I use Manus in Slack now for pretty much everything. The slack bot for Manus is using WAY less tokens and just as efficient.
ENTERPRISE AI
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Anthropic expands Amazon partnership securing 5 gigawatts compute Claude
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We're expanding our collaboration with Amazon to secure up to 5 gigawatts of compute for training and deploying Claude. Capacity begins coming online this quarter, with nearly 1 gigawatt expected by the end of 2026.
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Level 4 Autonomous Driving Already Here for Some Users
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You will only be right for a few more weeks. And I never look at the road anymore. So for me it's already Level 4.
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From AI Experimentation to Military Mission Impact
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We had a great time with Carahsoft at the Aberdeen AI/ML Tech Showcase. We enjoyed conversations with the Army and DoW community about what it really takes to move from experimentation to mission impact. #MissionDrivenAI #partnerships #Army
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Administrative Bloat: How Organizations Expand Inefficiently
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What do administrators do? They hire more administrators, a.k.a. cancer.
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Google Cloud gains momentum with competitive Gemini AI platform
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Google's rapid AI improvement has lifted its once-beleaguered cloud division, with startups and enterprises now clamoring to build on top of the newly competitive @GeminiApp
. This week, @googlecloud will have its next big cloud moment in Las Vegas at Cloud Next 2026, where -
CPU Optimization for Agentic AI Systems: Xeon 6 and RDU Stack
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In agentic systems, CPUs do two things: orchestrate inference and run everything around it: LLVM compilation, vector DB queries, tool calls.
— SambaNova (@SambaNovaAI) 20 avril 2026
Faster execution at each step = shorter agent loop. That's why Xeon 6 + RDU is the full stack, not just the accelerator.
🔗… pic.twitter.com/GUfTThjp7SIn agentic systems, CPUs do two things: orchestrate inference and run everything around it: LLVM compilation, vector DB queries, tool calls. Faster execution at each step = shorter agent loop. That's why Xeon 6 + RDU is the full stack, not just the accelerator.
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LangSmith Observability Reveals Agent Development Patterns Across Billions Runs
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We analyzed this information from LangSmith Observability data across billions of agent runs, and we’re just getting started. Stay tuned for more LangSmith Signals as we share how devs are building agents, by the numbers.
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AI transforms product leadership from exhaustion to engagement
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My biggest takeaways from @nikhyl:
— Lenny Rachitsky (@lennysan) 20 avril 2026
1. The best product leaders are in a state of “smiling exhaustion.” For years, PMs have just been feeling exhausted—endless alignment meetings, the monotony of organizational overhead, influence without authority. Now the work is genuinely fun… https://t.co/qt8LRsWu6YMy biggest takeaways from @nikhyl
: 1. The best product leaders are in a state of “smiling exhaustion.” For years, PMs have just been feeling exhausted—endless alignment meetings, the monotony of organizational overhead, influence without authority. Now the work is genuinely fun -
Enterprise AI adoption delayed by longer sales cycles
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one hypothesis: enterprise is slower sales cycle and longer contracts so market reaction is delayed compared to fast moving devs/startups