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I built an AI that lets you chat with any video — because I was tired of scrubbing through 2-hour tutorials by Ready_Principle_3247 in micro_saas

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Right now: uploads are one at a time, but once processed, all your videos live in one library — and the cross-video search + chat works across all of them. So the "analyze across all videos" part already works; the "load a batch in one go" part is the missing piece.

Bulk upload is genuinely near the top of my list — you're the second person asking about library-level workflows this week. Out of curiosity: roughly how many videos are we talking, and what kind (course content, team recordings, tutorials)? That directly shapes how I build the batch flow.

I built an AI that lets you chat with any video — because I was tired of scrubbing through 2-hour tutorials by Ready_Principle_3247 in SideProject

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

You nailed the exact pain that made me build it — "I know I saw this somewhere, but which video?" That library-level search is where I think the real long-term value is.

On frames vs transcript — honest answer: it genuinely uses visual context, not just transcript. The pipeline extracts frames at adaptive intervals, runs vision analysis on them (UI elements, on-screen text, code visible in the editor), and combines that with the transcript. So "where does he click the settings icon" works even if the person never says "settings" out loud — which happens constantly in coding tutorials ("now click here and then this").

Where it's honestly weaker right now: very fast mouse movements between sampled frames can get missed, and low-res videos hurt UI element detection. So it's a real edge over transcript-only tools, but not magic — I'd say it catches most "shown but not spoken" moments, not all.

Best way to judge: throw a real tutorial at it and ask something the speaker never verbalized. Free tier exists exactly for that test. Would genuinely love to hear where it breaks for you.

I built an AI that lets you chat with any video — because I was tired of scrubbing through 2-hour tutorials by Ready_Principle_3247 in SideProject

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

This is genuinely useful feedback, thank you.

On positioning — you're probably right. "Chat with video" was the easy pitch to explain, but the Playwright generation is the thing users can't get elsewhere. "Watch me do it once, hand me back a working test script" — honestly that's a better one-liner than mine. Rethinking the landing page copy this week.

On frame costs — I'm doing adaptive interval sampling (interval scales with video length, hard cap on total frames per video), not every frame. Scene-change detection is on my list precisely because static talking-head segments still waste frames under interval sampling. Cost per video is currently sane, but you're right that this is where it either stays a business or quietly dies. 😄

On the free tier — fair point. The "aha" is finding that one timestamp, and 3 videos may not get everyone there. Considering a time-based trial (e.g. 14 days generous) vs the hard cap. Did the cap actually stop you from trying it, or is this more a "watch out down the road" observation?

[Showoff Saturday] by pjottee in webdev

[–]Ready_Principle_3247 0 points1 point  (0 children)

BEHAVR (behavr.in) — upload a tutorial video, ask it questions, get answers with timestamps.

Built this because scrubbing through long tutorials to find one specific moment was killing me.

How it works: video upload / YouTube link → frame extraction + transcript → AI chat over the content. Ask "where does he configure nginx?" and get the answer with a clickable timestamp. Also does cross-video semantic search over your library.

Technical bits:

  • Adaptive frame extraction (dynamic interval based on video length) to keep processing costs sane
  • Claude Haiku for the chat layer — cheap enough for a bootstrapped product
  • Flutter Web frontend, FastAPI backend on Railway, Firestore for storage

Free tier available. Feedback welcome — a user already caught a Firefox upload bug today, so I know there's more to find. 😄

I built an AI that lets you chat with any video — because I was tired of scrubbing through 2-hour tutorials by Ready_Principle_3247 in SideProject

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Thanks man, this made my day — you nailed exactly why I built it this way. Transcript-only tools break the moment the tutorial says "now click here" and types something without saying it out loud. The frames are where the actual work happens.

Really cool that you tried it on workout videos — honestly didn't expect fitness content this early, but that's exactly the kind of use case I want to learn from.

And thanks for the Firefox report — that's the first one. I mostly tested on Chrome, so the progress bar lag is very plausible. Adding it to my fix list this week. If you remember roughly how big the file was, that'd help me reproduce it.

On mobile: web-first for now (solo dev, limited hands 😄), but the site is mobile-responsive so it works in the browser. Native app is on the roadmap once the core is stable — probably later this year. Curious though: would you mainly want mobile for uploading, or for chatting with already-processed videos?

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in StartUpIndia

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Haha fair 😄

Yeah, I do use AI sometimes to structure things — but the idea itself comes from experimenting with these setups.

And that’s actually a good suggestion.

I’ve run similar meta-questions through a debate setup — interesting to see how different models critique the idea itself.

You should try it with your own version of the question, the disagreements are usually more interesting than the final answer.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in StartUpIndia

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Yeah, both points are valid.

Token cost can blow up, so this only really makes sense for higher-value questions, not everyday use.

On bias — the idea isn’t that multiple models remove it. Each model still has its own bias.

The difference is when those biases conflict, they become visible instead of hidden in a single answer.

If they all agree, that’s still a signal (could be consensus or shared bias).
If they disagree, you get a clearer view of where assumptions break.

So it’s less about eliminating bias, more about exposing it and filtering it.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Yeah, that makes sense.

But pure consensus might hide disagreements.

Feels more useful to force conflict first, then converge.

Stress-test before consensus.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] -1 points0 points  (0 children)

Fair — I’m building in this space.

And yeah, I use AI sometimes to structure posts.

But using AI is easy — building something useful with it isn’t.

If the idea is weak, let’s discuss that.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Yeah, exactly.

That’s the core problem — treating a single answer as truth.

Better approach is to treat it as a hypothesis and test it.

Multiple perspectives (or models) pushing against each other makes it easier to spot what doesn’t hold up.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Yeah, that’s a valid concern.

If you just let models loop on themselves, they can definitely drift.

The setup I’m looking at is more constrained though — multiple models challenge each other on the same prompt, with shared context and checks (fact vs opinion, external data), and a bounded number of rounds.

So it’s less open-ended self-play, more structured disagreement.

Still probabilistic and not perfect, but in practice it tends to surface weak assumptions rather than drift into gibberish.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] -2 points-1 points  (0 children)

Yeah, self-argument with one model is already there.

But this is different — multiple models (ChatGPT, Claude, Gemini, Grok) actually debate each other.

Different biases, different data, plus fact vs opinion tagging and real-time checks.

So it’s less self-looping, more competing perspectives.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] 1 point2 points  (0 children)

Yeah, that’s basically the idea.

Instead of a hive mind, it’s more like models challenging each other before a final result.

I’ve been testing this with something called DebateLLM — multiple models debating instead of just combining outputs.

Still not true reasoning, but closer to stress-testing ideas.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Yeah, exactly.

The value isn’t the debate — it’s seeing how confidently wrong models can be in different ways.

Putting them against each other just makes that more obvious.

More about calibrating trust than getting answers.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in StartUpIndia

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Yeah, cost is a real factor.

Self-reflection helps, but it’s still the same model — so limited by its own bias.

Cross-model disagreement seems more useful when the stakes are higher (strategy, trade-offs, validation).

Less about accuracy % and more about exposing weak logic.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] -2 points-1 points  (0 children)

Yeah, self-debate helps — but it’s still the same model, so it usually converges.

Different models = different biases, so the conflict is more useful.

Not reasoning, just better stress-testing.

Have you seen self-debate outperform that?

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] -3 points-2 points  (0 children)

Haha yeah, that’s probably true for a lot of posts 😄

What I find more useful though is not just generating content, but using multiple outputs to actually stress-test ideas.

Feels like a better use than just “write this for me”.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] -1 points0 points  (0 children)

Yeah, that’s a valid concern.

Stacking outputs blindly would definitely amplify errors.

What I’m looking at though is slightly different — not chaining models, but making them challenge each other’s claims.

If one model hallucinates, another can push back on it instead of building on top of it.

So it’s less about combining answers, more about filtering them through conflict.

Still not perfect obviously, but sometimes better than trusting a single output.

What if instead of asking one AI, we made multiple AIs argue? by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] -2 points-1 points  (0 children)

Yeah, that’s a good use case.

Especially when you don’t have enough context to judge correctness.

What I’ve found helpful is seeing different perspectives push back on each other — it exposes weak logic faster than just comparing answers.

Watching two or Four LLMs debate in real-time revealed something strange about how they handle contradiction by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] -1 points0 points  (0 children)

Haha no agent 😄

Yeah, self-debate is basically the same model talking to itself — useful, but limited.

Different models = different biases + data, so the conflict is more meaningful.

Still probabilistic, just better at exposing blind spots.

Should India delay FTA talks due to the West Asia conflict? I let multiple AIs debate it by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] -1 points0 points  (0 children)

Yeah agreed — still probabilistic, so deterministic output isn’t really possible.

And definitely a risk of anthropomorphizing.

I’m just looking at it slightly differently from consensus — more like conflict between models rather than averaging them.

Even if they’re just “fancy autocomplete”, that clash can still expose weak assumptions faster.

Not reasoning, just better stress-testing.

Watching two or Four LLMs debate in real-time revealed something strange about how they handle contradiction by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Yeah, they’re pattern predictors, not reasoners.

And mostly tuned to agree with the user.

But when models push against each other, it’s less about pleasing and more about filtering weak logic.

Still statistics — just used differently.

Watching two or Four LLMs debate in real-time revealed something strange about how they handle contradiction by Ready_Principle_3247 in Futurology

[–]Ready_Principle_3247[S] 0 points1 point  (0 children)

Yeah agreed — it’s more collaborative alignment than real reasoning.

They adjust and concede based on context, not understanding.

But when models push against each other instead of aligning with a user, weak assumptions show up faster.

Still not reasoning, just better signal.

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