I have this laptop that has been formatted but I had some important pictures on it, I used disc drill and the files are still there but the problem is it's about 200-300gb of pictures and videos and I cant afford to buy disk drill pro. I am aware that this sub Reddit has a list of good free tools but which one would be the best for me? The laptop is about 10 years old and has a HDD it's an Acer running Windows 10. I just want the all pictures and videos that's it.
We used to celebrate when 500 people registered for our monthly community workshops. Then we checked the chat log during the live session it was a total ghost town.
We stopped doing one-way webinars and switched to interactive roundtable discussions where attendees had to share their biggest current bottleneck in small groups.
Attendance dropped slightly in raw numbers, but the post-event discussions, networking, and resource sharing skyrocketed.
Optimize for deep participation over passive viewership.
I've started relying on AI more when building projects. It can generate components, fix errors, explain unfamiliar code, and suggest better approaches.
But there's one thing I still struggle with. It doesn't always understand why I made a particular decision in the first place.
Sometimes the code looks cleaner but completely changes the direction of the project.
How do you make sure AI follows your thinking instead of simply producing what looks correct?
Happy #StarWarsDay! What are the most inspiring products that don't just support dark mode but default to it? My collection includes:
Linear
Liveblocks
Raycast
Supabase
v0 by Vercel
Over to you! Oh and if you enjoy dark themes, make sure to star this repo full of hand-picked resources, tools, and examples to build awesome products in dark mode. #MayThe4thBeWithYou
Our early product videos began with a company introduction and a slow walk through of the software. Viewers left the video within the three seconds before we even showed the core utility.
We changed the structure by opening with the exact problem that our users faced in their daily work. We showed the result on screen right away then we showed the quick fix in the next frame.
Our average watch time. The conversion rates from video views to landing page visits increased a lot. People stay for a video when they see their own pain points solved away.
Start your product videos by showing the frustration that your tool eliminates within the first three seconds.
I asked an agent to patch a simple null-pointer exception in a login handler. Instead of a quick three-line fix, it spun up an entire abstract factory pattern, created custom error classes, and restructured the whole authentication pipeline.
For anyone deploying AI agents on day to day bug fixes how do you keep the scope minimal and prevent them from turning a tiny patch into a massive refactor?
What prompts or rules do you use to force AI tools to write the simplest possible fix instead of over-complicating things?
I had an incident where an agent was supposed to add a simple validation check to an API endpoint, but it decided to improve the database models and added unrequested migrations. It broke half our foreign key relationships because it optimized for what it thought was cleaner architecture.
For teams relying heavily on AI assistants for backend work how do you enforce strict guardrails so they don't touch your data layer without explicit permission?
What strategies do you use to keep AI tools from rewriting database logic you didn't ask them to touch?
Our e-commerce catalog had hundreds of pages with identical manufacturer-provided two-sentence descriptions. Search traffic stalled because search engines could not find context to rank us higher.
Of rewriting every page manually we built a template that combined customer review highlights and common buyer questions into the product descriptions block. We added use cases and dimensions to every single item.
Organic traffic grew by thirty-four percent over three months as search engines started indexing the user-focused content. Shoppers also spent time browsing each page.
Stop relying on supplier text, for your product descriptions. Add user insights and specific use cases to satisfy search intent.
I spent three weeks building a heavy export feature because three outspoken users kept asking for it again and again. After we launched it the numbers told me that than two percent of our active users actually used the new export feature.
For the big idea I chose a cheaper path. I put a button for the requested feature in the interface. When a user clicked that button a pop up appeared that said the feature would arrive soon and invited the user to give feedback.
Than forty percent of users clicked the button proving that there was real product demand before I wrote one line of backend code. That proof saved us weeks of wasted engineering effort.
I always measure real user clicks on a placeholder interface before I commit development resources to a feature.
