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[📸] #CHAEYEON_pic# └ 📍#WManagement# in 쑤저우 오늘도 채리쉬들의 사랑으로🍒❤️ 행복한 마음 가득 안고 가요! (๑╹ω╹๑ ) #이채연# #LEECHAEYEON#

Retentive highlights the extraordinary potential of peer-to-peer infrastructure, positioning Perceptron Network as a cornerstone of next-generation artificial intelligence research, decentralized bandwidth sharing, and sovereign data management. @PerceptronNTWK #NodeAndProud#

dear any OF girl with management: u are a lazy piece of shit. theres no other way around it. u r simply a greedy money hungry whore. there is no excuse. u are simply a bad person. just admit it and i wont come 4 u

The cryptographic world computer: My attempt to express in somewhat concise terms the true meaning of basically everything planned to happen to Ethereum starting from the fork after Hegota. It's really not just a blockchain anymore. It's a hybrid architecture that combines together blockchains and modern cryptography, to enable much more powerful properties. FOCIL, EIP-8288, Lean consensus, state management, formal verification, advanced mempool improvements (including privacy), and the longer-term specter of obfuscation all mentioned.

Yep. Except: 1. This was about important internal tools. The team was stuck in some architecture nightmare of their own doing (writing it in rails but headless, with graphql api, and a SPA react app, constantly needing frontend engineers for changes). I call this kind of thing 'cosplaying an enterprise production app'. All that complexity was in the way and using straight rails was perfect in that case. 2. I make calls like this all the time. Usually someone on the team asks me to. They see what needs to happen but don’t want to be the bad guy. I’m happy to just make the call if I agree with the premise. Saves enormous amounts of meetings and change management etc. Sometimes this is jokingly referred to as Founder-mode-as-a-service here. 3. For ten years I’ve also run an internal podcast called Context, where I revisit decisions like these and explain the reasoning so everyone can learn from them. This is helpful to give people all the variables that were considered and why this was the choice made given the information available at the time. I want to teach how to make such decisions effectively without needing me. Sunk cost fallacy is a problem. 4. Any notions that Shopify is succcessful despite of me doing this, instead of because of it, will have a hard time making their argument come together I think 😄 the part of 'two weeks later tobi learns about...' is nonsese and the pivot of that project up there happens one of the more successful examples of interventions. But getting the company to work effectively with great architecture and low technical debt baggage into the right direction is literally the job, so guilty as charged I suppose. But there are always cope stories floating around like this because they are more fun, than saying 'somehow we needed tobi to stop doing silly architecture astronautics'. I can totally see that.

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ByteDance dropped a banger paper on self-evolving agent harnesses! HarnessDev evaluates whether AI agents can build a runnable harness from scratch and iteratively improve it using execution feedback. Most agent benchmarks keep the harness fixed and only evaluate the model inside it. HarnessDev changes the target of evaluation itself. The agent starts from a minimal seed, builds the harness around the task, runs it, observes what worked or failed, and then modifies that harness across multiple iterations. That means the agent is not only solving the task. It is also changing the planning, memory, tool use, state management, and execution logic around itself. The paper evaluates this in two stages: • Creation: can the model build a complete runnable harness from a minimal starting point? • Evolution: can it improve that harness using feedback from previous runs? The interesting part is that runnable does not automatically mean better. Some generated memory and state mechanisms existed in the code but were barely used during execution, and improvements on visible feedback did not always transfer to held-out tasks. Only 34 of 64 harness changes moved in the same direction on both visible feedback and held-out evaluation, and only 2 of 9 final harness versions were actually the best-performing version on the held-out set. So the paper is really exposing a new challenge: Agents can already start modifying the infrastructure they run on. The harder part is making sure those changes actually generalize. I've shared the paper in the comments!

The First U.S. Spot Staked $TRX ETF is now live @CanaryFunds has launched the spot $TRX ETF ($TRSX), with staking rewards included in its net asset value. This innovative approach marks a new era for the ETF space by offering yield-bearing products beyond passive index funds. Bridging asset management and on-chain activity through staking rewards integration is key.