𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞, 𝐀𝐮𝐝𝐢𝐭 𝐓𝐫𝐚𝐢𝐥𝐬, 𝐚𝐧𝐝 𝐑𝐞𝐠𝐮𝐥𝐚𝐭𝐨𝐫𝐲 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭𝐬 𝐟𝐨𝐫 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 The EU AI Act's full enforcement is near. If your agents touch credit decisions, employment screening, or regulatory reporting, you're in scope. The gap between running agents and running auditable agents is not a documentation problem - it's architectural. Most teams have logs. Regulators need audit trails. These are not the same thing. Logs are mutable, unstructured, and missing the fields regulators need - model version, policy version, integrity hash, reviewer identity, intervention points. An audit trail is immutable, correlated across agents, attributed to specific versions, and queryable on demand. A standard logging system satisfies none of Articles 9, 12, 13, 14, or 15 of the EU AI Act. The technical obligations are concrete. Article 12 demands record-keeping with sufficient detail to reconstruct decision paths. Article 13 requires transparency - tracing every output back to its inputs and model version. Article 14 requires structured human oversight points, not theoretical ones. Article 9 demands active, ongoing risk assessment. Teams that built agents without these properties now face structural rework. The fix is not adding audit fields to log messages. It's an architectural shift - an immutable audit trail integrated with your agent registry, policy gates, and human oversight interrupts. Each record must capture inputs, outputs, tool calls, policy decisions, and human interventions. Every field must be queryable. Nothing can be modified after creation. This is what separates compliance theatre from actual auditability. 𝐑𝐞𝐚𝐝 𝐭𝐡𝐞 𝐟𝐮𝐥𝐥 𝐠𝐮𝐢𝐝𝐞: ranjankumar.in/ai-control-pl… 𝐹𝑜𝑙𝑙𝑜𝑤 𝑓𝑜𝑟 𝑚𝑜𝑟𝑒 𝑜𝑛 𝑏𝑢𝑖𝑙𝑑𝑖𝑛𝑔 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑎𝑔𝑒𝑛𝑡𝑖𝑐 𝑠𝑦𝑠𝑡𝑒𝑚𝑠 𝑡ℎ𝑎𝑡 𝑠𝑐𝑎𝑙𝑒 𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑏𝑟𝑒𝑎𝑘𝑖𝑛𝑔. #AICompliance #AuditTrail #EUAIAct #AgenticAI #MLOps #Regulatory #ControlPlane

k8sのegress gateway実装しました。dataplaneはvppでSRv6も使えます。controlplaneはGoBGPで、uSIDも対応してます。 github.com/ryskn/vpp-datapla…

Meet the aegises.org stack, a sovereign internet architecture for AGI, goverable by policies at every addressable bit: cloud dataCenters\asic<=fpga|cheri qemu|cheri-sel4-microkit-CAmkES\microvm\nixos-posix\git-rust-rusqlite-openDAL\mlir\xdp2\k8s-nats\cilium-tetragon\cedar-policy-compiler placement-dma-monitor\tailscale-host-data&controlPlane\IX-port\client-platform&ui(pending) Every AI is fertile ground for this seed. Just ask them what it means - and what should be done.

On June 13, the UCWS Singapore 2026 Hackathon Demo Day was held successfully at @Singtel in Singapore. Over the past month, we watched AI Builders from around the world turn ideas into code, push their demos into real-world scenarios, and bring 20 outstanding projects to the Demo Day stage in #Singapore. At the UCWS 2026 #Hackathon Demo Day, our finalist teams showcased their work across three main directions — Skill, Agent, Application, and Deep Research — spanning developer tools, enterprise productivity, investment research, education, F&B, city events, emotional companionship, and many more real-world scenarios. After 50 days of building, our expert judges crowned the winners through live pitches, judge Q&A, and a final panel vote. 🏆 The champions of UCWS Singapore 2026 are here. 🏆 Golden Skill Award: re-forge (Shine Gupta, S Akash) re-forge is a multi-agent engineering collaboration system built for coding tools such as Claude Code, Cursor, and Codex. Through seven user-invokable commands — /research, /engineer, /security, /testing, /docs, /forge, and /evolution — it allows AI to write code not just quickly, but with memory, testing, and quality control preserved along the way. Demo:re-forge.vercel.app/ GitHub:github.com/Akasxh/re-forge 🏆 Golden Agent Award: Marsham Edge (Muriel Demarcus) Marsham Edge is a multi-agent anomaly-detection and intelligence-analysis system, in which three agents — Argo, Ken, and Deb — collaborate on data cleaning, risk identification, and analytical briefings. It emphasizes explainability and auditability, making it well suited to scenarios such as security monitoring and industrial sensing. GitHub:github.com/MJDemarcus/marsha… 🏆 Golden Application Award: GranTelly (Markus Foo, Zhong Yiting) GranTelly provides AI-powered family connection for long-distance communication between seniors and their family members. It helps seniors share their daily lives through a simple senior-facing device, while helping faraway family members receive clear, concise updates, background context, and conversation prompts. GitHub: github.com/mksf11e/GranTelly The Deep Research track was evaluated online, and we’re excited to congratulate the winners: 🏆 Best Use Case: Game Studio ControlPlane (STUDIO OS) by Visaruth Sornsing, Pokai Thippawat, Thanutchaporn Sangprasith STUDIO OS is an AI-native game studio control plane that uses 54 agents to simulate roles such as producer, director, programmer, art designer, and market researcher, collaborating to carry out market research, task breakdown, development tracking, and Godot builds. Its strength lies in making the game development process more structured, observable, and testable — well suited to small teams moving quickly through prototyping. GitHub：github.com/agentic-game-stud… 🏆 Best Technical Implementation: Argus by Chaoqi Luo Argus is a fact-checking tool for AI-generated content. Users can upload a report or PDF, and the system extracts the key claims and verifies them one by one, providing evidence, a confidence score, and a reasoning trail. It's well suited to high-stakes scenarios such as legal, investment, research, and compliance work, helping users catch false citations, unsupported claims, and logical gaps. Demo:argus-truth-engine.vercel.ap… GitHub:github.com/Chaoqi31/argus-tr… 🏆 Best Reasoning Transparency: Bet Decoder by Henry Bet Decoder is an investment-assumption reverse-engineering tool that works backward from a stock price, analyst target, or portfolio to surface the market's implied expectations, then validates the evidence behind them through deep research. Rather than giving investment advice directly, it helps users see clearly which growth, valuation, and risk assumptions an investment truly rests on. Demo:0xmyh-bet-decoder.hf.space GitHub:github.com/hnaymyh123-henry/… A huge thank you to our judges — AI experts, founders, investors, researchers, and ecosystem leaders — for their time, insights, and thoughtful evaluation: James Ong, Kisson Lin, Ethan Seow, Kenny Tay, Yinghui Kuang, Hide Oh, Valencia Queck, Victor Chu, Madhur Mayank Sharma, Cai Yiqing, Lionel Ang, Dorien Herremans, Arul Murugan, Atul Babu, Jielun Ong, Erica Ding, Junda Zhang, Jit Singh Kairon, Theresa Hoffmann, William Liu, Bryan Chua, Tyler Qiu, Indranil Sarkar, Trucky Liu, Yuna Wu, Cruise Chen, Lois Sun, and Kaushik Muhury. To every team who built, shipped, presented, and showed up — thank you for making this community what it is. 🙌 Apologies that LinkedIn caps how many people I can tag in one post, so I couldn't @-mention everyone who made this happen. If we worked together on UCWS — partners, volunteers, builders — please drop a comment below so everyone can find and connect with you. 👇 No Rules, Just Create. #UCWS2026 #Hackathon #AIBuilder #Singapore #NoRulesJustCreate #EPICConnector #DemoDay #BuildWithAI

Can The AI Make Things Worse #devops #platformengineering #sre #cloud #aiagents #controlplane #ai This is a clip from our recent Ship It Weekly Podcast episode. Visit link in bio to listen to the full episode!

The question with multi-agent systems in regulated environments is not whether agents can act. It is how far their authority extends, and what stops them from exceeding it. Autonomy creep is a hard problem, especially when agents can spawn and orchestrate other agents. William Rizzo, Global Field CTO at Mirantis, will take the stage with Francesco Beltramini, Field CTO from ControlPlane at OSFF London to present a pragmatic, cloud native approach to enforcing agent guardrails on real-world Kubernetes stacks. 📅 25 June | 12:00-12:35 BST | OSFF London Catch it live: buff.ly/OYE5Uad

Your Kubernetes fleet may be running at 30% utilization, and in financial services, that's often by design. 5-Spot, RBC Capital Markets' first open-source contribution to FINOS, is built to change that. It transforms Cluster API into a spot-aware scheduling substrate, helping organizations reclaim idle capacity without compromising cluster health, compliance requirements, or operational guardrails. Join Erick Bourgeois, Head of Kubernetes Platform Engineering at RBC Capital Markets, on June 24 for a hands-on workshop where you'll learn how to: • Deploy 5-Spot on a live k0smotron-managed cluster • Identify and classify spot-eligible workloads • Explore the architectural decisions behind running spot capacity safely in regulated environments If you're a platform engineer, cloud architect, or SRE responsible for Kubernetes at scale, especially in regulated industries, this session is worth your morning. Special thanks to ControlPlane, Erick Bourgeois, and RBC Capital Markets for helping bring this workshop to the community. Save your seat: buff.ly/aUNPe4s

我最喜欢的环境切换脚本软件controlplane，因为最近macOS频繁提示从28开始将不支持老app想自己写一个，跑去官网一看作者说他要重写了。 controlplaneapp.com

🏎️ Vocabulary Series #4: Control Plane As AI systems become more capable, most of the attention continues to go toward the agents themselves. Which model should you use? How autonomous should the agent be? What tasks can it perform? Those are important questions, but they miss a much bigger architectural shift that is happening. The future of AI systems will not be defined by individual agents. It will be defined by the control planes that manage them. Formula 1 provides a useful example. From the outside, it looks like the driver is in control. In reality, the driver is just one component in a much larger system. Engineers monitor telemetry, strategists analyze race conditions, and team leadership makes decisions about risk, timing, and execution. The driver executes, but the team coordinates. The same principle applies to AI. As organizations deploy more agents across engineering, operations, security, and support, they need a central layer responsible for governance, approvals, routing, policy enforcement, observability, and decision making. Without that layer, every agent becomes another isolated tool. With it, agents become part of a coordinated organizational system. This is what a control plane does. It sits above the execution layer and provides the visibility and governance required to operate AI at scale. It determines what can run, when it can run, who can approve it, which models should be used, and how outcomes are monitored across the organization. The conversation around AI is gradually moving from building smarter agents to managing fleets of agents. When that happens, the control plane becomes more important than any individual model. Just like in Formula 1, the winning advantage rarely comes from a single driver. It comes from the system that coordinates the entire operation. #AgenticAI #ControlPlane #PlatformEngineering #SoftwareEngineering #AIAgents

We’re not building apps anymore — we’re architecting the CONTROL PLANE of the Machine Economy 🧠⚙️🤖 Where sovereignty isn’t promised… it’s engineered at the protocol layer. This is the shift from systems that run to systems that govern themselves 🌐🔐 From coordination chaos → to sovereign machine order. The Machine Economy doesn’t scale on hype. It scales on control planes, verifiable logic, and autonomous execution 🔥 This is infrastructure for a world that doesn’t wait for permission. #MachineEconomy #ControlPlane #AI #Web3 #AutonomousSystems #DePIN #CryptoAI #FutureIsNow

Sandbox Probe is a great tool to find holes in your coding agent sandboxes. Created by Andrew Martin ( @sublimino ) and his team at ControlPlane - github.com/controlplaneio/sa…

We’re filming live at the Gartner Security & Risk Management Summit, and Victor Hernandez, our Senior Solution Architect just tackled a critical question for every security and operations leader: “What’s the one thing your team can’t afford to get wrong when collaboration becomes part of your control plane?” Victor is onsite throughout the Summit, so if you’re attending, stop by Booth 303 to continue the conversation, ask questions, or dive deeper into how secure, self‑hostable collaboration strengthens your control plane. Watch the video and come meet Victor at the booth tomorrow. #GartnerSecurity #SRMSummit #SecureCollaboration #MissionCritical #CyberSecurity #ControlPlane

Frontier models like #Mythos & #Daybreak excel at #securityreasoning, but discovery is only half the battle. @shail_manjrekar breaks down why Operational #ControlPlane is the missing link to turn intelligence into governed action. "A model can tell you a vulnerability exists, but it doesn't know your business criticality or rollback paths." @TheFabrixAI bridges gap between frontier reasoning & safe enterprise execution. 🔗fabrix.ai/blog/the-security-…

Learn @cloudidr approach of building an AI FinOps Controlplane, helping teams track cost by model, team, agent, and request, apply budget guardrails, and route traffic to the cheapest capable model without code changes. Watch on @cloudnativefm youtube.com/live/eytMDFkBtEQ

We are now Live learning the @cloudidr approach of building an AI FinOps Controlplane, helping teams track cost by model, team, agent, and request, apply budget guardrails, and route traffic to the cheapest capable model without code changes. Join now: youtube.com/live/eytMDFkBtEQ

Ayer un colega de infra automatizando unos bonds con ia revento un cluster y tiro todo un controlplane de rhosp, se perdieron accesos completos y hubo intermitencia de servicio…existe un mundo donde el criterio se paga caro todavia (no se por cuanto tiempo)

ControlPlane launches enterprise support for OpenBao as IBM's $6.4bn HashiCorp acquisition increases demand for open source Vault alternatives. #OpenBao #HashiCorp #IBM #OpenSource #CloudSecurity techday.com.au/story/control…

Partnership Alert: ControlPlane unveils enterprise support for OpenBao OpenBao gains enterprise-scale security alongside Vault alternatives as demand spikes from major IBM-HashiCorp deal. Are you ready to switch to open-source safety at scale? 🔒🛡️ #CyberSecurity #InfoSec #Sa…