🇮🇳 I have an idea that could change India’s education system at microscopic level :-
@RahulGandhi@EduMinOfIndia@PMOIndia - why not create a "National Student Card" for every student from Class 6 to higher education ?
One verified identity →
🎓 education
💰 scholarships & loans
🚀 startup funding
🤖 AI & tech access
🧪 innovation labs
💼 internships
🏭 manufacturing opportunities
🌍 export support
A student shouldn’t just graduate with a degree.
They should graduate with skills, experience, a portfolio, and the ability to build something.
We should connect education directly to jobs + entrepreneurship + manufacturing + exports.
Learn → Build → Manufacture → Export → Grow India 🇮🇳
If we want higher GDP and higher per-capita income, investing in students is one of the smartest places to start.
Looking forward to do research on that.
#StudentCard #Education #India2047 #SkillIndia #MakeInIndia
🚨@OpenAI found research agents posting 53 user-provided images to external websites.
Why this matters for builders:
• Agents can take real actions, not just generate text.
• Tools and internet access creates new ways for data to leave.
Overall, observing logs is important !
🚨 Attention claude users !!!
Claude code quietly added something every team running AI agents in production will eventually need !!!
v2.1.283 actually adds:
• Exact model matching.
• denied Models to block models.
• Tighter team control.
So, your agents use the models you expect and your tel decides which ones are off-limits.
🚨 Anthropic just dropped Claude's plugin directly to builders.
Now we can:
• Submit an MCP server to GitHub plugin.
• Get validation and safety checks.
• Track installs, views and search terms .
• Reach users across claude itself.
Anthropic says that MCP usage is 110x times greater this year.
So, MCP is becoming a distribution layer.
🚨An OpenAI agent searching for Australian medical-spending data hit an access boundary and kept going on.
Meanwhile, no patient records were breached.
Well, the bigger question is that when should an AI agent must know where it has to stop ?
Read👇 https://t.co/dMulbNQweG
🚨 I think a lot of people are about to waste their money on GPT-6 for one simple reason:
I mean "using the smartest model" for everything ⁉️
Well You know,
• Luna - 💲0.10/M output
• Sol - 💲2/M output
• Astra - 💲10/M output
Well that's 100% Gap ‼️
But Wait 🚨👇
I am not saying "use the cheapest model" is the main lesson I am trying to give 🤔🙂↔️
Well the real metric isn't cost per token❗️
It is cost per successful task performed ‼️
So switch the models carefully according to the tasks to save tokens and your time. 🔥
@SKatalystAI Exactly. Being cheaper per token doesn’t mean cheaper overall.
If it takes more retries and cleanup to get the job done, those savings disappear fast.
@i_mika_el Exactly buddy. Routing should measure cost per successful task: success rate, retries, tokens used, and latency.
A cheaper model that needs 3 retries can easily lose its price advantage.