Suppose the goal of the cold outreach campaign is to get customers for a B2B SaaS.
The B2B SaaS is low ticket & has a self-serve model with plans like $99/month and $149/month
For this case, when I am doing cold outreach should I optimize my cold email content to get a reply or instead put the direct link to the SaaS & optimize for signups instead?
Would love to know your take on this.
So my goal of the cold outreach campaign is to get customers for a SaaS.
The SaaS is low ticket & has a self-serve model with plans like $99/month and $149/month
For this case, when I am doing cold outreach should I optimize my cold email content to get a reply or instead put the direct link to the SaaS & optimize for signups instead?
Would love to know your take on this.
Suppose you're totally new to cold emailing. How would you do it in 2026?
Suppose you're totally new to cold emailing. How would you do it in 2026?
First of all. I want to thank Mongodb for just existing. If not for them I wouldn't be a business owner
I used Mongodb as my db to build multiple web apps since 2021 and one of them eventually took off & became profitable
That allowed me to quit my job & become a full time founder. Mongodb is super easy to setup if you are starting anything :)
Would love to know others in this community!
I just told it the story. Opus 5 (max effort) generated the prompts & edited the video
Edit: Since a lot of you asked how I created it, here's the workflow:
TLDR:
Claude's Opus 5 is really good at creative tasks. So I used it to help me first generate the characters using plain HTML. Then i wrote a rough draft of the story, fed to Claude and asked me to generate image prompts & video prompts for each scene. I used Grok Imagine to first generate the images & then to create the video scene from the generated image. Then used Claude with hyperframes & video-use to piece together the video
Actual Workflow:
The one rule: a video model will not draw your character from a text description. I ran the same prompt three ways - got a cream box, then a white blob, then something else. More words don't fix it. The fix is structural:
```
IMAGE model + character reference sheets → a still ← you approve this
VIDEO model + that approved still → the clip
```
The video model's only job is motion. Its prompt never describes the character. Here's a sample character sheet
Where Claude comes in
1. It built the character sheets as code, not as images. My character is a vector on our website, so I had Claude write a small renderer + an HTML page that lays out the turnaround, expressions and props, and a script that exports them all to PNG. Pixel-identical across every sheet by construction. AI-generated turnarounds drift between views and every shot inherits that drift. It also renders a labelled copy for me and a caption-free copy for the model, because a model will happily draw your captions into the scene.
2. It shot-listed the script. One shot = one camera setup = one clip. Claude splits anywhere the naction has more than one beat, then writes four things separately per shot: SCENE, POSE (the opening frame), ACTION (only what moves), CAMERA. It also flags the things that shouldn't be generated at all. Repeated framings are an edit, and a quick cut to an object is a still with a digital push.
3. It wrote the prompt pack. I give it all the character sheets and it produces both prompts per shot, plus a one-sentence plain-English "what this should look like" line above each.
4. It reviews the output. I drop the clip in a folder and say what looked wrong in plain English - *"one character moves through the table, some jump on it and it disappears, new characters emerge from the left"* — and it maps each symptom to the missing clause. Then the fix goes into the document, not into one pasted prompt, so every shot with that class of problem gets fixed at once. That last part is the whole reason Claude is in this at all: the shot list is the deliverable, the prompts are just its current contents.
The prompt rules that came out of it
The image prompt is a long structured document - identity block, style, `SCENE:` / `POSE:` / `AVOID:`. The video prompt is one comma-delimited stack of ~150 words: `action → expression → camera → world → identity → look → audio`. Mine started at 330 words with neat labelled sections; one said `CAMERA: Locked.` and came back with a full travelling dolly and the actual action missing. At that length a prompt is a suggestion.
State everything positively in video prompts. Mine were 40% negation and one clip produced all four banned items at once. Negation is weak in video models and can act as a prompt for the thing it forbids. Drop `AVOID:` from video prompts entirely — keep it in image prompts, where it works.
Say who's in frame and whether the cast can grow, what's still there at the end, what's solid. Skip it and characters walk through desks, furniture vanishes, and new characters sprout at the frame edge. Name every prop individually or the model duplicates or deletes it.
`POSE:` is frame one. Mine said "his eyes are wide" for a shot whose action was "his eyes widen". Give every character an explicit eye and mouth shape, and make constraints measurable ("clearly short of reaching" produced an arm that reached).
One image per clip, always. 2 conditioning frames makes it interpolate instead of animate. If a shot is too complex for one still, split the shot.
Generating the video
I used Grok Imagine to first generate the images & then to create the video from the generated image. Simply create the first frame supposed to be in a scene by feeding grok the character sheet and the prompt generated by Claude. Then used the image to generate the scene using Opus 5's prompt again
Editing the video
I edited the video using hyperframes & video-use (both are open source libraries) - simply ask Claude to download this and use it to edit the video, add transcription and also add B-roll if any
Music
I used Claude Opus 5 to help me generate the lyrics based on the final edited video
I did an experiment with ai models instead of doing real product photos
so these pics (including the people) were all generated from a product image captured on a phone
can i use these for an ecommerce store? or still too ai?
curious to know what you think?
I edited a video and posted it to YouTube in less than 10 minutes.
I am a solopreneur & know absolutely nothing about video editing
In fact, I once gave up on YouTube since it became overwhelming for me to handle while also running a business
So I wanted to give it one more shot & for this I wanted to use AI as much as possible to make my job easier
I started this mainly for my YouTube channel
My entire video editing setup is one folder, 1 GitHub repo, OpenAI Whisper, and Claude code in a terminal.
10 minutes from raw recording to YouTube upload. Here's exactly how I did it.
I used OBS Studio which is free and open source to record the video
The software is super simple to use. Recently to increase retention I shifted to using canvid
Then I export the MP4. That's the whole capture step.
I don't bother with takes.
I just talk. retakes, ums, stammers, dead air.
I leave it all in, and the pipeline handles them later.
I create new folder on the desktop.
Then I open claude code in terminal - Opus 4.8 with max effort
You can also open up cowork and simply paste this prompt
>Hey, I am starting up this project to be basically my video editing studio. So i want you to look at this github repository and i want you to pull in the skills and the important information you need from this. So that I can basically give you a raw video file and you would be able to edit it, remove the filler words, remove the repeated parts, add motion graphics. Basically the full pipeline
https://github.com/browser-use/video-use
→ video-use (browser-use/video-use) - the open source software that helps you with video editing
Claude reads the repository, registers the skills, and wires up the env. one-time setup.
Then it will ask you for Eleven Labs API key by default. But I went with OpenAI whisper due to me being able to run it locally.
If you would like to swap out with OpenAI's whisper, mention this:
>Replace Elevenlabs with OpenAI whisper and make it compatible with that for all future operations.
That's it. The setup is done. You never have to run these prompts again.
Drag the canvid/OBS studio export into the folder. Then I prompt:
>video.mp4 - use video-use to edit this. analyze it, remove any filler words, unnecessary silences, retakes. task is to edit out the mistakes and filler words. Do cuts where the silence is useless though there's user activity and can be trimmed off
what happens under the hood:
OpenAI's whisper (the open-source model, if accessed via their api - $0.006/min) transcribes with word-level timestamps. video-use packs the transcript down to ~12KB so an LLM can read it without choking. picks the cuts. ffmpeg renders.
Every cut lands on a word boundary, never mid-syllable. Then it self-evaluates its own output and re-cuts if pacing is off. up to 3 iterations.
i get back a finished mp4 + a project md file that remembers what i asked for next time.
Whisper sometimes merges a stretched/stammered word into one abnormally long token.
Video-use catches this - any word longer than 1s in the json is a stammer flag. but i ask explicitly:
>In some places i stammer some words then respeak the correct words after - remove the stammer or incorrect parts where i spoke and trim those out. Can you get me all those places?
It lists them. I confirm. It cuts. cleaner mp4 out.
Drag and drop into YouTube Studio. title, description, thumbnail. publish.
I go another step and ask Claude to also get me the subtitle file, timestamps, and optimized video description
No Premiere. No Resolve. No Capcut.
The entire stack is open source
Claude code is the only UI I interact with.
Plain English in, mp4 out.
──────────────────────────
I can't tell if this stack will look obvious in a year or weird forever. Probably both.
