与「AIProductivity」相关的搜索结果

Most people use Claude like a search engine. I use it like a business partner who knows everything about me. The difference is one file: CLAUDE.md It lives in my vault and tells Claude exactly: → Who I am and how I think → What I'm building right now → My writing style and tone → Mistakes I never want to repeat Every session starts with full context. No re-explaining. No generic answers. No starting over. I wrote it in 2 hours. It's saved me hundreds since. Most people treat AI like a tool. The ones winning treat it like infrastructure. @novak7747 — build the infrastructure. #Claude# #AIProductivity# #SecondBrain#

SAP shares jumped on strong Q2 results, driven by resilient enterprise demand and accelerating cloud growth! AI PRODUCTIVITY: SAP achieved a 30% boost in developer productivity from AI, enabling a non-AI hiring freeze while keeping cloud targets intact. EBIT OUTLOOK: Full-year operating profit targets sit at a €12.0B midpoint following dilutive acquisitions. THE RATING: Despite operational efficiency and a 2.01% dividend yield, geopolitical uncertainties keep the Seeking Alpha Quant score at a neutral HOLD. Is SAP's AI-driven productivity model the future for enterprise software? $SAP

【June 21 | Insights】 10B+ daily throughput is the new normal. is solidifying its position as the ultimate production foundation for global developers. 🔹Daily Token Throughput Hits 10.69B: Scale is skyrocketing as billions of real-world application workloads run robustly on 🔹99.4% API Dominance: Driven fundamentally by deep developer adoption. AI has officially evolved from a casual chat tool into foundational infrastructure. 🔹80.4% Stripe Share: Powered by long-term, production-grade usage from high-value global developers and enterprise teams. 🔹MiniMax M3 Dominates: As today's top-performing model, MiniMax M3's rock-solid stability and cost-efficiency make it the undisputed anchor for multi-agent orchestration and advanced coding. 💡 The Takeaway: Getting model access is cheap; orchestrating high-concurrency, scalable AI productivity is where the battle is won. is that heavy-duty foundation. 🎁 MiniMax M3, top-ranked on Artificial Analysis for performance, is now available on for FREE for a limited time! 👉 Deploy your enterprise AI workflows now:

📅 June 19 | Insights AI is moving rapidly into production, with developers driving the next wave of growth. 🔹Daily Token Throughput Hits 11.25B: Scale is skyrocketing as billions of real-world application workloads run on 🔹API Consumption Share at 99.4%: Growth is fundamentally fueled by developers. AI has officially evolved from a casual chat tool into foundational infrastructure. 🔹MiniMax M3 Dominates: Today's top-performing model, becoming the go-to choice for advanced coding and multi-agent workflows. 💡 The Takeaway: The LLM era is transitioning from parameter size to production reality. The ultimate differentiator is providing a rock-solid engineering foundation that scales AI productivity. 🎁 MiniMax M3, top-ranked on Artificial Analysis, is now available on for FREE for a limited time! 👉 Build your AI workflows on

Why is the creator of OpenCode pretty skeptical about AI productivity gains, and the hype around AI? A very conversation @thdxr (and lots of truth bombs:) Timestamps: 00:00 Intro 07:03 Dax’s path into tech 09:04 Early startup experience 13:16 Getting involved with open source 16:13 OpenCode 23:17 Anthropic banning OpenCode 30:34 From terminal to GUI 32:34 OpenCode’s business model 36:33 Why inference is profitable 39:11 GPU bottlenecks 40:54 AI hype 45:50 AI spending 48:47 Dax’s memo 55:41 Dax’s skepticism of predictions 58:58 Engineering culture at OpenCode 1:02:38 How building works at OpenCode 1:05:36 Taste and quality 1:11:32 Dax’s work setup 1:12:35 The role of engineers and EMs 1:15:50 Advice for engineers 1:18:12 Book recommendation Brought to you by: • @AntithesisHQ – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages • @WorkOS – everything you need to make your app enterprise ready • @turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable Three interesting thoughts from Dax: 1. No AI-native coding agent company is “winning” by being better with AI. Dax says that none of OpenCode’s competitors are crushing them, and that nobody is using AI so well that others cannot compete. 2. Most software engineers profit from AI as time gained, not increased output — unless you change incentives! Dax says the natural way for software engineers to “cash out” their AI tooling gains is with time savings, by doing the same work as before, but faster. Until compensation and motivation structures change, most teams should expect output to stay flat while engineers go home earlier. There’s nothing wrong with this, but AI vendors sell a different outcome to CFOs: increased output. 3. AI code generation mutes the “guilt” of doing the wrong thing, but this builds up tech debt. Pre-AI, writing a hack felt bad, the second time it felt really bad, and by the third time you’d often just refactor in order to fix up the code. Now, the agent hides the hack, which skews devs’ judgment and results in less tech debt being cleaned up.

Introducing xBubble xBubble is a low-prompt AI agent that unlocks cutting-edge AI productivity with far fewer prompts, much less trial-and-error, and a much lower learning curve. This advantage stems from the following innovations: Bubble Engine: An engine builds task-specific SOPs and probes the limits of AI capabilities for specified tasks. Bubble Pilot: An AI helps users operate AI by dispatching each request to the right SOP. Powerful AI won't require users to learn AI. Read the launch post ↓