I found a pretty cool piece of software 😂
Protect your spine: An AI assistant that watches your posture through your webcam 🤨
If you start turning into a shrimp or faceplanting into your monitor, the app will gently (or persistently) remind you to straighten up:
What it does:
• AI analyzes your neck and shoulder angles in real-time through your camera
• When it detects “tech neck syndrome,” you get a notification with recommendations
• Assigns your posture a score (0-100) and tracks your progress over time
• Fully configurable sensitivity and check intervals, so it won’t spam you every second
#TipsAndTools
Protect your spine: An AI assistant that watches your posture through your webcam 🤨
If you start turning into a shrimp or faceplanting into your monitor, the app will gently (or persistently) remind you to straighten up:
What it does:
• AI analyzes your neck and shoulder angles in real-time through your camera
• When it detects “tech neck syndrome,” you get a notification with recommendations
• Assigns your posture a score (0-100) and tracks your progress over time
• Fully configurable sensitivity and check intervals, so it won’t spam you every second
#TipsAndTools
👍2🔥2⚡1
#WeeklyDigest №3
🔹 Cursor releases Debug Mode so agents debug using real runtime logs instead of static guesses
🔹 OpenAI releases GPT-5.2, boosting reasoning, coding reliability, and long-context performance for production agents
🔹 Google launches Code Wiki, an automated system that keeps repo documentation continuously up to date
🔹 NVIDIA releases Nemotron 3, an open model family built for large-scale multi-agent AI systems
🔹 Anthropic rolls out syntax highlighting, prompt suggestions, and a plugin marketplace in Claude Code
🔹 Cursor releases Debug Mode so agents debug using real runtime logs instead of static guesses
🔹 OpenAI releases GPT-5.2, boosting reasoning, coding reliability, and long-context performance for production agents
🔹 Google launches Code Wiki, an automated system that keeps repo documentation continuously up to date
🔹 NVIDIA releases Nemotron 3, an open model family built for large-scale multi-agent AI systems
🔹 Anthropic rolls out syntax highlighting, prompt suggestions, and a plugin marketplace in Claude Code
🔥2
Media is too big
VIEW IN TELEGRAM
#TipsAndTools
OpenAI just dropped GPT-Image-1.5, and it's genuinely impressive 🔥
The new model follows prompts much more accurately, handles edits without breaking details, and generates images 4× faster than before. It's now free in ChatGPT and available via API.
What I love: you can edit existing images iteratively without losing quality — faces, text, and composition stay intact. Plus there's a dedicated Images panel with preset styles to speed up workflows.
Been testing it for two days now. If you do any work with AI images, definitely worth checking out.
Official prompting guide
OpenAI just dropped GPT-Image-1.5, and it's genuinely impressive 🔥
The new model follows prompts much more accurately, handles edits without breaking details, and generates images 4× faster than before. It's now free in ChatGPT and available via API.
What I love: you can edit existing images iteratively without losing quality — faces, text, and composition stay intact. Plus there's a dedicated Images panel with preset styles to speed up workflows.
Been testing it for two days now. If you do any work with AI images, definitely worth checking out.
Official prompting guide
1🔥2
Big news 🚀
After months of work, my private developer community is finally live 🥹
Ars Dev Hub
Join now to get:
📚 +5 Practical AI courses
📰 WeeklyDigest
🛠️ Collection of Tools & Resources
☕ MondaySync
💬 Real community
🚀 and more...
💎 First 50 members lock $5/month for lifetime (then $25/m)
💎 Try Risk FREE for 7-days
See you inside 🔥
After months of work, my private developer community is finally live 🥹
Ars Dev Hub
Join now to get:
📚 +5 Practical AI courses
📰 WeeklyDigest
🛠️ Collection of Tools & Resources
☕ MondaySync
💬 Real community
🚀 and more...
💎 First 50 members lock $5/month for lifetime (then $25/m)
💎 Try Risk FREE for 7-days
See you inside 🔥
👍5🔥1
The 7 skills that matter more than frameworks in 2025-26
If you're learning to code in 2025, don't just chase frameworks.
The game has changed. AI is here, and the developers winning are the ones who know how to think, not just how to code.
I broke down the 7 skills that actually matter now 👇
Read post in ADH Community
If you're learning to code in 2025, don't just chase frameworks.
The game has changed. AI is here, and the developers winning are the ones who know how to think, not just how to code.
I broke down the 7 skills that actually matter now 👇
Read post in ADH Community
⚡2
#WeeklyDigest №1 2026
🔹 Along with the regular GPT-5.2, OpenAI released GPT-5.2 Pro — their most powerful model to date. Costs a whopping $21/168 per million tokens, available via API.
🔹 Right after that, GPT-5.2 Codex dropped — SOTA among closed models for development. Currently only available in the Codex app and CLI, API access promised for early 2026.
🔹 Google launches Gemini 3 Flash, matching Pro-level reasoning while cutting inference cost by almost 50%
🔹...
The complete WeeklyDigest is now available in HUB
🔹 Along with the regular GPT-5.2, OpenAI released GPT-5.2 Pro — their most powerful model to date. Costs a whopping $21/168 per million tokens, available via API.
🔹 Right after that, GPT-5.2 Codex dropped — SOTA among closed models for development. Currently only available in the Codex app and CLI, API access promised for early 2026.
🔹 Google launches Gemini 3 Flash, matching Pro-level reasoning while cutting inference cost by almost 50%
🔹...
The complete WeeklyDigest is now available in HUB
🔥2👍1
Andrej Karpathy’s 2025 Year in Review
Andrej Karpathy published his comprehensive year-end retrospective, and it’s packed with insights on where AI actually stands right now.
🔗 Read the full post: karpathy.bearblog.dev/year-in-review-2025/
Key Takeaways:
1. RLHF is out, Verifiable Rewards are in
Reinforcement Learning from Verifiable Rewards has replaced RLHF as the dominant training paradigm. Models now learn from automatically verifiable rewards rather than human feedback—and this shift is what unlocked reasoning capabilities. The year’s biggest breakthrough? Scaling test-time compute.
2. Benchmarks have lost their credibility
LLMs don’t work like human brains. They can be superhuman in some domains while surprisingly weak in adjacent ones. 2025 made it crystal clear: high benchmark scores ≠ AGI.
3. The Cursor era has begun
Cursor and similar tools represent a new layer of LLM applications. AI is no longer just about raw models—it’s about orchestrating API calls, managing context, designing UX, balancing autonomy, and optimizing costs for specific tasks.
4. “Vibe coding” went mainstream
Writing code is now cheap and accessible. Anyone can vibe-code something functional. The democratization is real.
5. Autonomous AI agents have arrived
We’re seeing the first examples of truly capable autonomous agents working directly on your computer—tools like Claude Code. They’re here, and they work.
6. Image and video generation made a huge leap
The progress has been so dramatic that an LLM-powered operating system no longer feels like distant sci-fi.
Definitely worth reading in full 👉 karpathy.bearblog.dev/year-in-review-2025/
Andrej Karpathy published his comprehensive year-end retrospective, and it’s packed with insights on where AI actually stands right now.
🔗 Read the full post: karpathy.bearblog.dev/year-in-review-2025/
Key Takeaways:
1. RLHF is out, Verifiable Rewards are in
Reinforcement Learning from Verifiable Rewards has replaced RLHF as the dominant training paradigm. Models now learn from automatically verifiable rewards rather than human feedback—and this shift is what unlocked reasoning capabilities. The year’s biggest breakthrough? Scaling test-time compute.
2. Benchmarks have lost their credibility
LLMs don’t work like human brains. They can be superhuman in some domains while surprisingly weak in adjacent ones. 2025 made it crystal clear: high benchmark scores ≠ AGI.
3. The Cursor era has begun
Cursor and similar tools represent a new layer of LLM applications. AI is no longer just about raw models—it’s about orchestrating API calls, managing context, designing UX, balancing autonomy, and optimizing costs for specific tasks.
4. “Vibe coding” went mainstream
Writing code is now cheap and accessible. Anyone can vibe-code something functional. The democratization is real.
5. Autonomous AI agents have arrived
We’re seeing the first examples of truly capable autonomous agents working directly on your computer—tools like Claude Code. They’re here, and they work.
6. Image and video generation made a huge leap
The progress has been so dramatic that an LLM-powered operating system no longer feels like distant sci-fi.
LLMs turned out to be simultaneously smarter and dumber than expected. But they’re already incredibly useful—and the industry has barely tapped into their potential, maybe 10% at most.
Definitely worth reading in full 👉 karpathy.bearblog.dev/year-in-review-2025/