5/ Official resources:
Docs: https://t.co/Kk7fasCYCj
API Keys: https://t.co/eEFCqivHeZ
Source Code: https://t.co/IIQm3dmbj1
If you're already using GitHub Copilot, setup takes only a few minutes.
Tired of being limited to default GitHub Copilot models?
You can now use DeepSeek V4 directly inside GitHub Copilot on VS Code Insiders.
What you get:
👇👇👇👇
#DeepSeek#GitHubCopilot#VSCode#Coding#AI
3/ To route Copilot requests through DeepSeek models, create:
.vscode/settings.json
Recommended configuration:
deepseek-v4-pro for utility/chat tasks
deepseek-v4-flash for completions and fast interactions
Enable stabilizeToolList for improved reliability
2/ Generate a DeepSeek API key:
https://t.co/eEFCqivHeZ
Open the VS Code Command Palette (Ctrl+Shift+P) and run the extension's setup command. Paste your API key when prompted.
1/ Install the DeepSeek V4 for Copilot extension in VS Code Insiders.
Extension:
https://t.co/IIQm3dmbj1
After installation, DeepSeek models become available inside GitHub Copilot.
What you get:
• DeepSeek V4 Pro for advanced coding tasks
• DeepSeek V4 Flash for fast completions
• Bring Your Own API Key support
• Project-level model configuration
A simple setup and you're coding with DeepSeek inside Copilot.
Here are 10 GitHub repos that quietly print money while you sleep.
1. Cal. com
Open-source Calendly. Fork it, white-label it, sell to dentists and lawyers for $200/month. The founders hit $5M ARR in 3 years doing exactly this.
Repo → https://t.co/haz8ihRsHm
2. Plausible Analytics
Privacy-first Google Analytics. Self-host it, resell to agencies for $50/month per client. Two founders bootstrapped this to 7 figures.
Repo → https://t.co/RFrcpqTBQ7
3. Ghost
Open-source Substack with 100% margin. 1,000 readers at $5/month equals $60,000 a year. Forever.
Repo → https://t.co/Z1MdZ5Zapg
4. n8n
Open-source Zapier. Sell automation services for $500-$2,000 per setup. n8n raised $14M because the agency model behind it works.
Repo → https://t.co/hdycABGGc1
5. Supabase
Free Firebase replacement. Build a SaaS in a weekend, charge $29-$99/month. They raised $116M for a reason.
Repo → https://t.co/dFB2QvafA7
6. Medusa
Open-source Shopify. Take 5% on every sale forever. Zero rev share to Shopify.
Repo → https://t.co/uEuCK6zuZO
7. AppFlowy
Open-source Notion. Sell self-hosted to enterprises worried about data privacy. They raised $30M because this market is massive.
Repo → https://t.co/IDMykTCkMU
8. Coolify
Open-source Vercel and Heroku. Charge developers $20/month to manage their deployments. Replace their $200 Vercel bill.
Repo → https://t.co/N5Fk22qraT
9. Listmonk
Open-source Mailchimp. Send unlimited emails for the cost of an AWS bill. Resell to agencies at 10x markup.
Repo → https://t.co/NS6Uukcklw
10. Penpot
Open-source Figma. Sell self-hosted design tools to agencies who refuse to upload client files to the cloud.
Repo → https://t.co/Lx1CYUP4p4
The difference between developers who build features and developers who build businesses is one decision.
Pick one of these. Fork it this weekend. Ship it next week.
The founders behind these repos already proved the model.
Save this. Share it with the developer in your life who deserves to break free.
100% free. 100% open source.
lol...Kimi really cooked Claude Design
tested the same prompt on both Kimi K2.6 and Claude Design,
and these are the outputs
not to mention Kimi is 7x cheaper and 100% open source...
see prompt in the comments👇
ESTO ES UNA LOCURA
La mayoría pasa AÑOS usando apps de idiomas y aun así no logra hablar bien.
Claude hizo en 4 semanas lo que Duolingo no pudo arreglar en 4 años.
Aquí van los prompts 👇
AI in robotics gets all the attention right now, but sometimes the most interesting work is very practical.
Viet built a small vision system that counts potatoes on a conveyor belt. No giant dataset. No huge model. Just a clear problem and a smart setup.
He used Ultralytics’ ObjectCounter, trained a tiny YOLO11 nano model, and because there was no potato dataset, he annotated a single frame with SAM 2 and trained from that. One frame. Still works across the whole video.
It is a good reminder that useful AI in industry often looks like this.
Focused. Lightweight. Solves a real task.
If you work in manufacturing or robotics, these small systems are usually the fastest wins. They save time, reduce errors, and do not need massive infrastructure.
Nice work, Viet.
His projects:
https://t.co/1TSrwcKGCW
—-
Weekly robotics and AI insights.
Subscribe free: https://t.co/dsa6wcvq6n
If you want to become a world-class software engineer, learn these 19 system design case studies:
1 How Stock Exchange Works:
↳ https://t.co/iFNSX9TM9O
2 How Payment System Works:
↳ https://t.co/ARiLxGR43G
3 How YouTube Works:
↳ https://t.co/kHk3g6jz6t
4 How Google Docs Works:
↳ https://t.co/W57IkAjXpT
5 How Kafka Works:
↳ https://t.co/8rOy9KgCMo
6 How Pastebin Works:
↳ https://t.co/8NSUNlYM7q
7 How WhatsApp Works:
↳ https://t.co/VScq8QwHMr
8 How Airbnb Works:
↳ https://t.co/Bi5SAjfv5S
9 How Spotify Works:
↳ https://t.co/BxrH3oHIFS
10 How Slack Works:
↳ https://t.co/eIo29uOQOJ
11 How Reddit Works:
↳ https://t.co/o6Pw2hhj3T
12 How Google Search Works:
↳ https://t.co/jwOaC4bhnv
13 How Real-Time Leaderboard Works:
↳ https://t.co/HEChNTOHWb
14 How Twitter Works:
↳ https://t.co/pF2RYmPaIG
15 How Uber Computes ETA:
↳ https://t.co/hw1hYJqQmj
16 How Amazon Lambda Works:
↳ https://t.co/lx0BjeSRZt
17 How Amazon S3 Works:
↳ https://t.co/iReWAEHwmj
18 How Do AirTags Work:
↳ https://t.co/upWcgsXwKh
19 How ChatGPT Works:
↳ https://t.co/5lCKxq2g4N
What else should make this list?
——
👋 PS - Want my System Design Playbook (for FREE)?
Join my newsletter with 200K+ software engineers right now:
→ https://t.co/ByOFTtOihX
———
💾 Save this for later & RT to help others become good at system design.
👤 Follow @systemdesignone + turn on notifications.
Link: https://t.co/vPP4jVP5kl
If you want more practical AI gems and use cases, join our free newsletter with daily tutorials and latest news in AI: https://t.co/SFv0jdOYBK
Calling what we do now vibe coding is like calling flying a plane vibe flying.
Nobody's vibing at 40,000 feet. You have a destination, you make decisions, the autopilot handles the rest. Same thing. The models got serious. The workflows got serious. The results got serious but the name didn't.
It should be called intent coding.
You think clearly, you express what you want, the model executes.
The skill shifted from typing to thinking.
As a developer,
Please slap yourself if you can't explain at least 10 of these :
API Gateway
Load Balancer
Reverse Proxy
Rate Limiting
Throttling
Pagination
Cache stampede
Idempotency
GraphQL
gRPC
Webhooks
JWT
OAuth
Cache invalidation
Composite index
Query optimization
CAP THEOREM
ACID
Sharding
Circuit breaker
Livelock
CSRF
Backpressure
False sharing
mTLS