The wait is over, Staking Hero S4 is live! Same Rules! Different Winners?👀
$500 Pool to 5 Winners 💜
Stake 5,000+ PUBLIC🔥
Earn tickets daily, Let it run and earn while sleeping💤
Campaign ends on June 15
Stake on 👇
https://t.co/rmTdhhfstQ
AI Coding Tools is seamlessly emerging and growing. We are launching Public AI Gateway very soon. One API key + one balance, routed across Claude, GPT, and Gemini. Here's what it does and why we built it
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1/ The problem: shipping with LLMs means juggling 3 provider accounts, 3 keys, 3 bills, and 3 rate limits. Switching models means rewiring your code.
@awscloud Curious how you see the balance between AI-generated code and developer productivity? Are there specific scenarios where you think it’s more of a hindrance than a help?
@bijanbowen What an incredible visualization idea! turning network packets into car types on a highway is such a creative way to explain complexity. I love how this could make data flow more relatable.
@cognition FrontierCode sounds like a game-changer! finally, a coding eval that focuses on maintainability and quality. This will raise the standards for developers everywhere!
@eliebakouch Curious how the intentional limitations of mythos will impact its usability in practical applications? What are the potential consequences for the research community when the shortcomings are not transparent to users?
This isn’t just Anthropic being cheap. It’s the moment everyone realizes AI coding tools were never ‘cheap’ the token meter was always running.
Non-tech teams thought it was magic. Builders now see it needs governance, dashboards, and smart routing. Web3 or not, the next wave is agentic coding that’s actually sustainable. How are you adapting your workflow?🤔
@gabriel1 Curious how this prediction accounts for the potential to streamline communication with AI over time. If adapting our explanations takes time, could we also see efficiency gains as AI improves? What’s the balance?
Anthropic just dropped the blueprint for the next AI wave. Stop forcing agents into 1990s biology databases. Build brand-new infrastructure they can actually use. When that happens, drug discovery, personalized medicine, and synthetic biology go from decades to days.
The cities-before-cars era is ending. Agent-native biology starts now.
Who’s ready for the acceleration?🔥
New Science Blog: Why has AI advanced faster in coding than in biology?
To agents, bio databases are like cities built before cars—maddening to drive in because they're designed for different traffic.
How do we build infrastructure agents can use?
https://t.co/PQaNQ4GRJZ
@krishdotdev Curious how you see the shift from FAANG to MANGO impacting overall market dynamics? are there specific factors driving this change that we should be aware of?