to search. Google didn't just break it—they murdered it. They methodically conditioned us to believe that fast responses and first-page results delivered the best, most relevant answers to our queries. But for anyone who needs accuracy, this model has become an intellectual dead end.
How We Got Manipulated
Remember when search was about finding the most relevant information? Those days vanished when search engines realized they could monetize our attention.
They systematically trained us like lab rats to accept that 3-word queries were acceptable ways to gather information. Meanwhile, they were force-feeding us ads cleverly disguised as "top results." The uncomfortable truth?
"The highest bidder is almost never the best answer. Page 1 isn't relevance—it's a marketplace."
For casual consumers looking for the nearest coffee shop, perhaps this model is sufficient. But for professionals whose decisions impact markets, products, and investments? It's intellectual malpractice.
"It's intellectual malpractice."
Breaking the Conditioning
At Perigon, we're built on a radical premise: you're smarter than Google thinks you are.
The average query in Perigon is 15 words because they understand that precision matters. They know that context creates value, not speed. They recognize that meaningful insights require nuanced questions.
When you've spent years submitting to the 3-word search paradigm, crafting a 15-word query feels revolutionary. It is. It's the difference between:
"crypto market trend"
And:
"negative sentiment indicators for cryptocurrency adoption in institutional banking sector Q1 2025"
One gives you ads and SEO-optimized blog posts. The other gives you actionable intelligence.
The Intelligence Engine, Not Just a Search Box
Perigon doesn't just index the open web; we enrich it with layers of intelligence:
Full sentiment vectors that reveal emotional currents beneath surface content
Entity resolution that connects people, companies, and concepts across disparate sources
Topic tagging that goes far beyond primitive keyword matching
Content labeling that differentiates between opinion, fact-checking, and reporting
AI-generated insight capsules that distill complex information patterns
This isn't just search enhanced. This is search reimagined from the ground up.
A Tool That Respects Your Intelligence
Traditional search engines assume you want the fastest answer. Perigon assumes you want the right answer.
With our approach, you can move beyond the basic question of "What are people saying?" to ask far more valuable questions:
Who's actually driving this narrative?
How has sentiment evolved over time on this issue?
What information is factual, what's reactive, and what's recycled?
These questions aren't just academic—they're the foundation of competitive intelligence for market researchers, product developers, financial analysts, and technology strategists.
Real-World Intelligence, Not Just Results
Consider this real application:
“What are recent negatively reported cyberattacks targeting infrastructure in the energy sector? Exclude opinion pieces”
Query:
This query doesn't just find content about cyberattacks. It delivers:
Results clustered by narrative coherence, not keyword density
Clear separation of fact from opinion
Delivery in a format designed for analysis, not just reading
The output isn't a list of links—it's actionable intelligence.
Reclaiming Search for the Intelligent
Search isn't dead, but Google's version of it is—at least for serious professionals who need more than ads and SEO-optimized content.
If you're done with a search tool that delivers more misinformation than revelation, Perigon offers an alternative based on a simple premise: we respect your intelligence.
In a world of complex challenges, 3-word queries and paid results aren't just insufficient—they're actively harmful to quality decision-making. The future of professional research requires tools built for insight, not just indexing.
Perigon isn't just a better search engine. It's a declaration of independence from a broken model that has degraded our ability to find truth in a sea of noise.
For researchers who refuse to be lab rats in an experiment designed to maximize ad revenue, Perigon offers something revolutionary: search that serves you, not the other way around.
From manipulation to revelation, one intelligent query at a time.
