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The conversation around AI is rapidly shifting from “How powerful can AI become?” to “How safe should AI be before it reaches the world?”
A new proposal highlighted by Reuters
suggests that AI labs may need to pass official safety evaluations before receiving US government contracts. The goal is to reduce risks related to misinformation, cybersecurity threats, and uncontrolled AI behavior.
As AI systems become more integrated into business, defense, healthcare, and public services, safety and transparency are becoming critical priorities not optional features.
This could become a major turning point for the global AI industry, where trust, accountability, and regulation may matter just as much as innovation itself.
#AI #ArtificialIntelligence #AISafety #TechNews #Innovation #FutureOfAI #MachineLearning #Technology #OpenAI #Anthropic
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saastock retired itself last week after 10 years of being THE place european founders met their investors. gone. replaced with shift ai.
Replacing a decade of SaaS legacy with AI focus is the ultimate proof that the old Structure is breaking. When "seats" no longer matter, Visual Authority and strategic execution are the only things left to differentiate a brand. A bold but necessary pivot.
I recently built Job Board Hub, a MERN stack application that helps users discover remote job opportunities across different areas like technology, design, marketing, and more.
The idea is simple: job descriptions are often too long, repetitive, or hard to scan quickly. So I integrated an AI-powered job summary feature that allows users to generate a quick summary of each position and understand faster whether the role fits their profile.
But beyond the UI, this project was focused on demonstrating important backend decisions that are often overlooked.
The AI integration was built through an AI Gateway, making the system flexible enough to change models over time or even combine different providers in the future. I also implemented rate limiting to prevent abuse, protect token usage, and control costs.
Another key detail is the use of streaming responses, which improves the user experience by showing the AI summary progressively instead of waiting for the entire response to finish.
Some backend highlights:
- MERN stack application
- AI Gateway architecture
- AI-powered job summaries
- Streaming responses for better UX
- Rate limiting to protect API usage
- Clean backend structure for scalability
- Remote jobs organized by category:
This project helped me explore how AI can be integrated into real product experiences while keeping backend performance, scalability, and cost control in mind.
Job Board Hub is not just a job listing app — it’s a small example of how AI can make everyday platforms faster, clearer, and more useful.
“All AI agents are just the same 3 steps.”
Reason → Act → Observe. (ReAct — Yao et al., ICLR 2023)
The challenge is not development.
It’s knowing that your system actually works, reliably, in production.
How does it handle edge cases?
Is it safe?
Does it stay on task?
How repeatable are the outputs?
What’s the delay? What’s the price?
Strong evaluations are necessary here.
Evals turn impressive demos into battle tested AI products that teams can really count on and scale.
Working on AI products where reliability actually matters?
Let’s connect.
– Mann, AI Product Engineer: Ideation, Development, Deployment
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