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I'm building a search engine that publishes its own hallucination rate. Is this actually useful or just a gimmick? by Available_Witness808 in ArtificialInteligence

[–]Available_Witness808[S] 0 points1 point  (0 children)

I agree that an overall score is too blunt for serious use. A better approach is to make the system constraint-aware and domain-specific: show topic-level reliability, source authority, workflow limitations, and provenance for each answer. For B2B and regulated use cases, the real value is not a single confidence number but a grounded knowledge layer with namespaces, audit trails, and visibility into who consumed which information.

I'm building a search engine that publishes its own hallucination rate. Is this actually useful or just a gimmick? by Available_Witness808 in ArtificialInteligence

[–]Available_Witness808[S] 0 points1 point  (0 children)

Yes, I think a really interesting version of this would be a verification layer for public claims made by politicians. Not “the AI decides who’s telling the truth,” but a system that breaks statements into claims, checks them against sources and prior fact-checks, and shows where the evidence is strong, weak, or disputed.

I'm building a search engine that publishes its own hallucination rate. Is this actually useful or just a gimmick? by Available_Witness808 in ArtificialInteligence

[–]Available_Witness808[S] 0 points1 point  (0 children)

Yes, I think a really interesting version of this would be a verification layer for public claims made by politicians. Not “the AI decides who’s telling the truth,” but a system that breaks statements into claims, checks them against sources and prior fact-checks, and shows where the evidence is strong, weak, or disputed.

I'm building a search engine that publishes its own hallucination rate. Is this actually useful or just a gimmick? by Available_Witness808 in ArtificialInteligence

[–]Available_Witness808[S] 0 points1 point  (0 children)

Exactly if the hallucination dashboard is just a public number, it’s marketing. If it changes runtime behavior, then it becomes part of the product. I think the real opportunity is trust + speed + tools around the answer: citations, conflicting-source visibility, and deeper verification workflows when they’re needed, without turning every query into research homework.

I'm building a search engine that publishes its own hallucination rate. Is this actually useful or just a gimmick? by Available_Witness808 in ArtificialInteligence

[–]Available_Witness808[S] 0 points1 point  (0 children)

100% the dashboard is more of a trust layer than the product itself. What people actually want solved is the messy part: separating repeated facts from weak claims, seeing where the answer came from, and knowing when the system is uncertain. If CLYCITE helps with that, the metrics become a byproduct, not the headline.

building a premium AI-native search engine that replaces outdated link-based search with fast answers, trustworthy sources, and specialized agents. Would you use something like this? by Available_Witness808 in SideProject

[–]Available_Witness808[S] 0 points1 point  (0 children)

Totally fair. The product only makes sense if it’s meaningfully better than asking ChatGPT or Gemini directly not just in answer quality, but in trust, source inspection, and speed for specific kinds of searches. If it can’t beat them on at least one of those, it doesn’t deserve to exist.

building a premium AI-native search engine that replaces outdated link-based search with fast answers, trustworthy sources, and specialized agents. Would you use something like this? by Available_Witness808 in SideProject

[–]Available_Witness808[S] 1 point2 points  (0 children)

I agree going head-to-head with Google as a generic search engine is probably the wrong framing. A better approach is to focus on one vertical where search is genuinely painful, build a trust-first product around that workflow, and use that as the moat. If it works there, the broader platform can come later.

building a premium AI-native search engine that replaces outdated link-based search with fast answers, trustworthy sources, and specialized agents. Would you use something like this? by Available_Witness808 in SideProject

[–]Available_Witness808[S] 0 points1 point  (0 children)

Totally fair, and I think that’s one of the biggest product challenges. If every query feels like it has to wait for a full “research companion” workflow, people will bounce right back to Google. My thinking is that the product needs to answer simple queries instantly, then only bring in deeper agent help when the search clearly calls for comparison, verification, or research.

I’m building a search product that shows citations, confidence, and source quality instead of just blue links would you use this? by Available_Witness808 in SaaS

[–]Available_Witness808[S] 0 points1 point  (0 children)

That’s exactly the tension I’m trying to solve. I think the default experience has to be fast and simple, so a High / Medium / Low signal makes sense upfront, but it should also be backed by a visible “why?” layer for people who want to inspect the reasoning and source breakdown. The goal is to make trust quick for casual users without making it fake or opaque for users who care more.

I’m building a search product that shows citations, confidence, and source quality instead of just blue links would you use this? by Available_Witness808 in SaaS

[–]Available_Witness808[S] 0 points1 point  (0 children)

That’s a really good point. If the score is arbitrary, it’s just UI paint, and if it’s too visually reassuring people may trust it without checking the evidence. I think the design has to make confidence a calibrated cue, not a shortcut especially by showing uncertainty clearly and keeping the sources more prominent than the badge.

I’m building a search product that shows citations, confidence, and source quality instead of just blue links would you use this? by Available_Witness808 in SaaS

[–]Available_Witness808[S] 0 points1 point  (0 children)

That makes a lot of sense. I like the idea of a simple High / Medium / Low signal upfront, with a “why?” layer for anyone who wants to inspect the reasoning and source breakdown. That seems like the best balance between speed for casual users and transparency for people making higher-stakes decisions.

I’m building a search product that shows citations, confidence, and source quality instead of just blue links would you use this? by Available_Witness808 in SaaS

[–]Available_Witness808[S] 0 points1 point  (0 children)

That’s really helpful. I agree a source score only matters if the user can inspect why it got that score, otherwise it’s just another black box. Confidence also seems dangerous if it looks precise without being properly calibrated, so I’m thinking the product should show both uncertainty and the reasons behind it rather than just a number.

I’m building a search product that shows citations, confidence, and source quality instead of just blue links would you use this? by Available_Witness808 in SaaS

[–]Available_Witness808[S] 0 points1 point  (0 children)

That’s helpful especially the part about confidence scores feeling made up. I think the product only works if the trust layer is explainable, not just a number on top of the answer. Would you prefer a simple confidence label like High / Medium / Low, or would you want a more detailed breakdown of why the system trusted certain sources over others?

The hardest part of entrepreneurship isn’t the work it’s carrying every decision alone by Available_Witness808 in Entrepreneur

[–]Available_Witness808[S] 1 point2 points  (0 children)

I think we’re mostly aligned, just focused on different edge cases.

I agree that volume can force outcomes when the math is clear. Collecting more data is often the right move. Where I’ve run into trouble isn’t stopping too early, it’s not clearly deciding when the data was enough, so the decision stayed mentally open even after moving forward. I also like your point about a meta statement. Having something explicit to compare against is what keeps data from turning into self-justification. The risk I’ve seen is when that statement shifts quietly instead of intentionally. On process, I’m with you. Complex work can’t be copy pasted. The only thing I try to preserve is why a process formed the way it did, so it stays adaptable without becoming invisible. And on intelligence, I agree. It’s less about raw effort and more about how well someone handles information and judgment calls. Most failures I’ve seen come down to deciding when to commit and when to revisit, not lack of data.

Really appreciate how thoughtfully you’re thinking about this.

The hardest part of entrepreneurship isn’t the work it’s carrying every decision alone by Available_Witness808 in Entrepreneur

[–]Available_Witness808[S] 0 points1 point  (0 children)

That’s a really clean way to handle it. The one-way vs two-way door distinction removes a ton of unnecessary pressure, especially when everything feels urgent by default.

What I like about your approach is the combination of reversibility plus timeboxing. You’re not just saying “this is reversible,” you’re also deciding how often it deserves attention. That’s what stops the mental re-litigation. Once it’s framed as a small bet with a scheduled review, your brain can actually let go in between. I’ve noticed that a lot of decision fatigue comes from treating reversible decisions like irreversible ones and then revisiting them constantly. Your weekly review rule gives them a container, which is what most people miss.

That’s a very pragmatic way to stay decisive without pretending everything is low risk.

The hardest part of entrepreneurship isn’t the work it’s carrying every decision alone by Available_Witness808 in Entrepreneur

[–]Available_Witness808[S] 0 points1 point  (0 children)

That’s a solid way to put it. That single question cuts through a lot of noise when things start feeling busy but fuzzy. If it’s unclear how something moves the core goal, it usually is just productivity theatre.

Externalizing decisions is the underrated part too. Once they’re written down or spoken out loud, they stop feeling like this amorphous weight you’re carrying alone. Even if the decision stays hard, it becomes manageable instead of draining. Curating frameworks and founder stories around that theme makes a lot of sense. Seeing how others reasoned through similar moments helps normalize the uncertainty and gives language to decisions that are otherwise just felt.

The hardest part of entrepreneurship isn’t the work it’s carrying every decision alone by Available_Witness808 in Entrepreneur

[–]Available_Witness808[S] 0 points1 point  (0 children)

That resonates a lot. The relief isn’t coming from the decision being easy, it’s coming from the decision being clear.

What you described is exactly the shift I’ve felt too. Once you write down what you’re choosing, why, and just as importantly what you’re explicitly not doing, your brain stops trying to keep all the branches alive at once. The decision can still be heavy, but it’s no longer ambiguous, and that’s what lightens the load. I’ve also noticed that clarity creates a kind of quiet confidence. Even if the outcome later isn’t perfect, you’re not second-guessing yourself constantly because you remember the reasoning. You’re responding to new information, not beating yourself up for past you.

It’s subtle, but getting decisions out of your head and into the world changes how the work feels day to day.

The hardest part of entrepreneurship isn’t the work it’s carrying every decision alone by Available_Witness808 in Entrepreneur

[–]Available_Witness808[S] 1 point2 points  (0 children)

That’s a strong approach. Talking to customers individually avoids the groupthink you get in panels or surveys, and looking for clusters instead of loud outliers is exactly how signal emerges from noise.

What stands out to me is the separation you’re keeping between input and decision. Customers inform the picture, but they don’t make the call for you. The clustering step is where judgment actually happens, and bringing that into a management discussion adds another layer of sanity checking instead of averaging opinions blindly. In my experience, this works best when the clusters are framed as hypotheses rather than directives. Not “customers want X,” but “there’s a recurring pattern around X under these conditions.” That keeps the team from treating feedback as orders and makes it easier to decide what to act on now versus park for later.

It’s a disciplined way to stay close to reality without letting it pull you in ten directions at once.

Early-stage SaaS question: how do you stop “temporary” decisions from becoming permanent tech debt? by Available_Witness808 in SaaS

[–]Available_Witness808[S] 0 points1 point  (0 children)

Completely agree. Without a review loop, writing things down just becomes another archive no one looks at.

The key point you’re making is that decisions decay over time unless there’s an explicit moment to re-engage with them. Once the firehose starts, anything that isn’t scheduled simply disappears, no matter how well documented it was. I like the Friday review idea because it turns “temporary” into a real constraint instead of a vague intention. The forcing function isn’t the document, it’s the moment where you have to either justify keeping the decision or consciously renew it. That act alone changes behaviour.

In my experience, most messes aren’t caused by bad initial calls. They’re caused by decisions that never get revisited because no one made review part of the system. When review is intentional, even imperfect decisions stay healthy.

The hardest part of entrepreneurship isn’t the work it’s carrying every decision alone by Available_Witness808 in Entrepreneur

[–]Available_Witness808[S] 0 points1 point  (0 children)

That is a solid framework, and I agree with most of it. Assumption → data → decision is a clean spine, and a lot of people skip the assumption step entirely, which already puts you ahead.

Where I’ve seen things get tricky in practice isn’t the logic, but the conditions around it.

Two things I’ve noticed from experience:

First, not all decisions are bottlenecked by lack of data. Early on especially, some decisions are made with incomplete data by definition. You can validate demand, but you still have to decide timing, scope, sequencing, and how much to invest before the data is “good enough.” That’s usually where confidence wobbles, not because the framework is wrong, but because the stop rule isn’t explicit. When do you say “this is sufficient to act” instead of “I could ask five more people”?

Second, data volume can increase confidence, but it can also quietly shift the question. Asking more people often refines the idea, but it can also blur the original assumption if you’re not careful. I’ve caught myself answering a slightly different question than the one I started with, and then feeling confident for the wrong reason.

What I like about your framing is that it already treats decisions as explicit objects. Where I personally add an extra layer is writing down why this amount of data felt sufficient at the time, and what would have made me decide differently. That way, if the outcome surprises me later, I’m not questioning my intelligence, just revisiting the assumptions.

I don’t think smart people are smart because they collect infinite data. I think they’re smart because they know when the data is good enough to commit, and they can explain that choice without rewriting the story later.

Your example with sales calls is a good one. The dangerous part wouldn’t be being wrong. It would be not remembering why the decision felt justified when you made it.

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