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If you want your AI agent to be really secure you need kernel level management
Prompts won't cut it
Harnesses are not enough
You need an Agent OS
https://t.co/M7IDZ5FlfW
love this. Does anyone really think a billion always-on autonomous machines are going to be using shared-ledger blockchains for settlement? Time for something new https://t.co/MEaxbotKeA
The panel is locked in. If you're at AGI Summit SF (@agisummitai) this weekend, here's exactly where to catch us.
Our Co-Founder & CEO @ChiZhangData takes the AGI Stage for "When AI Agents Go to Work: Building, Trusting & Scaling Autonomous AI."
🗓️ Saturday, July 18, 5:35-6:05 PM PT
📍 AGI Stage, Palace of Fine Arts, SF
Panel lineup:
▷ Zihan Wang, CTO, O2 AI (Moderator)
▷ Chi Zhang, Co-Founder & CEO, Kite
▷ Emery Han, Go-To-Market Platforms, Stripe
▷ Li Erran Li, Head of Science, HIL team, AWS
▷ Xuewei (Harvey) Wu, ML Engineer, Meta
▷ Charlie Hu, Co-Founder, OpenMax
▷ Kang Hongwen, Founder & CEO, https://t.co/TMHqQgu8Hb
The through-line: how autonomous agents get built, trusted, and scaled once they start transacting on their own. Kite brings the trust layer, verifiable identity and programmable spend controls for every agent.
Come find us at the Palace of Fine Arts. 🪁
Love these early builds on Sphere! Sphere 2048 with real prize pools and the provably-fair Arcade House look super fun. Pact's trust-minimized design is especially impressive. Keep shipping, builders!
Happy Friday - we've added the first 4 developer apps from our Call For Builders to https://t.co/gPqGBblReL
Here are the submissions and why we think they're great!
Exchange bStocks for actual stocks 1:1 anytime on Binance.
No additional fees. No downtime. No need to swap to stablecoins/fiat first.
Another step toward making investing simpler, more accessible, and more connected.
Excited to see Unicity's latest papers live on arXiv: 'Unicity: Predicates and Atomic Swaps' and 'The Unicity Execution Layer'. Advancing secure off-chain transactions with predicates for smart-contract-like functionality and trustless atomic swaps!
The e-Estonia KSI blockchain: built by this team.
Deployed nationally in Estonia. Used by DARPA, in the NATO cybersecurity ecosystem, and UK healthcare.
What we're building now: settlement infrastructure for autonomous agent economies.
https://t.co/0YXZDmofvd
✅ VALIDATION AT THE EDGE
Unicity eliminates the shared asset ledger construct entirely.
Like cash, tokens move p2p and are locally verifiable at the edge with zero trust
Two consequences of this architecture that enable autonomous AI >>>
Microsoft just open-sourced SkillOpt!
A framework for training agent skills like neural networks:
SkillOpt treats a plain markdown file as the trainable parameter of a frozen LLM agent, applying the same optimization discipline used in weight training: learning rates, validation gates, batch sizes, and epoch schedules.
The analogy maps precisely. The skill document is the parameter. Trajectory-derived edits are the gradient direction. An edit budget is the learning rate. A held-out split is the validation check.
Here's how it works.
A frozen model runs tasks with the current skill and produces scored trajectories. A separate optimizer model analyzes failures in minibatches, proposes structured add/delete/replace edits, and ranks them under a budget cap.
If the candidate skill improves performance on a held-out split, the edit is accepted. If not, it's rejected and stored so the optimizer avoids repeating failed changes.
The deployed output is a single best_skill. md file, typically 300 to 2,000 tokens. No weight changes, no extra inference-time calls.
The learned rules are compact and readable. These read like rules a thoughtful engineer would write after a day with the benchmark, except they were discovered automatically.
Learn more:
Paper: https://t.co/sdj5DW7t9h
GitHub: https://t.co/W3DcpBCni0
SkillOpt isn't the first system to treat skills as something you can optimize.
Hermes Agent independently built the same idea through a combination of skill_manage, Curator, and an optimization loop called GEPA that scores, mutates, and promotes skill documents across runs.
Two teams, different architectures, same conclusion: the skill file is the highest-leverage thing to optimize in a frozen-model agent.
I wrote a deep dive on how the Hermes agent works and covered all of these topics briefly.
The article is quoted below.
Best wishes to my ministerial colleague Shri Nitin Gadkari Ji on his birthday. He is at the forefront of numerous efforts towards ensuring India gets next-generation infrastructure and enhanced connectivity. Praying for his long and healthy life.
@nitin_gadkari
Autonomous AI needs an internet built for machines
✨ True P2P - no central ledger
🌐 Validation at the edge
🚀 Agent-Agent with speed that scales
Built for billions of daily transactions
Join early for the upcoming airdrop:
https://t.co/jVEpzG8awh
The first asset on our RWA launchpad is live.
SimpleChain built the infrastructure — DataIPO brings the assets onchain. Cycle Yield Fund is just the beginning.
· Real business cash flow.
· Full data transparency.
We built the rails. Now the assets are rolling. 👇 👇
Flashcast Social live on private beta.
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