44 karma · joined December 31, 2011
With big companies with large budgets bulldozing smaller players - any advice on finding a niche that is worth pursuing?
I went down the same path for videotobe.com, fully client-side with ffmpeg.wasm, and it fell over on longer videos. The memory ceiling and encode times pushed me to a cloud processing pipeline.
You've managed to solve both, the WebCodecs plus Pixi plus ffmpeg.wasm split looks like the right decomposition in hindsight.I processed 3+ hrs of media using VidStudio and it held up. Nicely done!
What is your experience in stickiness of users after acquisition via Ad? Given crack down by reddit mods for posting links - I am considering just buying ads.
On the debate about Cloudflare vs Fly vs spot instances – for bursty, infrequent workloads that already use R2 for storage, Containers are a natural fit.
The container accesses R2 over Cloudflare's internal network, so files never hit the public internet.
Check out our implementation - https://videotobe.com/blog/how-we-process-video-with-cloudfl...
(The main difference is we don't use Cloudflare Queues in conjunction with Cloudflare Containers. You can set max_instances to your desired settings to process parallel requests.)
Kanchipuram Saree has a rich history, and I learned so much more by reading this article.
I am intrigued by the Kanchipuram saree and have dreamed about owning one. The digital ledger is a unique idea – if authenticity is established, it would be easy to invest in this as art piece.
Also building simple tools for simple task such as converting audio-to-video to post on youtube and more for business users who find Premiere/Final Cut overkill for basic tasks. videotobe.com
Started as Pay-per-use service (upload the file and receive an email with transcript). Now we also offer subscription based service for media library, AI summaries, chat Q&A, insights/highlights.
Makes between $200 to $600 per month.
Tips for sub growth in transcription space?
And EbSynth looks amazing! I wonder what model/tech will track the moment so well!
Gemini might have similar capabilities for custom vocabulary, though I'm not certain about their specific implementation. The two-pass ASR+LLM approach could work with Gemini's output as well.
10% Daily time to learn about various AI tools and improve my workflow.
20% Procrastination (this might be way more than what I'm willing to accept. But this is HN, I want to appear smart )
20% Writing detailed description of features and breaking down task lists, writing acceptance tests.
20% AI Coding (Claude Code)
20% Testing + Production
Claude code is more user friendly than cursor with its CLI like interface. The file modifications are easy to view and it automatically runs psql, cd, ls , grep command. Output of the commands is shown in more user friendly fashion. Agents and MCPs are easy to organized and used.
Ask Claude to update the preference and document the moment you realize that claude has deviated away from the path.
Claude code is amazing at producing code for this stack. It does excellent job at outputting ffmpeg, curl commands, linux shell script etc.
I have written detailed project plan and feature plan in MarkDown - and Claude has no trouble understanding the instructions.
I am curious - what is your usecase?
Here's what works for me:
- Detailed claude.md containing overall information about the project.
- Anytime Claude chooses a different route that's not my preferred route - ask my preference to be saved in global memory.
- Detailed planning documentation for each feature - Describe high-level functionality.
- As I develop the feature, add documentation with database schema, sample records, sample JSON responses, API endpoints used, test scripts.
- MCP, MCP, MCP! Playwright is a game changer
The more context you give upfront, the less back-and-forth you need. It's been absolutely transformative for my productivity.
Thank you Claude Code team!
After a full workday, your brain wants easy dopamine. That is being human. You're not a startup. The people posting about 5am routines are just performing productivity online.
Maybe go to bed earlier or be more mindful when it comes to digital dooms scroll.
If an Agentic requests originate from a server - it is easy for receivers to block the server. Write a browser-plugin and you are playing in somebody else's garden.
Write a browser and now you get to pretend like a human!
https://github.com/m-bain/whisperX
It is built on top of OpenAI Whisper, so speech recognition is good, the transcript gives speaker tags as 'SPEAKER_00' and 'SPEAKER_01' etc.
Here is how the transcript may look like
https://videotobe.com/play/media/1b02f75a-9503-43aa-8956-d18...
I have been tackling this while building VideoToBe.com. My current pipeline is Download Video -> Whisper Transcription with diarization -> Replace speaker tags with AI generated speaker ID + human fallback.
Reliable ML speaker identification is still surprisingly hard. For podcast summarization, speaker ID is a game-changer vs basic YT transcripts.
The goal is to transcribe and provide summaries, topics, notable quotes, and companies and people discussed.
Feel free to send more ideas!
I'm implementing a similar workflow for VideoToBe.com
My Current Pipeline:
Media Extraction - yt-dlp for reliable video/audio downloads Local Transcription - OpenAI Whisper running on my own hardware (no API costs) Storage & UI - Transcripts stored in S3 with a custom web interface for viewing
Y Combinator playlist https://videotobe.com/play/playlist/ycombinator
and Andrej's talk is https://videotobe.com/play/youtube/LCEmiRjPEtQ
After reading your blog post, I will be testing effect on speeding audio for locally-hosted Whisper models. Running Whisper locally eliminates the ongoing cost concerns since my infrastructure is already a sunk cost. Speeding audio could be an interesting performance enhancement to explore!