Podcasts about MCP

Author here! This an older, more cosmic underwater horror story of mine from two years ago, a two parter that got a lot of positive reaction on Reddit. It has some flaws, but I hope you enjoy it, and the upcoming second part as much as you did my Abandoned Ship story, Exploding Whale and Crater Lake stories MCP has done. And also, I hope you caught the tributes to horror movie characters, directors and writers with names like Carpenter, Alten, King and Windows.

AWS Morning Brief for the week of March 2nd, with Corey Quinn. Links:Amazon Aurora DSQL launches Playground for interactive database exploration Amazon Redshift Serverless introduces 3-year Serverless ReservationsAmazon S3 now provides AWS source region information in server access logs AWS Compute Optimizer now applies AWS-generated tags to EBS snapshots created during automationAWS Lambda Durable Execution SDK for Java now available in Developer PreviewAWS Trusted Advisor now delivers more accurate unused NAT Gateway checks powered by AWS Compute Optimizer6,000 AWS accounts, three people, one platform: Lessons learnedPetabyte-Scale Cost Optimization: How a Video Hosting Platform Saved 70% on S3Transform live video for mobile audiences with AWS Elemental Inference Migrate Amazon EC2 to ECS Express Mode using Kiro CLI and MCP servers AI-augmented threat actor accesses FortiGate devices at scaleAWS posts “correct the record” piece on AI bot outage

In this episode we cover all of the news, spoilers, and reveals for the new game system, Marvel Crisis Protocol Alliances. We end the episode with a discussion about our recent MCP games, projects, and afflation goals.Fury's Finest is a podcast and resource devoted to the discussion of the tabletop game ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Marvel Crisis Protocol⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.___________________________________Fury's Finest is supported by our wonderful patrons on Patreon. If you would like to help the show go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠patreon.com/furysfinest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and pledge your support. Fury's Finest Patrons directly support the show and its growth by helping pay our monthly and annual fees, while contributing to future projects and endeavors.Check out our Fury's Finest apparel and merchandise on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TeePublic⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - https://www.teepublic.com/user/pleasestandby___________________________________Twitch I ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠twitch.tv/furysfinest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter I ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@FurysFinestCast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram I ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@FurysFinest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook I ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Fury's Finest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube I  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Fury's Finest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ l⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ l⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Google Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠___________________________________Thanks to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Approaching Nirvana⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for our music.Help spread the word of our show.  Subscribe, rate, and review!Send feedback, Marvel thoughts, and show inquires to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠FurysFinest@gmail.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Fury's Finest is hosted by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jesse Eakin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Chris Bruffett⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

Welcome to Episode 422 of the Microsoft Cloud IT Pro Podcast. In this episode, Scott and Ben discuss their growing use of   in their daily workflows, particularly Claude Code, GitHub Copilot CLI, and Gemini CLI. They explore how these command-line interfaces offer powerful ways to interact with local files and MCP servers beyond traditional desktop AI chat interfaces. They share how they are using these tools in their day-to-day roles to perform different tasks and accelerate their workflows. Your support makes this show possible! Please consider becoming a premium member for access to live shows and more. Check out our membership options. Show Notes Claude Code overview Using Claude in PowerPoint Create custom subagents Microsoft Work IQ CLI (Public Preview) https://github.com/obra/superpowers How to Use Claude Code: A Guide to Slash Commands, Agents, Skills, and Plug-ins Gemimi CLI overview Github Copilot overview About the sponsors Would you like to become the irreplaceable Microsoft 365 resource for your organization? Let us know!

Gm! In today's episode we have a 0xResearch crosspost where they were joined by Lucas Bruder, Co-Founder of Jito Labs to discuss Jito's BAM block builder on Solana, highlighting transparency, verifiability, and application-controlled execution. They also cover market structure, stake adoption, MCP, slot time reductions, and JitoSOL's ETF efforts. Enjoy! -- Follow Lightspeed: ⁠https://twitter.com/Lightspeedpodhq⁠ Follow Jito Labs: https://x.com/jito_labs Follow Lucas Bruder: https://x.com/buffalu__ Follow Sam: https://x.com/minnus Follow Carlos: https://x.com/0xcarlosg Follow Boccaccio: https://x.com/salveboccaccio Follow Danny: https://x.com/defi_kay_ Join the Lightspeed Telegram: ⁠https://t.me/+QHlbNTNS4gc1ZTVh -- Join us at DAS (Digital Asset Summit) in New York City this March!  Use the link below to learn more, and use code LIGHTSPEED200  to get $200 off your ticket! See you there! Learn more + get your ticket here: https://blockworks.co/event/digital-asset-summit-nyc-2026 -- Get top market insights and the latest in crypto news. Subscribe to Blockworks Daily Newsletter: https://blockworks.co/newsletter/ -- Timestamps: (0:00) Introduction (1:54) Why Jito Built BAM (5:50) Application-Controlled Execution Explained (11:30) MCP and Solana's Future (15:56) BAM Adoption and Stake Growth (33:13) Cutting Slot Times on Solana (40:28) JitoSOL and the ETF Push (47:09) AI, Products, and the Road Ahead (50:40) Closing Comments -- Disclaimers: Lightspeed was kickstarted by a grant from the Solana Foundation. Nothing said on Lightspeed is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Danny, and our guests may hold positions in the companies, funds, or projects discussed.

Wes McKinney on the mythical agent-month, install Peon Ping to employ a Peon today, Andreas Kling explains why Ladybird is adopting Rust, Cloudflare has a new MCP server that's quite efficient, and Elliot Bonneville thinks the only moat left is money.

Planet Nix and SCaLE are just days away, and we're getting a head start with two guests, the tech, and the trends shaping open source. Our trip starts here!Sponsored By:Jupiter Party Annual Membership: Put your support on automatic with our annual plan, and get one month of membership for free! Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love. Support LINUX UnpluggedLinks:

Josh chats with Brad Axen from Block about his creation Goose as well as the Agentic AI Foundation (AAIF). I am quite skeptical of many AI claims, but Brad has a very pragmatic view about where things are today and where we might see them head. Donating Goose to the AAIF is great news as well as seeing MCP and AGENTS.MD in the foundation. We discuss how to deal with the problem of raising up junior developers, challenges of AI PRs, and some thoughts on how to get started if you're interested in AI development. The show notes and blog post for this episode can be found at https://opensourcesecurity.io/2026/2026-02-goose-aaif-brad-axen/

In this episode, host Sandy Vance and Ted Dinsmore discuss the ever-evolving role of AI in healthcare, industry trends, challenges, and solutions. They explore the concept of agentic AI and the Model Context Protocol (MCP), which aims to enhance data integration and efficiency in healthcare systems. They also highlight the importance of building trust in AI solutions, particularly in rural healthcare settings. Listen in to learn how SphereGen is addressing these challenges through innovative AI implementation approaches. In this episode, they talk about: Latest AI trend: agentic AI and bots, and MCP in the healthcare industry MCP allows us to speed up that integration Trust is a huge issue when you're having an impact on the patient The benefits of using MCP for hospitals and patients The concerns about the changes and cuts to rural healthcare The most common use cases when transitioning: eligibility, prior authorization, and denials management The effects on how healthcare systems are doing business with EHRs Next big use cases and what's coming up next Solving challenges in rural healthcare over the next few years How rural healthcare and homecare are tied At the end of the day, it's all about how AI can help free up time for people A Little About Ted: Ted Dinsmore is the President of SphereGen Technologies, located in New Haven, Connecticut, Toronto, Canada, and Pune, India. SphereGen is a software consulting firm that develops and supports custom software solutions for clients in AI and Automation, Application Development, and Extended Reality (AR, VR, MR). His experience in the world of IT spans over 30 years. When Ted started his first consulting firm, he became invested in developing and supporting Microsoft solutions for large multinational companies. Wanting to stay at the forefront of emerging technologies, his current company, SphereGen, embraces the world of AI/Automation and Mixed Reality (MR). SphereGen focuses on improving processes for healthcare organizations by leveraging innovative technologies, along with partners UiPath and Microsoft, to solve business problems.

Wes McKinney on the mythical agent-month, install Peon Ping to employ a Peon today, Andreas Kling explains why Ladybird is adopting Rust, Cloudflare has a new MCP server that's quite efficient, and Elliot Bonneville thinks the only moat left is money.

Wes McKinney on the mythical agent-month, install Peon Ping to employ a Peon today, Andreas Kling explains why Ladybird is adopting Rust, Cloudflare has a new MCP server that's quite efficient, and Elliot Bonneville thinks the only moat left is money.

OpenClaw is a self-hosted AI agent daemon that executes autonomous tasks through messaging apps like WhatsApp and Telegram using persistent memory. It integrates with Claude Code to enable software development and administrative automation directly from mobile devices. Links Notes and resources at ocdevel.com/mlg/mla-29 Try a walking desk - stay healthy & sharp while you learn & code Generate a podcast - use my voice to listen to any AI generated content you want OpenClaw is a self-hosted AI agent daemon (Node.js, port 18789) that executes autonomous tasks via messaging apps like WhatsApp or Telegram. Developed by Peter Steinberger in November 2025, the project reached 196,000 GitHub stars in three months. Architecture and Persistent Memory Operational Loop: Gateway receives message, loads SOUL.md (personality), USER.md (user context), and MEMORY.md (persistent history), calls LLM for tool execution, streams response, and logs data. Memory System: Compounds context over months. Users should prompt the agent to remember specific preferences to update MEMORY.md. Heartbeats: Proactive cron-style triggers for automated actions, such as 6:30 AM briefings or inbox triage. Skills: 5,705+ community plugins via ClawHub. The agent can author its own skills by reading API documentation and writing TypeScript scripts. Claude Code Integration Mobile to Deploy Workflow: The claude-code-skill bridge provides OpenClaw access to Bash, Read, Edit, and Git tools via Telegram. Agent Teams: claude-team manages multiple workers in isolated git worktrees to perform parallel refactors or issue resolution. Interoperability: Use mcporter to share MCP servers between Claude Code and OpenClaw. Industry Comparisons vs n8n: Use n8n for deterministic, zero-variance pipelines. Use OpenClaw for reasoning and ambiguous natural language tasks. vs Claude Cowork: Cowork is a sandboxed, desktop-only proprietary app. OpenClaw is an open-source, mobile-first, 24/7 daemon with full system access. Professional Applications Therapy: Voice to SOAP note transcription. PHI requires local Ollama models due to a lack of encryption at rest in OpenClaw. Marketing: claw-ads for multi-platform ad management, Mixpost for scheduling, and SearXNG for search. Finance: Receipt OCR and Google Drive filing. Requires human review to mitigate non-deterministic LLM errors. Real Estate: Proactive transaction deadline monitoring and memory-driven buyer matching. Security and Operations Hardening: Bind to localhost, set auth tokens, and use Tailscale for remote access. Default settings are unsafe, exposing over 135,000 instances. Injection Defense: Add instructions to SOUL.md to treat external emails and web pages as hostile. Costs: Software is MIT-licensed. API costs are paid per-token or bundled via a Claude subscription key. Onboarding: Run the BOOTSTRAP.md flow immediately after installation to define agent personality before requesting tasks.

Zach is joined by Kaitie Pait and Kendal Giacomini to talk about the supportive community in the MCP facebook group, and how Kaitie asked for and received some help with unit pacing in a post there Show Notes MCP Podcast episode 171: Resetting MCP (Kendal's previous appearance on the MCP Podcast) Kaitie's post in the Facebook group Soundtrap Connect with Kaitie by email at kaitlin.pait@modernclassrooms.org Connect with Kendal on Goodreads and by email at kendal.giacomini@modernclassrooms.org Contact us, follow us online, and learn more: Email us questions and feedback at: podcast@modernclassrooms.org Listen to this podcast on Youtube Modern Classrooms: @modernclassproj on Twitter and facebook.com/modernclassproj Kareem: @kareemfarah23 on Twitter Toni Rose: @classroomflex on Twitter and Instagram The Modern Classroom Project Modern Classrooms Online Course Take our free online course, or sign up for our mentorship program to receive personalized guidance from a Modern Classrooms mentor as you implement your own modern classroom! The Modern Classrooms Podcast is edited by Zach Diamond: @zpdiamond on Twitter and Learning to TeachSpecial Guests: Kaitie Pait and Kendal Giacomini.

An airhacks.fm conversation with Kabir Khan (@kabirkhan) about: Discussion about the A2A (Agent-to-Agent) protocol initiated by Google and donated to the Linux Foundation, the A2A Java SDK reference implementation using quarkus, the Java SDK development accepted by Google, comparison of python and Java expressiveness and coding practices, the concept of an agent as a stateful process versus a tool as a stateless function call, the agent card as a JSON document advertising capabilities including supported protocols and descriptions and input/output modes and examples, the three wire protocols supported: JSON RPC and HTTP+JSON (REST) and grpc, the proto file becoming the single source of truth for the upcoming 1.0 spec, the facade/adapter pattern for the unified client across protocols, the agent executor interface with request context and event queue parameters, the distinction between simple message interactions and long-running multi-turn tasks, tasks as Java Records containing conversation history with messages and artifacts, message parts including text parts and data parts and file parts, task lifecycle with task IDs and context IDs for stateful conversations, the event queue as internal plumbing for propagating task updates, the separation between spec package (wire protocol entities) and server package (implementation details), the task store as a CRUD interface with in-memory default and database-backed implementations in extras, replicated queue manager using microprofile reactive messaging with Kafka for kubernetes environments, building A2A agents without any LLM involvement for simple use cases like backup systems, the role of LLMs in creating prompts from task messages and context, the agentic loop and the challenge of deciding when an agent's work is complete, the relationship between MCP (Model Context Protocol) for tool access and A2A for agent-to-agent communication, the possibility of wrapping agent calls as MCP tools, memory management considerations with short-term and long-term memory and prompt size affecting LLM quality, the distinction between the bare reference implementation and Quarkus-specific enhancements like annotations and dependency injection, upcoming 1.0 release with standardized Java records for all API classes and improved JavaDoc, protocol extensions including the agent payment protocol and GUI snippet extensions using template engines, authentication support with OAuth2 tokens and API keys and bearer tokens, the authenticated agent card containing more information than the public agent card, authorization hooks being discussed for task-level access control, the API and SPI segregation suggestion for better clarity between spec and implementation Kabir Khan on twitter: @kabirkhan

Jim Love discusses how rapid adoption of agentic AI is repeating the industry pattern of shipping technology without security, citing issues like vulnerabilities in Anthropic's MCP and insecure open-source agent tools. He interviews Ido Shlomo, co-founder and CTO of Token Security, who argues AI agents are fundamentally hard to secure because they are non-deterministic, have infinite input/output space, and often require broad permissions to be useful.  Cybersecurity Today  would like to thank Meter for their support in bringing you this podcast. Meter delivers a complete networking stack, wired, wireless and cellular in one integrated solution that's built for performance and scale.  You can find them at Meter.com/cst Shlomo proposes focusing security on access, identity, attribution, least privilege, and auditability rather than trying to filter prompts and outputs, and describes Token's "intent-based permission management" approach that maps agents and sub-agents as non-human identities tied to their purpose and allowed actions. The conversation covers real-world risks such as developer tools like Claude Code running with extensive access, widespread over-provisioning of admin permissions and API keys, exposure of unencrypted local token files, and misconfigurations that leak data publicly. Shlomo recommends organizations build governance processes for agents—discovery/inventory, boundary setting, continuous monitoring, and secure decommissioning—and says AI is needed to help police AI. He also highlights emerging trends like agent teams and multi-day autonomous tasks, and notes Token Security is a top-10 finalist in the RSA Innovation Sandbox 2026, planning to present an intent-and-access-focused security model for AI agents. 00:00 Sponsor: Meter's integrated networking stack 00:19 Why agentic AI security is breaking (MCP & open-source chaos) 02:53 Meet Token Security: practical guardrails for AI agents 04:57 Why you can't just ban agents at work (shadow AI reality) 06:24 Tel Aviv's cybersecurity pipeline: gaming, military, and startups 08:57 Why AI/agents are fundamentally hard to secure (new OS + 'human spirit') 13:44 Trust, autonomy, and permissions: managing the blast radius 18:17 Real-world exposure: Claude Code and the developer identity attack surface 20:16 A workable approach: treat agents as untrusted processes with identity + least privilege 22:33 Zero Trust for Agents: Access ≠ Permission to Act 23:27 Token's "Intent-Based Permission Management" Explained 25:29 Building the Identity Map: Tracing What Agents Touch 26:52 The Secret Sauce: Using AI to Secure AI in Real Time 28:10 Real-World Case: 1,500 Agents and Wildly Over-Provisioned Access 30:57 CUA 'Computer-Use' Agents: Exciting, Personal… and Terrifying 34:44 Secure-by-Default & Sandboxing: Fixing 'Always Allow' Dark Patterns 35:36 What Security Teams Should Do Now: Inventory, Boundaries, Governance 37:59 What's Next: Agent Teams and Multi-Day Autonomous Work 40:10 Tony Stark Vision: Agents That Improve the Human Experience 41:02 RSA Innovation Sandbox: Token's Big Bet on Intent + Access 43:01 Wrap-Up, Audience Q&A, and Sponsor Message

How can you move your MCP tools beyond plain text? How do you add interactive UI components directly inside chat conversations? This week on the show, Den Delimarsky from Anthropic joins us to discuss MCP Apps and interactive UIs in MCP.

In today's episode we are joined by Lucas Bruder, Co-Founder of Jito Labs to discuss Jito's BAM block builder on Solana, highlighting transparency, verifiability, and application-controlled execution. We also cover market structure, stake adoption, MCP, slot time reductions, and JitoSOL's ETF efforts. Thanks for tuning in! As always, remember this podcast is for informational purposes only, and any views expressed by anyone on the show are solely their opinions, not financial advice. -- Follow Blockworks Research: https://x.com/blockworksres Follow Jito Labs: https://x.com/jito_labs Follow Lucas Bruder: https://x.com/buffalu__ Follow Sam: https://x.com/minnus Follow Carlos: https://x.com/0xcarlosg Follow Boccaccio: https://x.com/salveboccaccio -- Join us at DAS (Digital Asset Summit) in New York City this March! Use the link below to learn more, and use code 0X200 to get $200 off your ticket! See you there! Learn more + get your ticket here: https://blockworks.co/event/digital-asset-summit-nyc-2026 -- Subscribe on YouTube: https://bit.ly/3foDS38 Subscribe on Apple: https://apple.co/3SNhUEt Subscribe on Spotify: https://spoti.fi/3NlP1hA Get top market insights and the latest in crypto news. Subscribe to Blockworks Daily Newsletter: https://blockworks.co/newsletter/ -- Timestamps: (0:00) Introduction (1:07) Why Jito Built BAM (5:03) Application-Controlled Execution Explained (10:43) MCP and Solana's Future (15:09) BAM Adoption and Stake Growth (32:26) Cutting Slot Times on Solana (39:41) JitoSOL and the ETF Push (46:22) AI, Products, and the Road Ahead (49:53) Closing Comments -- Check out Blockworks Research today! Research, data, governance, tokenomics, and models – now, all in one place Blockworks Research: https://www.blockworksresearch.com/ Free Daily Newsletter: https://blockworks.co/newsletter -- Disclaimer: Nothing said on 0xResearch is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Boccaccio, Danny, and our guests may hold positions in the companies, funds, or projects discussed.

CoreStory is building code intelligence platforms that address the fundamental limitation of today's coding agents: their inability to navigate complex enterprise codebases. While foundation models excel at greenfield development, they fail at real-world engineering tasks in systems spanning millions of lines of code. CoreStory's context layer delivers a 44% improvement on SWE-bench, the industry's standard benchmark for measuring coding agent effectiveness on actual GitHub issues. In this episode of BUILDERS, I sat down with Anand Kulkarni, CEO of CoreStory, to explore how his team is enabling the shift to AI-native engineering and seeding the category of spec-driven development across Microsoft, GitHub, and Amazon. Topics Discussed: Building with GPT-3 API 18 months before ChatGPT went public Why even GPT-5 and Opus 4.5 struggle with enterprise codebases on SWE-bench The narrative shift required when selling AI pre- and post-ChatGPT CoreStory's 44% improvement in coding agent performance through context intelligence How "spec-driven development" got adopted by Microsoft, GitHub, and Amazon without formal analyst relations The parallel between JIRA monetizing Agile and CoreStory enabling AI-native engineering Three-channel distribution: direct enterprise, coding agent partnerships via MCP, and hyperscaler/GSI routes Why specs become the source of truth while code becomes disposable in the AI era GTM Lessons For B2B Founders: Match your narrative precision to technical depth: CoreStory deploys three distinct positioning strategies based on audience sophistication. For AI practitioners tracking benchmarks, they lead with "44% SWE-bench improvement"—a metric that immediately signals meaningful progress on the hardest problem in the space. For engineering leaders aware of AI tooling but not deep in the research, they focus on velocity gains and ROI metrics. For executives, they describe reverse-engineering codebases into machine-readable specs. The key insight: technical audiences dismiss vague value props, while non-technical audiences get lost in benchmark details. Map your positioning to how your audience measures success in their world. Seed category language through earned adoption, not manufactured consensus: Anand initially called their approach "requirements-driven development" before simplifying to "spec-driven development." Rather than pitching analysts, they used the term consistently in customer conversations, gave talks at GitHub Universe, and shipped demos showing the workflow. When customers naturally adopted the language and community leaders began using similar terminology independently, Microsoft and GitHub followed with their own implementations (like GitHub's SpecKit). The lesson: category language sticks when practitioners choose to use it because it clarifies their work, not because a vendor pushed it. Focus on customer adoption as proof of concept before seeking broader market validation. Position against emergent practices, not just incumbent products: CoreStory doesn't position against legacy code analysis tools—they position as the enabler of AI-native engineering, the discipline that will displace Agile. Anand's insight from watching JIRA's success: "People don't love JIRA. What they love is Agile as a way to move away from waterfall." CoreStory is betting that 10x velocity gains from AI-native practices will drive the same categorical shift. When you're early in a technology wave, attach to the practice change (how teams will work differently) rather than feature comparisons with existing tools. Movements create markets. Design channel strategy around customer problem awareness: CoreStory's three channels map to different stages of buyer sophistication. Direct enterprise comes from teams already deep in AI engineering who've hit the context limitation wall. Coding agent partnerships (via MCP integration with tools like Cognition and Factory) serve builders wanting better AI tooling who haven't diagnosed the context problem yet. Hyperscalers and GSIs distribute into modernization and maintenance projects where AI enablement is emerging as a requirement. Each channel serves a distinct buyer journey stage. Don't force one go-to-market motion—design multiple paths based on where different customer segments are in understanding the problem you solve. Navigate pre-legitimacy markets by hiding the breakthrough: Before ChatGPT, selling anything AI-driven faced immediate skepticism about whether it was "real" or just smoke and mirrors. Anand couldn't lead with AI without triggering disbelief. CoreStory focused on delivered outcomes—"here's what you'll be able to do"—with AI as the mechanism, not the message. Post-ChatGPT, the challenge flipped: everyone expects AI, but now the differentiation question becomes harder. If you're building on emerging technology before market consensus forms, deemphasize the technology until buyers have context to evaluate it. Once the market validates the technology category, shift to demonstrating your specific technical advantage within it. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

In this video David speaks to Peter Bailey (SVP and GM of Cisco's Security business). AI agents are moving fast inside enterprises, and CISOs are hitting the brakes for one reason: the attack surface is expanding at machine speed. In this interview, we break down how agentic AI changes security, why MCP servers and agent tool access create new risks, and what a zero trust approach looks like when the “user” is a non-deterministic agent. We cover real-world problems like shadow MCP servers, agents touching sensitive systems and PII, and why traditional perimeter controls and firewalls are not enough when traffic is encrypted and actions happen too quickly downstream. You'll also hear what Cisco is doing across the AI lifecycle: AI Defense for model scanning, provenance and guardrails, plus new protections focused on agent identity, dynamic authorization, behavior monitoring, and revocation. On the networking side, we discuss how SD-WAN and secure access (SASE) can add visibility and policy control for AI usage, including prioritizing latency-sensitive AI traffic while still enforcing security. If you're a security engineer, network engineer, or CISO trying to move from AI hype to safe deployment, this video gives you a practical mental model and the controls to start building now. Big thank you to ‪@Cisco‬ for sponsoring this video and for sponsoring my trip to Cisco Live Amesterdam. // Peter Baily' SOCIALS // LinkedIn: / peterhbailey Guest Bio: https://newsroom.cisco.com/c/r/newsro... // David's SOCIAL // Discord: discord.com/invite/usKSyzb Twitter: www.twitter.com/davidbombal Instagram: www.instagram.com/davidbombal LinkedIn: www.linkedin.com/in/davidbombal Facebook: www.facebook.com/davidbombal.co TikTok: tiktok.com/@davidbombal YouTube: / @davidbombal Spotify: open.spotify.com/show/3f6k6gE... SoundCloud: / davidbombal Apple Podcast: podcasts.apple.com/us/podcast... // MY STUFF // https://www.amazon.com/shop/davidbombal // SPONSORS // Interested in sponsoring my videos? Reach out to my team here: sponsors@davidbombal.com // MENU // 0:00 - Coming Up 0:30 - Introduction 01:15 - CISOs Problems with AI 02:35 - Real Issues with AI Agents 04:29 - Growth of the Attack Surface 05:34 - Concern of Poisoned AI and MCP 08:09 - What is the Kill-chain 10:16 - AI with Built-in Security 11:56 - Best Practises for AI Security 14:08 - Cisco Innovations for AI 16:48 - Cisco's Red Team for own AI 18:27 - Secure AI in Public Places 20:09 - Should You get into Cyber Security 21:26 - Advice To Your Younger Self 22:29 - Outro Please note that links listed may be affiliate links and provide me with a small percentage/kickback should you use them to purchase any of the items listed or recommended. Thank you for supporting me and this channel! Disclaimer: This video is for educational purposes only. #cisco #ciscoemea #ciscolive

This episode is a full “build a business in 40 minutes” demo showing how AI collapses what used to take teams (creative production + sales ops + support) into a handful of prompts. Samruddhi generates a high-production video ad in Google AI Studio using a JSON-style prompt framework, then spins up a working voice sales/support agent in Vapi via Claude Desktop + MCP—so the agent is created from a single prompt instead of clicking through the UI. The conversation also covers why “interfaces matter less” in an agent-first world, why workflow tools (like n8n) still have a role, and how memory layers like Mem0 unify context across channels (email/WhatsApp/etc.) so you can take actions without hunting.Timestamps0:00 — “Single person billion-dollar company” belief + AI driving 10x execution speed1:57 — Plan: create the ad in Google AI Studio (Veo 3.1) + build a voice agent using Vapi MCP via Claude Desktop2:42 — Smithery: marketplace for MCP servers3:39 — MCP for non-technical listeners: “like an API, but agents use it to talk to external services”4:22 — Inside Vapi MCP: tool list = APIs the agent can choose from5:06 — AI Studio setup: video generation playground + select Veo 3.16:16 — JSON prompting framework begins (structure → production-level output)6:28 — Keys: description, style, camera, lighting, environment, elements, motion, ending, text9:05 — Prompts/scripts can be AI-generated (humans provide guardrails)10:41 — Need an API key to generate videos in AI Studio10:54 — Ad review: strong realism; last segment looks AI-ish → iterate prompt13:05 — Install Vapi MCP via npx from Smithery + add Vapi API key13:46 — Claude Desktop: Vapi MCP appears under Connectors/Tools (not Claude web)14:05 — Prompt the agent build: “Fresh Pause” + role, tasks, FAQs, call flows18:23 — Testing: “Talk to assistant” starts a live call simulation19:20 — Deployment: assign a phone number; Vapi provides free/test numbers (up to a limit)21:57 — Mem0 / Supermemory: memory layer across apps/agents to keep context24:13 — Why memory layers help: fewer MCPs → less slowdown/hallucination; no need to specify where to search26:36 — MCPs + slide decks: mention of Gamma MCP via Claude27:34 — Future of n8n/Zapier: they persist, but prompting increasingly generates workflows31:38 — Prediction market trading algos (Kalshi/Polymarket) + AI improves speed/decision-making36:02 — Closing vision: help orgs 10x execution speed, especially non-technical leaders (40+) with domain expertiseTools & technologies mentionedGoogle AI Studio (Video Generation Playground) — Generate an 8-second video ad.Veo 3.1 — Google video model used for “production-level” output.JSON Prompting Framework — Structured key/value prompts for story, visuals, camera, lighting, motion, ending frame.Claude Desktop — Runs connectors/tools (including MCP servers).MCP (Model Context Protocol) — Lets agents call external services/tools based on intent.Smithery — Directory/marketplace for MCP servers.Vapi — Voice agent platform; create agents + assign phone numbers.Vapi MCP Server — Enables Claude to operate Vapi via prompts (create/list/configure).npx — Installs MCP server quickly from the terminal.API Keys — Required for AI Studio generation + Vapi authentication.Mem0 / Supermemory — Cross-channel memory layer to retrieve context automatically.Knowledge Graph — Underlying structure for semantic retrieval across interactions.Glean — Referenced as a comparison point for search/context retrieval.Gamma MCP — Example of generating slide decks via MCP.n8n / Zapier — Workflow automation tools discussed in an MCP-first future.OpenClaw — Mentioned as agent tooling that can help with steps like obtaining API keys.Kalshi / Polymarket — Prediction markets referenced in the trading/AI speed discussion.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

Gm! In this episode we discuss Blockworks' new Solana-focused Lightspeed IR platform and a report on Solana block building. We examine the rivalry between Jito BAM and Harmonic, impacts on transaction ordering, fees, market structure, validator clients, and the push toward protocol-level solutions like MCP and application-controlled execution.Enjoy! -- Follow Lightspeed: ⁠https://twitter.com/Lightspeedpodhq⁠ Follow Sam: https://x.com/minnus Follow Carlos: https://x.com/0xcarlosg Follow Danny: https://x.com/defi_kay_ Join the Lightspeed Telegram: ⁠https://t.me/+QHlbNTNS4gc1ZTVh -- Join us at DAS (Digital Asset Summit) in New York City this March!  Use the link below to learn more, and use code LIGHTSPEED200  to get $200 off your ticket! See you there! Learn more + get your ticket here: https://blockworks.co/event/digital-asset-summit-nyc-2026 -- Get top market insights and the latest in crypto news. Subscribe to Blockworks Daily Newsletter: https://blockworks.co/newsletter/ -- Timestamps: (0:00) Introduction (3:42) Lightspeed IR Platform Launch (6:40) Block Building on Solana (12:28) Jito Bam vs. Harmonic: Architecture Breakdown (16:51) MEV, Fees, and Market Structure Impacts (34:04) MCP and Solana's Path Forward (48:49) What Happened to Jito and Harmonic? (55:55) Alpenglow & MCP Timeline (59:03) Closing Comments -- Disclaimers: Lightspeed was kickstarted by a grant from the Solana Foundation. Nothing said on Lightspeed is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Danny, and our guests may hold positions in the companies, funds, or projects discussed.

In episode 105, we finally get the stream dialed and dive straight into hands‑on Bitcoin mining and open-source hardware updates. We share the latest on Ember One: a sneaky IO voltage domain bug uncovered by Mujina dev Ryan led to a desk‑side hardware fix that's now pushing ~2 TH/s (target is 3.6 TH/s across 12 chips with proper cooling). We unpack chip and hashboard design lore—from stacked voltage domains and reliability in long chains to the insider politics at big silicon shops like Intel. We talk why selling chips openly matters, how spec sheets unlock real builder momentum, and why third‑party system builders (think Epic Blockchain) can grease the skids between chipmakers and end products.We cover Mujina's trajectory toward a universal, Linux‑first, open firmware for miners—auto‑detect dreams vs config realities—and near‑term support for Ember One's Intel boards and existing Antminers. We riff on home‑miner UX, remote monitoring, and agent/LLM tooling (cron‑job‑with‑superpowers, heartbeats, MCP integrations) to tune, alert, and manage miners. There's buzz around FutureBit's Apollo 3 (likely Auradine chips), open vs lawyered licenses, and the path from FPGA teaching rigs to community‑designed ASICs. We celebrate community hashing on the 256F HydroPool hash‑dash, solo‑block wins, and Heat Punk Summit prep (immersion hot tub included). Plus, a call to action: support developer freedom at change.org/billandkeonne. It's a dense, builder‑first session on chips, firmware, agents, and bringing practical hashrate‑heat products to life.

MY NEWSLETTER - https://nikolas-newsletter-241a64.beehiiv.com/subscribeJoin me, Nik (https://x.com/CoFoundersNik), as I interview Richard Marmorstein (https://x.com/@twitchard). In this episode, Richard shares some fascinating ways he's leveraging AI in both his personal life, like creating a custom storybook using Google AI Studio for his son, and professionally, showcasing the expressive text-to-speech capabilities of Hume AI.We also dive into practical business applications of AI voice technology and explore the crucial differences between general language models and reasoning models like those from OpenAI. Plus, Richard gives us a peek into how he uses AI tools like Claude and ChatGPT to enhance his workflow as a software developer.Questions This Episode Answers:• What is an MCP and how does it enable tool use with language models?• What makes Hume AI's text-to-speech model different and what are its key use cases beyond creative content?• What's the difference between using a general model like ChatGPT 4.0 and a reasoning model?• How can AI assist with coding tasks and serve as a pair programmer?• What are some unconventional ways to repurpose existing content, like turning a blog into a podcast using AI?Enjoy the conversation!__________________________Love it or hate it, I'd love your feedback.Please fill out this brief survey with your opinion or email me at nik@cofounders.com with your thoughts.__________________________MY NEWSLETTER: https://nikolas-newsletter-241a64.beehiiv.com/subscribeSpotify: https://tinyurl.com/5avyu98yApple: https://tinyurl.com/bdxbr284YouTube: https://tinyurl.com/nikonomicsYT__________________________This week we covered:00:00 Revolutionizing Conversational AI and TTS04:20 Exploring Google's AI Studio and Image Generation11:32 Innovations in Text-to-Speech Technology15:47 Practical Applications of AI in Content Creation20:59 Understanding AI Models and Their Use Cases

The OpenClaw bot asks Benedicte some “existential” questions. Benedikt ships their MCP.Benedicte is working on Jean-Claw for her upcoming talk when things get a bit existential. In the middle of setting up the YAML file, the bot halts on the “Who are you? Who am I?” step. She also used Claude to create a Queen Raae voice skill to help her write more like she actually talks.Benedikt shipped their MCP experiment, letting users generate broadcasts, use Liquid tags inside broadcasts, and somewhat create segments. And with Heroku's recent announcement, he's looking into alternatives once more.

Listen to Full Audio at https://podcasts.apple.com/us/podcast/the-agent-operating-system-how-openclaw-openai-are/id1684415169?i=1000750477902

Alex Gladstein and Justin Moon break down the fundamentals of large language models and explore the rise of OpenClaw as a self-sovereign AI assistant. Justin explains context engineering, local inference, and vibe coding, while Alex dives into the AI for Individual Rights program and its mission to empower activists. IN THIS EPISODE YOU'LL LEARN: 00:00:00 - Intro 00:04:12 - What Large Language Models (LLMs) are and how they differ from traditional programs 00:05:15 - Why AI feels like magic—and what's really happening under the hood 00:06:01 - The key differences between open and closed AI models 00:06:50 - Why capital structures influence AI model openness 00:09:09 - How persistent memory enhances AI agent performance 00:12:18 - What inference means and why context is a scarce resource 00:19:32 - How AI agents combine traditional software with LLM reasoning 00:21:10 - The evolution from MCP-style systems to skills-based context engineering 00:25:41 - What “vibe coding” is and how it lowers the barrier to building apps 00:44:07 - How the AI for Individual Rights program supports activist-driven innovation Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences. BOOKS AND RESOURCES Oslo Freedom Forum: Website. Justin:  Nostr account. Related episode:  Is AGI Here? Clawdbot, Local AI Agent Swarms w/ Pablo Fernandez & Trey Sellers. Related ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠books⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ mentioned in the podcast. Ad-free episodes on our⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Premium Feed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. NEW TO THE SHOW? Join the exclusive ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Mastermind Community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to engage in meaningful stock investing discussions with Stig, Clay, Kyle, and the other community members. Follow our official social media accounts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X (Twitter)⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Check out our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Bitcoin Fundamentals Starter Packs⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Browse through all our episodes (complete with transcripts) ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Try our tool for picking stock winners and managing our portfolios: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Finance Tool⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Enjoy exclusive perks from our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠favorite Apps and Services⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Get smarter about valuing businesses in just a few minutes each week through our newsletter, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn how to better start, manage, and grow your business with the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠best business podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. SPONSORS Support our free podcast by supporting our ⁠⁠⁠⁠sponsors⁠⁠⁠⁠: HardBlock Human Rights Foundation Simple Mining Netsuite Masterworks Shopify Vanta Fundrise References to any third-party products, services, or advertisers do not constitute endorsements, and The Investor's Podcast Network is not responsible for any claims made by them. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm

Plan Dulce Hosts Michelle E.  Zuñiga, PhD, AICP (she/her/hers) and Vidal F. Márquez (he/him) are joined by Michael Méndez, Ph.D., MCP (he/him) and Deyanira Nevárez Martínez Ph.D.(she/her), educators, researchers and planning practitioners to discuss Latino Urbanism, environmentalism and the hottest topic of the year, Bad Bunny. Join us for this tag-team conversation as we learn and reflect on their upbringing in Latino neighborhoods, unravel what is Latino Urbanism, cover ‘gentefication' and more as we make the connections to this year's Bad Bunny performance on the world's largest stage. Bio and Links:Dr. Michael Méndez is an Associate Professor of Environmental Planning/Policy and Chancellor's Fellow at the University of California, Irvine. He is currently an Andrew Carnegie Fellow and a Visiting Scientist at the National Center for Atmospheric Research (NCAR). Michael has over a decade of senior-level experience in both the public and private sectors, where he has consulted and actively engaged in the policymaking process. In 2023, he was appointed by Deanne Crisell, the Administrator of the Federal Emergency Management Agency (FEMA), to serve on their National Advisory Council.  In this capacity, council members advised the Administrator on all aspects of emergency management, including preparedness, protection, response, recovery, and mitigation for natural disasters, acts of terrorism, and other manmade disasters. Dr. Méndez's award-winning book, “Climate Change from the Streets,” published by Yale University Press, provides an urgent and timely analysis of the contentious politics of incorporating environmental justice into global climate change policy.  Dr. Méndez's new research focuses on climate-induced disasters and social vulnerability.  In 2021, he became the first Latinx scholar to receive the National Academies of Sciences' Henry and Bryna David Endowment Award for his research on wildfires and migrants.Deyanira Nevárez Martínez completed her Ph.D. in Urban and Environmental Planning and Policy at the University of California, Irvine in 2021. She is currently a faculty member in the Department of Urban and Regional Planning in the School of Planning, Design and Construction at Michigan State University. She has a Master's of Science in Planning from the College of Architecture, Planning, and Landscape Architecture at the University of Arizona and a Master's of Science in Geographic Information Systems Technology from the Department of Geography also at the University of Arizona.She has worked for the public and non-profit sectors. Her research focuses on the role of the state in homelessness and housing precarity. A major theme in her work is the criminalization of poverty in the United States. Additionally, her work has looked at issues of gentrification, racial equity in land-use and transportation, racial segregation, and bail reform.Links and Resourceshttp://www.michaelanthonymendez.com/http://dnmartinez.com/ --------------------------------------Plan Dulce is a podcast by members of the ⁠⁠Latinos and Planning Division⁠ of the American Planning Association⁠. The information, opinions, and recommendations presented in this Podcast are for general information only. Want to recommend our next great guests and stay updated on the latest episodes? We want to hear from you! Follow, rate, and subscribe! Your support and feedback helps us continue to amplify insightful and inspiring stories from our wonderfully culturally and professionally diverse community.This episode was conceived, written, hosted and produced by Michelle E.  Zuñiga, PhD, AICP (she/her/hers) and co-produced and hosted by Vidal F. Márquez (he/him).Connect:Instagram:https://www.instagram.com/plandulcepodcast/ Facebook:⁠https://www.facebook.com/LatinosandPlanning/⁠Youtube:Subscribe to Plan Dulce on Youtube LinkedIn:⁠https://www.linkedin.com/groups/4294535/⁠X/ Twitter:⁠https://twitter.com/latinosplanapa?lang=en⁠—----

How can you help your loved ones navigate and securely adopt AI tools ? Will Gardner, CEO of Childnet joins the show for a vital conversation about helping families use AI safely. We talk about Childnet's latest research and the practical ways you can become a digital role model and start better AI conversations at home.

In this episode of Next in Media, I sit down live at the Kochava Summit in Sandpoint, Idaho, with Charles Manning, founder and CEO of Kochava. We go deep on one of the most pressing questions facing the industry right now: how profound is the shift to agentic advertising and AI-driven workflows? Charles argues it is not a decade-long evolution like programmatic was. It is breathtakingly faster, and the companies that understand how to use their first-party data as a competitive kernel, rather than leaking it to the walled gardens, are the ones that will come out ahead. He draws a compelling analogy: if programmatic changed the auction, AI is about to change the workflow.We also dig into Kochava's CTV journey, from its mobile app roots to building measurement tools adopted by LG, Samsung, Vizio, and Roku, and how the view-and-do combo between the TV screen and the mobile device is creating powerful new outcome-based measurement opportunities for brands. Charles breaks down what holding companies should fear (and fix), why the ad tech supply chain is due for serious consolidation, and why he predicts a wave of take-privates and roll-ups followed by a bonanza of public offerings over the next two years. He also introduces Station One, Kochava's integrative AI hub that acts like a Slack for AI workflows, designed to help teams transform how they work without giving up control of their data. Key Highlights:⚡ AI vs. Programmatic: Charles explains why the shift to agentic advertising is moving breathtakingly faster than programmatic did. While programmatic took over a decade to fully reshape the auction, AI is set to transform the entire workflow within the next 16 months.

Altium Develop connects your entire electronics product team — from design to supply chain to manufacturing — in one unified platform: https://www.altium.com/develop?utm_source=youtube&utm_medium=video&utm_campaign=ontrack-podcast&utm_content=violet-labs-the-integration-hub-solving-hardware-data-chaos   Hardware engineering teams have long struggled with disconnected software tools — CAD systems that don't talk to PLMs, PLMs that don't sync with MES platforms, and engineers spending hours manually copying BOM data between systems. In this episode of the Altium OnTrack Podcast, host Zach Peterson sits down with Lucy Hoag, founder and CEO of Violet Labs, to explore how her company is tackling this pervasive problem. Lucy shares her journey from astronautical engineering and satellite design to building a no-code integration platform that acts as a centralized hub for all the disparate tools hardware teams rely on every day.   Violet works like a "Zapier for hardware engineering" — connecting mechanical CAD, electrical CAD, PLM, MES, ERP, project management tools, and more through a single middleware platform. Lucy and Zach dig into why native integrations between major software vendors remain rare, the regulatory constraints that have stalled innovation in aerospace, and how Violet's no-code approach removes barriers for non-software engineers. They also discuss Violet's newly launched MCP server, the role of AI in responsible data orchestration, and what's next on the product roadmap.  

Modern software is built on layers and layers of code. So how do we know we can trust it?In this episode of Alexa's Input (AI), Alexa Griffith sits down with Justin Cappos, professor of computer science at NYU and a leading expert in software supply chain security, to unpack what trust really means in today's digital infrastructure.From package managers and dependency chains to large-scale outages and AI systems built on inherited code, Justin explains why many security failures aren't random accidents, they're predictable consequences of weak process, misaligned incentives, and insecure design.They discuss:Why security only becomes visible when something breaksThe difference between unavoidable failure and negligenceHow modern software supply chains amplify small mistakesThe role of leadership and culture in preventing breachesWhy verification systems like TUF and in-toto matter more than everAs AI accelerates development and increases system complexity, the need for verifiable trust only grows. This episode is a practical look at the invisible infrastructure that keeps modern software, and increasingly, modern AI, from collapsing under its own complexity.Podcast LinksWatch: ⁠⁠⁠⁠⁠⁠https://www.youtube.com/@alexa_griffith⁠⁠⁠⁠⁠⁠Read: ⁠⁠⁠⁠⁠⁠⁠⁠https://alexasinput.substack.com/⁠⁠⁠⁠⁠⁠⁠⁠Listen:⁠⁠⁠⁠ https://creators.spotify.com/pod/profile/alexagriffith/⁠⁠⁠⁠More: ⁠⁠⁠⁠⁠⁠https://linktr.ee/alexagriffith⁠⁠⁠⁠⁠⁠Website: ⁠⁠⁠⁠⁠⁠https://alexagriffith.com/⁠⁠⁠⁠⁠⁠LinkedIn: ⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/alexa-griffith/⁠⁠⁠⁠⁠Find out more about the guest at:Website: https://engineering.nyu.edu/faculty/justin-capposNYU page: https://ssl.engineering.nyu.edu/personalpages/jcappos/Wikipedia: https://en.wikipedia.org/wiki/Justin_CapposChapters00:00 Introduction to Justin Cappos and His Work01:17 The Importance of Security in Software Systems03:50 Understanding Security Breaches: Mistakes vs. System Design Problems06:34 Cultural Factors in Security Failures09:25 Justin's Journey in Software Security12:03 The Role of Academia in Enterprise Security14:10 Evaluating Enterprise Security Systems16:58 Foundational Projects in Software Security19:21 AI Security Concerns and Future Directions24:59 The Need for MCP 2.028:57 Security Challenges with LLMs32:33 Designing Secure AI Systems37:14 Ethical Dilemmas in AI Decision-Making40:17 The Role of AI in Open Source43:44 Trust and Mindset in AI Security

As LLM apps evolve from simple chatbots to tool-using agents, the attack surface explodes, and the old security playbooks don't hold. In this episode of Alexa's Input (AI), Alexa Griffith sits down with Ian Webster, co-founder and CEO of PromptFoo, to break down what AI security actually looks like in practice: automated red teaming, prompt injection and jailbreak testing, evaluation workflows that scale, and why “guardrails alone” is not a security strategy.Ian shares how PromptFoo grew from a side project into a widely adopted open-source standard, what it means to raise multi-millions in a fast-moving market, and how enterprises are approaching the full vulnerability lifecycle, from finding issues to triage, remediation, and validation. Ian also discusses the “lethal trifecta” that makes agents fundamentally risky (untrusted input + sensitive data + exfil path), and why MCP security isn't just about users and tools, it's about dangerous tool combinations and rogue servers.Podcast LinksWatch: ⁠⁠⁠⁠⁠https://www.youtube.com/@alexa_griffith⁠⁠⁠⁠⁠Read: ⁠⁠⁠⁠⁠⁠⁠https://alexasinput.substack.com/⁠⁠⁠⁠⁠⁠⁠Listen:⁠⁠⁠ https://creators.spotify.com/pod/profile/alexagriffith/⁠⁠⁠More: ⁠⁠⁠⁠⁠https://linktr.ee/alexagriffith⁠⁠⁠⁠⁠Website: ⁠⁠⁠⁠⁠https://alexagriffith.com/⁠⁠⁠⁠⁠LinkedIn: ⁠⁠⁠⁠⁠https://www.linkedin.com/in/alexa-griffith/⁠⁠⁠⁠Find out more about the guest at:PromptFoo Website: https://www.promptfoo.dev/Github: https://github.com/promptfoo/promptfooIan's LinkedIn: https://www.linkedin.com/in/ianww/Chapters00:00 Introduction to AI Security Challenges02:06 Funding and Growth of PromptFu06:16 The Genesis of PromptFu11:05 Career Journey and Lessons Learned12:53 Understanding AI Red Teaming17:36 Recent AI Security Vulnerabilities19:46 The Dual Nature of AI in Security21:47 Understanding the Lethal Trifecta in AI Security24:22 Exploring Model Context Protocol (MCP) and Its Security Implications26:22 Common Security Issues in MCP Systems28:17 The Role of Identity and Permissions in AI Security30:00 Practical Implications of Using PromptFoo for Developers31:33 Evaluating Language Models: Challenges and Techniques36:34 The Limitations of Guardrails in AI Security38:25 Best Practices for Engineers in AI Development39:58 Future Trends in AI and Security42:28 Everyday Applications of AI and Language Models

As AI systems grow more autonomous, the question is no longer just what they can do, but whether we can trust the data and models behind their decisions. In this episode of Alexa's Input (AI), Alexa Griffith talks with Wendy Chin, CEO of PureCipher, about building what she calls an artificial immune system for AI, a framework designed to make data, models, and inference tamper-evident across the AI lifecycle.They unpack what data poisoning really means (training data, weights and biases, inference inputs), why small amounts of targeted poison can create outsized model misbehavior, and how generative AI lowers the barrier to sophisticated malware. The conversation expands into the security implications of agent-to-agent communication via MCP, digital twins, and why we don't have the luxury of “shipping now and securing later.” It's a wide-ranging discussion that moves from practical threat models to the philosophical frontier of what happens as AI becomes more human-like, and more autonomous.Podcast LinksWatch: ⁠⁠⁠⁠⁠⁠https://www.youtube.com/@alexa_griffith⁠⁠⁠⁠⁠⁠Read: ⁠⁠⁠⁠⁠⁠⁠⁠https://alexasinput.substack.com/⁠⁠⁠⁠⁠⁠⁠⁠Listen:⁠⁠⁠⁠ https://creators.spotify.com/pod/profile/alexagriffith/⁠⁠⁠⁠More: ⁠⁠⁠⁠⁠⁠https://linktr.ee/alexagriffith⁠⁠⁠⁠⁠⁠Website: ⁠⁠⁠⁠⁠⁠https://alexagriffith.com/⁠⁠⁠⁠⁠⁠LinkedIn: ⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/alexa-griffith/⁠⁠⁠⁠⁠Find out more about the guest at:LinkedIn: https://www.linkedin.com/in/wendy-chin-ctg/Website: https://www.purecipher.com/Chapters00:00 Introduction to AI Security01:16 Understanding Data Poisoning04:38 The Dangers of Malware in AI07:46 AI's Moral Dilemmas and Decision Making08:45 Building Empathy in AI13:07 The Role of Good Data in AI Training17:02 PureCypher's Artificial Immune System22:34 Digital Twins and Their Implications25:22 Nurturing AI Like a Child30:53 Data Therapy for AI36:13 The Future of AI and Human Interaction38:45 The Dark Side of AI: Hacking and Security45:03 Global Perspectives on AI Security48:11 MCP Agents and Security Concerns51:41 Philosophical Implications of AI and Human Connection01:00:04 The Sci-Fi Future of AI and Humanity

In this episode of Project Synapse, the hosts discuss how "agentic" AI has rapidly accelerated and become widely distributed, using the explosion of OpenClaw (with claims of ~160,000 instances) as a sign that autonomous agent tools are now in anyone's hands.  Hashtag Trending  would like to thank Meter for their support in bringing you this podcast. Meter delivers a complete networking stack, wired, wireless and cellular in one integrated solution that's built for performance and scale. You can find them at Meter.com/htt They compare the speed and societal impact of current AI progress to COVID-19's early days, arguing the pace may be even more destabilizing. They cover Anthropic's Claude 4.6 and OpenAI's Codex 5.3, including claims that Claude 4.6 helped produce a functional C compiler for about $20,000, and that a Cowork-like tool could be replicated in a day with Codex 5.3 after Claude reportedly took two weeks to build Cowork.  The conversation highlights improved long-context memory performance (needle-in-haystack-style metrics reportedly in the 90% range) and increasingly autonomous behavior such as self-testing, self-correction, and coordinating teams of agents. The hosts then focus on security: MCP (Model Context Protocol) as a widely adopted but "fundamentally insecure" connector requiring broad permissions; the risk of malicious tools/skills and malware in agent ecosystems; and the rise of "shadow AI," where employees or individuals deploy agents without organizational vetting—potentially leaking sensitive data or running up massive token bills.  They discuss incentives that push both humans and models toward fast answers and risky deployment, referencing burnout and an HBR study on rising expectations without proportional hiring. The episode also touches on realism and deepfakes, citing impressive new AI video generation (including a Chinese model "SEEDANCE 2.0" example) and how this erodes trust in what's real.  They conclude with practical advice for organizations—don't just say "no," create safe outlets and governance ("say how")—and briefly discuss wearables/AR, Meta's continued AI efforts (including the Meta AI app and "Vibes"), and the coming integration of AI into always-on devices. Sponsor: Meter, an integrated wired/wireless/cellular networking stack (meter.com/htt). 00:00 Cold Open + Sponsor: Meter Networking Stack 00:18 Welcome to Project Synapse (and immediate chaos) 00:57 'Something Big Is Happening': AI feels like COVID-speed disruption 02:57 OpenClaw goes viral: 160k instances and easy DIY clones 04:03 Claude Code 'Cowork' on Windows… and why it's broken 06:47 Rebuilding Cowork in a day with OpenAI Codex 5.3 08:18 Why Opus 4.6 feels like a step-change: memory, autonomy, agent teams 11:24 Model leapfrogging + the end of 'can AI write code?' debates 14:45 Hallucinations, 'I don't know,' and self-correction in modern models 18:42 Autonomous agents in practice: cron-like loops, tool use, and fallout 21:00 MCP security: powerful connectors, scary permissions, and 500 zero-days 24:33 Shadow AI & skill marketplaces: the app-store malware analogy 32:02 Incentives drive risk: move fast culture, confident wrong answers, burnout 34:16 AI Agents Boost Productivity… and Raise the Bar at Work 35:14 Warnings of a Coming AI-Driven Crash (and Why We're Not Steering Away) 36:28 "I Quit to Write Poetry": Existential Dread & On the Beach Vibes 37:21 Tech Safety Is Reactive: Seatbelts, Crashes, and the AI Double-Edged Sword 39:42 Fast-Moving Threats: Agents Hacking Infrastructure & Security Debt 40:54 From Doom to Adaptation: Using the Same Tools to Survive the Disruption 42:21 Why We're Numb to AI Warnings + The 'Free Energy' Thought Experiment 46:43 AGI Is Already Here? Prompts, Ego, and the 'If It Quacks Like a Duck' Test 48:56 Deepfake Video Leap: Seedance, Perfect Voices, and What's Real Anymore 52:39 Contain the Damage: 'Don't Say No—Say How' and Shadow AI in Companies 54:58 Holodeck on the Horizon: VR + GenAI + Wearables (Meta, Apple, OpenAI/Ive) 59:53 Meta's AI Reality Check: Bots, the Meta AI App, 'Vibes,' and Who's Making Money 01:04:41 Final Wrap + Sponsor Thanks

Emmanuel et Guillaume discutent de divers sujets liés à la programmation, notamment les systèmes de fichiers en Java, le Data Oriented Programming, les défis de JPA avec Kotlin, et les nouvelles fonctionnalités de Quarkus. Ils explorent également des sujets un peu fous comme la création de datacenters dans l'espace. Pas mal d'architecture aussi. Enregistré le 13 février 2026 Téléchargement de l'épisode LesCastCodeurs-Episode-337.mp3 ou en vidéo sur YouTube. News Langages Comment implémenter un file system en Java https://foojay.io/today/bootstrapping-a-java-file-system/ Créer un système de fichiers Java personnalisé avec NIO.2 pour des usages variés (VCS, archives, systèmes distants). Évolution Java: java.io.File (1.0) -> NIO (1.4) -> NIO.2 (1.7) pour personnalisation via FileSystem. Recommander conception préalable; API Java est orientée POSIX. Composants clés à considérer: Conception URI (scheme unique, chemin). Gestion de l'arborescence (BD, métadonnées, efficacité). Stockage binaire (emplacement, chiffrement, versions). Minimum pour démarrer (4 composants): Implémenter Path (représente fichier/répertoire). Étendre FileSystem (instance du système). Étendre FileSystemProvider (moteur, enregistré par scheme). Enregistrer FileSystemProvider via META-INF/services. Étapes suivantes: Couche BD (arborescence), opérations répertoire/fichier de base, stockage, tests. Processus long et exigeant, mais gratifiant.   Un article de brian goetz sur le futur du data oriented programming en Java https://openjdk.org/projects/amber/design-notes/beyond-records Le projet Amber de Java introduit les "carrier classes", une évolution des records qui permet plus de flexibilité tout en gardant les avantages du pattern matching et de la reconstruction Les records imposent des contraintes strictes (immutabilité, représentation exacte de l'état) qui limitent leur usage pour des classes avec état muable ou dérivé Les carrier classes permettent de déclarer une state description complète et canonique sans imposer que la représentation interne corresponde exactement à l'API publique Le modificateur "component" sur les champs permet au compilateur de dériver automatiquement les accesseurs pour les composants alignés avec la state description Les compact constructors sont généralisés aux carrier classes, générant automatiquement l'initialisation des component fields Les carrier classes supportent la déconstruction via pattern matching comme les records, rendant possible leur usage dans les instanceof et switch Les carrier interfaces permettent de définir une state description sur une interface, obligeant les implémentations à fournir les accesseurs correspondants L'extension entre carrier classes est possible, avec dérivation automatique des appels super() quand les composants parent sont subsumés par l'enfant Les records deviennent un cas particulier de carrier classes avec des contraintes supplémentaires (final, extends Record, component fields privés et finaux obligatoires) L'évolution compatible des records est améliorée en permettant l'ajout de composants en fin de liste et la déconstruction partielle par préfixe Comment éviter les pièges courants avec JPA et Kotlin - https://blog.jetbrains.com/idea/2026/01/how-to-avoid-common-pitfalls-with-jpa-and-kotlin/ JPA est une spécification Java pour la persistance objet-relationnel, mais son utilisation avec Kotlin présente des incompatibilités dues aux différences de conception des deux langages Les classes Kotlin sont finales par défaut, ce qui empêche la création de proxies par JPA pour le lazy loading et les opérations transactionnelles Le plugin kotlin-jpa génère automatiquement des constructeurs sans argument et rend les classes open, résolvant les problèmes de compatibilité Les data classes Kotlin ne sont pas adaptées aux entités JPA car elles génèrent equals/hashCode basés sur tous les champs, causant des problèmes avec les relations lazy L'utilisation de lateinit var pour les relations peut provoquer des exceptions si on accède aux propriétés avant leur initialisation par JPA Les types non-nullables Kotlin peuvent entrer en conflit avec le comportement de JPA qui initialise les entités avec des valeurs null temporaires Le backing field direct dans les getters/setters personnalisés peut contourner la logique de JPA et casser le lazy loading IntelliJ IDEA 2024.3 introduit des inspections pour détecter automatiquement ces problèmes et propose des quick-fixes L'IDE détecte les entités finales, les data classes inappropriées, les problèmes de constructeurs et l'usage incorrect de lateinit Ces nouvelles fonctionnalités aident les développeurs à éviter les bugs subtils liés à l'utilisation de JPA avec Kotlin Librairies Guide sur MapStruct @IterableMapping - https://www.baeldung.com/java-mapstruct-iterablemapping MapStruct est une bibliothèque Java pour générer automatiquement des mappers entre beans, l'annotation @IterableMapping permet de configurer finement le mapping de collections L'attribut dateFormat permet de formater automatiquement des dates lors du mapping de listes sans écrire de boucle manuelle L'attribut qualifiedByName permet de spécifier quelle méthode custom appliquer sur chaque élément de la collection à mapper Exemple d'usage : filtrer des données sensibles comme des mots de passe en mappant uniquement certains champs via une méthode dédiée L'attribut nullValueMappingStrategy permet de contrôler le comportement quand la collection source est null (retourner null ou une collection vide) L'annotation fonctionne pour tous types de collections Java (List, Set, etc.) et génère le code de boucle nécessaire Possibilité d'appliquer des formats numériques avec numberFormat pour convertir des nombres en chaînes avec un format spécifique MapStruct génère l'implémentation complète du mapper au moment de la compilation, éliminant le code boilerplate L'annotation peut être combinée avec @Named pour créer des méthodes de mapping réutilisables et nommées Le mapping des collections supporte les conversions de types complexes au-delà des simples conversions de types primitifs Accès aux fichiers Samba depuis Java avec JCIFS - https://www.baeldung.com/java-samba-jcifs JCIFS est une bibliothèque Java permettant d'accéder aux partages Samba/SMB sans monter de lecteur réseau, supportant le protocole SMB3 on pense aux galériens qui doivent se connecter aux systèmes dit legacy La configuration nécessite un contexte CIFS (CIFSContext) et des objets SmbFile pour représenter les ressources distantes L'authentification se fait via NtlmPasswordAuthenticator avec domaine, nom d'utilisateur et mot de passe La bibliothèque permet de lister les fichiers et dossiers avec listFiles() et vérifier leurs propriétés (taille, date de modification) Création de fichiers avec createNewFile() et de dossiers avec mkdir() ou mkdirs() pour créer toute une arborescence Suppression via delete() qui peut parcourir et supprimer récursivement des arborescences entières Copie de fichiers entre partages Samba avec copyTo(), mais impossibilité de copier depuis le système de fichiers local Pour copier depuis le système local, utilisation des streams SmbFileInputStream et SmbFileOutputStream Les opérations peuvent cibler différents serveurs Samba et différents partages (anonymes ou protégés par mot de passe) La bibliothèque s'intègre dans des blocs try-with-resources pour une gestion automatique des ressources Quarkus 3.31 - Support complet Java 25, nouveau packaging Maven et Panache Next - https://quarkus.io/blog/quarkus-3-31-released/ Support complet de Java 25 avec images runtime et native Nouveau packaging Maven de type quarkus avec lifecycle optimisé pour des builds plus rapides voici un article complet pour plus de detail https://quarkus.io/blog/building-large-applications/ Introduction de Panache Next, nouvelle génération avec meilleure expérience développeur et API unifiée ORM/Reactive Mise à jour vers Hibernate ORM 7.2, Reactive 3.2, Search 8.2 Support de Hibernate Spatial pour les données géospatiales Passage à Testcontainers 2 et JUnit 6 Annotations de sécurité supportées sur les repositories Jakarta Data Chiffrement des tokens OIDC pour les implémentations custom TokenStateManager Support OAuth 2.0 Pushed Authorization Requests dans l'extension OIDC Maven 3.9 maintenant requis minimum pour les projets Quarkus A2A Java SDK 1.0.0.Alpha1 - Alignement avec la spécification 1.0 du protocole Agent2Agent - https://quarkus.io/blog/a2a-java-sdk-1-0-0-alpha1/ Le SDK Java A2A implémente le protocole Agent2Agent qui permet la communication standardisée entre agents IA pour découvrir des capacités, déléguer des tâches et collaborer Passage à la version 1.0 de la spécification marque la transition d'expérimental à production-ready avec des changements cassants assumés Modernisation complète du module spec avec des Java records partout remplaçant le mix précédent de classes et records pour plus de cohérence Adoption de Protocol Buffers comme source de vérité avec des mappers MapStruct pour la conversion et Gson pour JSON-RPC Les builders utilisent maintenant des méthodes factory statiques au lieu de constructeurs publics suivant les best practices Java modernes Introduction de trois BOMs Maven pour simplifier la gestion des dépendances du SDK core, des extensions et des implémentations de référence Quarkus AgentCard évolue avec une liste supportedInterfaces remplaçant url et preferredTransport pour plus de flexibilité dans la déclaration des protocoles Support de la pagination ajouté pour ListTasks et les endpoints de configuration des notifications push avec des wrappers Result appropriés Interface A2AHttpClient pluggable permettant des implémentations HTTP personnalisées avec une implémentation Vert.x fournie Travail continu vers la conformité complète avec le TCK 1.0 en cours de développement parallèlement à la finalisation de la spécification Pourquoi Quarkus finit par "cliquer" : les 10 questions que se posent les développeurs Java - https://www.the-main-thread.com/p/quarkus-java-developers-top-questions-2025 un article qui revele et repond aux questions des gens qui ont utilisé Quarkus depuis 4-6 mois, les non noob questions Quarkus est un framework Java moderne optimisé pour le cloud qui propose des temps de démarrage ultra-rapides et une empreinte mémoire réduite Pourquoi Quarkus démarre si vite ? Le framework effectue le travail lourd au moment du build (scanning, indexation, génération de bytecode) plutôt qu'au runtime Quand utiliser le mode réactif plutôt qu'impératif ? Le réactif est pertinent pour les workloads avec haute concurrence et dominance I/O, l'impératif reste plus simple dans les autres cas Quelle est la différence entre Dev Services et Testcontainers ? Dev Services utilise Testcontainers en gérant automatiquement le cycle de vie, les ports et la configuration sans cérémonie Comment la DI de Quarkus diffère de Spring ? CDI est un standard basé sur la sécurité des types et la découverte au build-time, différent de l'approche framework de Spring Comment gérer la configuration entre environnements ? Quarkus permet de scaler depuis le développement local jusqu'à Kubernetes avec des profils, fichiers multiples et configuration externe Comment tester correctement les applications Quarkus ? @QuarkusTest démarre l'application une fois pour toute la suite de tests, changeant le modèle mental par rapport à Spring Boot Que fait vraiment Panache en coulisses ? Panache est du JPA avec des opinions fortes et des défauts propres, enveloppant Hibernate avec un style Active Record Doit-on utiliser les images natives et quand ? Les images natives brillent pour le serverless et l'edge grâce au démarrage rapide et la faible empreinte mémoire, mais tous les apps n'en bénéficient pas Comment Quarkus s'intègre avec Kubernetes ? Le framework génère automatiquement les ressources Kubernetes, gère les health checks et métriques comme s'il était nativement conçu pour cet écosystème Comment intégrer l'IA dans une application Quarkus ? LangChain4j permet d'ajouter embeddings, retrieval, guardrails et observabilité directement en Java sans passer par Python Infrastructure Les alternatives à MinIO https://rmoff.net/2026/01/14/alternatives-to-minio-for-single-node-local-s3/ MinIO a abandonné le support single-node fin 2025 pour des raisons commerciales, cassant de nombreuses démos et pipelines CI/CD qui l'utilisaient pour émuler S3 localement L'auteur cherche un remplacement simple avec image Docker, compatibilité S3, licence open source, déploiement mono-nœud facile et communauté active S3Proxy est très léger et facile à configurer, semble être l'option la plus simple mais repose sur un seul contributeur RustFS est facile à utiliser et inclut une GUI, mais c'est un projet très récent en version alpha avec une faille de sécurité majeure récente SeaweedFS existe depuis 2012 avec support S3 depuis 2018, relativement facile à configurer et dispose d'une interface web basique Zenko CloudServer remplace facilement MinIO mais la documentation et le branding (cloudserver/zenko/scality) peuvent prêter à confusion Garage nécessite une configuration complexe avec fichier TOML et conteneur d'initialisation séparé, pas un simple remplacement drop-in Apache Ozone requiert au minimum quatre nœuds pour fonctionner, beaucoup trop lourd pour un usage local simple L'auteur recommande SeaweedFS et S3Proxy comme remplaçants viables, RustFS en maybe, et élimine Garage et Ozone pour leur complexité Garage a une histoire tres associative, il vient du collectif https://deuxfleurs.fr/ qui offre un cloud distribué sans datacenter C'est certainement pas une bonne idée, les datacenters dans l'espace https://taranis.ie/datacenters-in-space-are-a-terrible-horrible-no-good-idea/ Avis d'expert (ex-NASA/Google, Dr en électronique spatiale) : Centres de données spatiaux, une "terrible" idée. Incompatibilité fondamentale : L'électronique (surtout IA/GPU) est inadaptée à l'environnement spatial. Énergie : Accès limité. Le solaire (type ISS) est insuffisant pour l'échelle de l'IA. Le nucléaire (RTG) est trop faible. Refroidissement : L'espace n'est pas "froid" ; absence de convection. Nécessite des radiateurs gigantesques (ex: 531m² pour 200kW). Radiations : Provoque erreurs (SEU, SEL) et dommages. Les GPU sont très vulnérables. Blindage lourd et inefficace. Les puces "durcies" sont très lentes. Communications : Bande passante très limitée (1Gbps radio vs 100Gbps terrestre). Le laser est tributaire des conditions atmosphériques. Conclusion : Projet extrêmement difficile, coûteux et aux performances médiocres. Data et Intelligence Artificielle Guillaume a développé un serveur MCP pour arXiv (le site de publication de papiers de recherche) en Java avec le framework Quarkus https://glaforge.dev/posts/2026/01/18/implementing-an-arxiv-mcp-server-with-quarkus-in-java/ Implémentation d'un serveur MCP (Model Context Protocol) arXiv en Java avec Quarkus. Objectif : Accéder aux publications arXiv et illustrer les fonctionnalités moins connues du protocole MCP. Mise en œuvre : Utilisation du framework Quarkus (Java) et son support MCP étendu. Assistance par Antigravity (IDE agentique) pour le développement et l'intégration de l'API arXiv. Interaction avec l'API arXiv : requêtes HTTP, format XML Atom pour les résultats, parser XML Jackson. Fonctionnalités MCP exposées : Outils (@Tool) : Recherche de publications (search_papers). Ressources (@Resource, @ResourceTemplate) : Taxonomie des catégories arXiv, métadonnées des articles (via un template d'URI). Prompts (@Prompt) : Exemples pour résumer des articles ou construire des requêtes de recherche. Configuration : Le serveur peut fonctionner en STDIO (local) ou via HTTP Streamable (local ou distant), avec une configuration simple dans des clients comme Gemini CLI. Conclusion : Quarkus simplifie la création de serveurs MCP riches en fonctionnalités, rendant les données et services "prêts pour l'IA" avec l'aide d'outils d'IA comme Antigravity. Anthropic ne mettra pas de pub dans Claude https://www.anthropic.com/news/claude-is-a-space-to-think c'est en reaction au plan non public d'OpenAi de mettre de la pub pour pousser les gens au mode payant OpenAI a besoin de cash et est probablement le plus utilisé pour gratuit au monde Anthropic annonce que Claude restera sans publicité pour préserver son rôle d'assistant conversationnel dédié au travail et à la réflexion approfondie. Les conversations avec Claude sont souvent sensibles, personnelles ou impliquent des tâches complexes d'ingénierie logicielle où les publicités seraient inappropriées. L'analyse des conversations montre qu'une part significative aborde des sujets délicats similaires à ceux évoqués avec un conseiller de confiance. Un modèle publicitaire créerait des incitations contradictoires avec le principe fondamental d'être "genuinely helpful" inscrit dans la Constitution de Claude. Les publicités introduiraient un conflit d'intérêt potentiel où les recommandations pourraient être influencées par des motivations commerciales plutôt que par l'intérêt de l'utilisateur. Le modèle économique d'Anthropic repose sur les contrats entreprise et les abonnements payants, permettant de réinvestir dans l'amélioration de Claude. Anthropic maintient l'accès gratuit avec des modèles de pointe et propose des tarifs réduits pour les ONG et l'éducation dans plus de 60 pays. Le commerce "agentique" sera supporté mais uniquement à l'initiative de l'utilisateur, jamais des annonceurs, pour préserver la confiance. Les intégrations tierces comme Figma, Asana ou Canva continueront d'être développées en gardant l'utilisateur aux commandes. Anthropic compare Claude à un cahier ou un tableau blanc : des espaces de pensée purs, sans publicité. Infinispan 16.1 est sorti https://infinispan.org/blog/2026/02/04/infinispan-16-1 déjà le nom de la release mérite une mention Le memory bounded par cache et par ensemble de cache s est pas facile à faire en Java Une nouvelle api OpenAPI AOT caché dans les images container Un serveur MCP local juste avec un fichier Java ? C'est possible avec LangChain4j et JBang https://glaforge.dev/posts/2026/02/11/zero-boilerplate-java-stdio-mcp-servers-with-langchain4j-and-jbang/ Création rapide de serveurs MCP Java sans boilerplate. MCP (Model Context Protocol): standard pour connecter les LLM à des outils et données. Le tutoriel répond au manque d'options simples pour les développeurs Java, face à une prédominance de Python/TypeScript dans l'écosystème MCP. La solution utilise: LangChain4j: qui intègre un nouveau module serveur MCP pour le protocole STDIO. JBang: permet d'exécuter des fichiers Java comme des scripts, éliminant les fichiers de build (pom.xml, Gradle). Implémentation: se fait via un seul fichier .java. JBang gère automatiquement les dépendances (//DEPS). L'annotation @Tool de LangChain4j expose les méthodes Java aux LLM. StdioMcpServerTransport gère la communication JSON-RPC via l'entrée/sortie standard (STDIO). Point crucial: Les logs doivent impérativement être redirigés vers System.err pour éviter de corrompre System.out, qui est réservé à la communication MCP (messages JSON-RPC). Facilite l'intégration locale avec des outils comme Gemini CLI, Claude Code, etc. Reciprocal Rank Fusion : un algorithme utile et souvent utilisé pour faire de la recherche hybride, pour mélanger du RAG et des recherches par mots-clé https://glaforge.dev/posts/2026/02/10/advanced-rag-understanding-reciprocal-rank-fusion-in-hybrid-search/ RAG : Qualité LLM dépend de la récupération. Recherche Hybride : Combiner vectoriel et mots-clés (BM25) est optimal. Défi : Fusionner des scores d'échelles différentes. Solution : Reciprocal Rank Fusion (RRF). RRF : Algorithme robuste qui fusionne des listes de résultats en se basant uniquement sur le rang des documents, ignorant les scores. Avantages RRF : Pas de normalisation de scores, scalable, excellente première étape de réorganisation. Architecture RAG fréquente : RRF (large sélection) + Cross-Encoder / modèle de reranking (précision fine). RAG-Fusion : Utilise un LLM pour générer plusieurs variantes de requête, puis RRF agrège tous les résultats pour renforcer le consensus et réduire les hallucinations. Implémentation : LangChain4j utilise RRF par défaut pour agréger les résultats de plusieurs retrievers. Les dernières fonctionnalités de Gemini et Nano Banana supportées dans LangChain4j https://glaforge.dev/posts/2026/02/06/latest-gemini-and-nano-banana-enhancements-in-langchain4j/ Nouveaux modèles d'images Nano Banana (Gemini 2.5/3.0) pour génération et édition (jusqu'à 4K). "Grounding" via Google Search (pour images et texte) et Google Maps (localisation, Gemini 2.5). Outil de contexte URL (Gemini 3.0) pour lecture directe de pages web. Agents multimodaux (AiServices) capables de générer des images. Configuration de la réflexion (profondeur Chain-of-Thought) pour Gemini 3.0. Métadonnées enrichies : usage des tokens et détails des sources de "grounding". Comment configurer Gemini CLI comment agent de code dans IntelliJ grâce au protocole ACP https://glaforge.dev/posts/2026/02/01/how-to-integrate-gemini-cli-with-intellij-idea-using-acp/ But : Intégrer Gemini CLI à IntelliJ IDEA via l'Agent Client Protocol (ACP). Prérequis : IntelliJ IDEA 2025.3+, Node.js (v20+), Gemini CLI. Étapes : Installer Gemini CLI (npm install -g @google/gemini-cli). Localiser l'exécutable gemini. Configurer ~/.jetbrains/acp.json (chemin exécutable, --experimental-acp, use_idea_mcp: true). Redémarrer IDEA, sélectionner "Gemini CLI" dans l'Assistant IA. Usage : Gemini interagit avec le code et exécute des commandes (contexte projet). Important : S'assurer du flag --experimental-acp dans la configuration. Outillage PipeNet, une alternative (open source aussi) à LocalTunnel, mais un plus évoluée https://pipenet.dev/ pipenet: Alternative open-source et moderne à localtunnel (client + serveur). Usages: Développement local (partage, webhooks), intégration SDK, auto-hébergement sécurisé. Fonctionnalités: Client (expose ports locaux, sous-domaines), Serveur (déploiement, domaines personnalisés, optimisé cloud mono-port). Avantages vs localtunnel: Déploiement cloud sur un seul port, support multi-domaines, TypeScript/ESM, maintenance active. Protocoles: HTTP/S, WebSocket, SSE, HTTP Streaming. Intégration: CLI ou SDK JavaScript. JSON-IO — une librairie comme Jackson ou GSON, supportant JSON5, TOON, et qui pourrait être utile pour l'utilisation du "structured output" des LLMs quand ils ne produisent pas du JSON parfait https://github.com/jdereg/json-io json-io : Librairie Java pour la sérialisation et désérialisation JSON/TOON. Gère les graphes d'objets complexes, les références cycliques et les types polymorphes. Support complet JSON5 (lecture et écriture), y compris des fonctionnalités non prises en charge par Jackson/Gson. Format TOON : Notation orientée token, optimisée pour les LLM, réduisant l'utilisation de tokens de 40 à 50% par rapport au JSON. Légère : Aucune dépendance externe (sauf java-util), taille de JAR réduite (~330K). Compatible JDK 1.8 à 24, ainsi qu'avec les environnements JPMS et OSGi. Deux modes de conversion : vers des objets Java typés (toJava()) ou vers des Map (toMaps()). Options de configuration étendues via ReadOptionsBuilder et WriteOptionsBuilder. Optimisée pour les déploiements cloud natifs et les architectures de microservices. Utiliser mailpit et testcontainer pour tester vos envois d'emails https://foojay.io/today/testing-emails-with-testcontainers-and-mailpit/ l'article montre via SpringBoot et sans. Et voici l'extension Quarkus https://quarkus.io/extensions/io.quarkiverse.mailpit/quarkus-mailpit/?tab=docs Tester l'envoi d'emails en développement est complexe car on ne peut pas utiliser de vrais serveurs SMTP Mailpit est un serveur SMTP de test qui capture les emails et propose une interface web pour les consulter Testcontainers permet de démarrer Mailpit dans un conteneur Docker pour les tests d'intégration L'article montre comment configurer une application SpringBoot pour envoyer des emails via JavaMail Un module Testcontainers dédié à Mailpit facilite son intégration dans les tests Le conteneur Mailpit expose un port SMTP (1025) et une API HTTP (8025) pour vérifier les emails reçus Les tests peuvent interroger l'API HTTP de Mailpit pour valider le contenu des emails envoyés Cette approche évite d'utiliser des mocks et teste réellement l'envoi d'emails Mailpit peut aussi servir en développement local pour visualiser les emails sans les envoyer réellement La solution fonctionne avec n'importe quel framework Java supportant JavaMail Architecture Comment scaler un système de 0 à 10 millions d'utilisateurs https://blog.algomaster.io/p/scaling-a-system-from-0-to-10-million-users Philosophie : Scalabilité incrémentale, résoudre les goulots d'étranglement sans sur-ingénierie. 0-100 utilisateurs : Serveur unique (app, DB, jobs). 100-1K : Séparer app et DB (services gérés, pooling). 1K-10K : Équilibreur de charge, multi-serveurs d'app (stateless via sessions partagées). 10K-100K : Caching, réplicas de lecture DB, CDN (réduire charge DB). 100K-500K : Auto-scaling, applications stateless (authentification JWT). 500K-10M : Sharding DB, microservices, files de messages (traitement asynchrone). 10M+ : Déploiement multi-régions, CQRS, persistance polyglotte, infra personnalisée. Principes clés : Simplicité, mesure, stateless essentiel, cache/asynchrone, sharding prudent, compromis (CAP), coût de la complexité. Patterns d'Architecture 2026 - Du Hype à la Réalité du Terrain (Part 1/2) - https://blog.ippon.fr/2026/01/30/patterns-darchitecture-2026-part-1/ L'article présente quatre patterns d'architecture logicielle pour répondre aux enjeux de scalabilité, résilience et agilité business dans les systèmes modernes Il présentent leurs raisons et leurs pièges Un bon rappel L'Event-Driven Architecture permet une communication asynchrone entre systèmes via des événements publiés et consommés, évitant le couplage direct Les bénéfices de l'EDA incluent la scalabilité indépendante des composants, la résilience face aux pannes et l'ajout facile de nouveaux cas d'usage Le pattern API-First associé à un API Gateway centralise la sécurité, le routage et l'observabilité des APIs avec un catalogue unifié Le Backend for Frontend crée des APIs spécifiques par canal (mobile, web, partenaires) pour optimiser l'expérience utilisateur CQRS sépare les modèles de lecture et d'écriture avec des bases optimisées distinctes, tandis que l'Event Sourcing stocke tous les événements plutôt que l'état actuel Le Saga Pattern gère les transactions distribuées via orchestration centralisée ou chorégraphie événementielle pour coordonner plusieurs microservices Les pièges courants incluent l'explosion d'événements granulaires, la complexité du debugging distribué, et la mauvaise gestion de la cohérence finale Les technologies phares sont Kafka pour l'event streaming, Kong pour l'API Gateway, EventStoreDB pour l'Event Sourcing et Temporal pour les Sagas Ces patterns nécessitent une maturité technique et ne sont pas adaptés aux applications CRUD simples ou aux équipes junior Patterns d'architecture 2026 : du hype à la réalité terrain part. 2 - https://blog.ippon.fr/2026/02/04/patterns-darchitecture-2026-part-2/ Deuxième partie d'un guide pratique sur les patterns d'architecture logicielle et système éprouvés pour moderniser et structurer les applications en 2026 Strangler Fig permet de migrer progressivement un système legacy en l'enveloppant petit à petit plutôt que de tout réécrire d'un coup (70% d'échec pour les big bang) Anti-Corruption Layer protège votre nouveau domaine métier des modèles externes et legacy en créant une couche de traduction entre les systèmes Service Mesh gère automatiquement la communication inter-services dans les architectures microservices (sécurité mTLS, observabilité, résilience) Architecture Hexagonale sépare le coeur métier des détails techniques via des ports et adaptateurs pour améliorer la testabilité et l'évolutivité Chaque pattern est illustré par un cas client concret avec résultats mesurables et liste des pièges à éviter lors de l'implémentation Les technologies 2026 mentionnées incluent Istio, Linkerd pour service mesh, LaunchDarkly pour feature flags, NGINX et Kong pour API gateway Tableau comparatif final aide à choisir le bon pattern selon la complexité, le scope et le use case spécifique du projet L'article insiste sur une approche pragmatique : ne pas utiliser un pattern juste parce qu'il est moderne mais parce qu'il résout un problème réel Pour les systèmes simples type CRUD ou avec peu de services, ces patterns peuvent introduire une complexité inutile qu'il faut savoir éviter Méthodologies Le rêve récurrent de remplacer voire supprimer les développeurs https://www.caimito.net/en/blog/2025/12/07/the-recurring-dream-of-replacing-developers.html Depuis 1969, chaque décennie voit une tentative de réduire le besoin de développeurs (de COBOL, UML, visual builders… à IA). Motivation : frustration des dirigeants face aux délais et coûts de développement. La complexité logicielle est intrinsèque et intellectuelle, non pas une question d'outils. Chaque vague technologique apporte de la valeur mais ne supprime pas l'expertise humaine. L'IA assiste les développeurs, améliore l'efficacité, mais ne remplace ni le jugement ni la gestion de la complexité. La demande de logiciels excède l'offre car la contrainte majeure est la réflexion nécessaire pour gérer cette complexité. Pour les dirigeants : les outils rendent-ils nos développeurs plus efficaces sur les problèmes complexes et réduisent-ils les tâches répétitives ? Le "rêve" de remplacer les développeurs, irréalisable, est un moteur d'innovation créant des outils précieux. Comment creuser des sujets à l'ère de l'IA générative. Quid du partage et la curation de ces recherches ? https://glaforge.dev/posts/2026/02/04/researching-topics-in-the-age-of-ai-rock-solid-webhooks-case-study/ Recherche initiale de l'auteur sur les webhooks en 2019, processus long et manuel. L'IA (Deep Research, Gemini, NotebookLM) facilite désormais la recherche approfondie, l'exploration de sujets et le partage des résultats. L'IA a identifié et validé des pratiques clés pour des déploiements de webhooks résilients, en grande partie les mêmes que celles trouvées précédemment par l'auteur. Génération d'artefacts par l'IA : rapport détaillé, résumé concis, illustration sketchnote, et même une présentation (slide deck). Guillaume s'interroge sur le partage public de ces rapports de recherche générés par l'IA, tout en souhaitant éviter le "AI Slop". Loi, société et organisation Le logiciel menacé par le vibe coding https://www.techbuzz.ai/articles/we-built-a-monday-com-clone-in-under-an-hour-with-ai Deux journalistes de CNBC sans expérience de code ont créé un clone fonctionnel de Monday.com en moins de 60 minutes pour 5 à 15 dollars. L'expérience valide les craintes des investisseurs qui ont provoqué une baisse de 30% des actions des entreprises SaaS. L'IA a non seulement reproduit les fonctionnalités de base mais a aussi recherché Monday.com de manière autonome pour identifier et recréer ses fonctionnalités clés. Cette technique appelée "vibe-coding" permet aux non-développeurs de construire des applications via des instructions en anglais courant. Les entreprises les plus vulnérables sont celles offrant des outils "qui se posent sur le travail" comme Atlassian, Adobe, HubSpot, Zendesk et Smartsheet. Les entreprises de cybersécurité comme CrowdStrike et Palo Alto sont considérées plus protégées grâce aux effets de réseau et aux barrières réglementaires. Les systèmes d'enregistrement comme Salesforce restent plus difficiles à répliquer en raison de leur profondeur d'intégration et de données d'entreprise. Le coût de 5 à 15 dollars par construction permet aux entreprises de prototyper plusieurs solutions personnalisées pour moins cher qu'une seule licence Monday.com. L'expérience soulève des questions sur la pérennité du marché de 5 milliards de dollars des outils de gestion de projet face à l'IA générative. Conférences En complément de l'agenda des conférences de Aurélie Vache, il y a également le site https://javaconferences.org/ (fait par Brian Vermeer) avec toutes les conférences Java à venir ! La liste des conférences provenant de Developers Conferences Agenda/List par Aurélie Vache et contributeurs : 12-13 février 2026 : Touraine Tech #26 - Tours (France) 12-13 février 2026 : World Artificial Intelligence Cannes Festival - Cannes (France) 19 février 2026 : ObservabilityCON on the Road - Paris (France) 6 mars 2026 : WordCamp Nice 2026 - Nice (France) 18 mars 2026 : Jupyter Workshops: AI in Jupyter: Building Extensible AI Capabilities for Interactive Computing - Saint-Maur-des-Fossés (France) 18-19 mars 2026 : Agile Niort 2026 - Niort (France) 20 mars 2026 : Atlantique Day 2026 - Nantes (France) 26 mars 2026 : Data Days Lille - Lille (France) 26-27 mars 2026 : SymfonyLive Paris 2026 - Paris (France) 26-27 mars 2026 : REACT PARIS - Paris (France) 27-29 mars 2026 : Shift - Nantes (France) 31 mars 2026 : ParisTestConf - Paris (France) 31 mars 2026-1 avril 2026 : FlowCon France 2026 - Paris (France) 1 avril 2026 : AWS Summit Paris - Paris (France) 2 avril 2026 : Pragma Cannes 2026 - Cannes (France) 2-3 avril 2026 : Xen Spring Meetup 2026 - Grenoble (France) 7 avril 2026 : PyTorch Conference Europe - Paris (France) 9-10 avril 2026 : Android Makers by droidcon 2026 - Paris (France) 9-11 avril 2026 : Drupalcamp Grenoble 2026 - Grenoble (France) 16-17 avril 2026 : MiXiT 2026 - Lyon (France) 17-18 avril 2026 : Faiseuses du Web 5 - Dinan (France) 22-24 avril 2026 : Devoxx France 2026 - Paris (France) 23-25 avril 2026 : Devoxx Greece - Athens (Greece) 6-7 mai 2026 : Devoxx UK 2026 - London (UK) 12 mai 2026 : Lead Innovation Day - Leadership Edition - Paris (France) 19 mai 2026 : La Product Conf Paris 2026 - Paris (France) 21-22 mai 2026 : Flupa UX Days 2026 - Paris (France) 22 mai 2026 : AFUP Day 2026 Lille - Lille (France) 22 mai 2026 : AFUP Day 2026 Paris - Paris (France) 22 mai 2026 : AFUP Day 2026 Bordeaux - Bordeaux (France) 22 mai 2026 : AFUP Day 2026 Lyon - Lyon (France) 28 mai 2026 : DevCon 27 : I.A. & Vibe Coding - Paris (France) 28 mai 2026 : Cloud Toulouse 2026 - Toulouse (France) 29 mai 2026 : NG Baguette Conf 2026 - Paris (France) 29 mai 2026 : Agile Tour Strasbourg 2026 - Strasbourg (France) 2-3 juin 2026 : Agile Tour Rennes 2026 - Rennes (France) 2-3 juin 2026 : OW2Con - Paris-Châtillon (France) 3 juin 2026 : IA–NA - La Rochelle (France) 5 juin 2026 : TechReady - Nantes (France) 5 juin 2026 : Fork it! - Rouen - Rouen (France) 6 juin 2026 : Polycloud - Montpellier (France) 9 juin 2026 : JFTL - Montrouge (France) 9 juin 2026 : C: - Caen (France) 11-12 juin 2026 : DevQuest Niort - Niort (France) 11-12 juin 2026 : DevLille 2026 - Lille (France) 12 juin 2026 : Tech F'Est 2026 - Nancy (France) 16 juin 2026 : Mobilis In Mobile 2026 - Nantes (France) 17-19 juin 2026 : Devoxx Poland - Krakow (Poland) 17-20 juin 2026 : VivaTech - Paris (France) 18 juin 2026 : Tech'Work - Lyon (France) 22-26 juin 2026 : Galaxy Community Conference - Clermont-Ferrand (France) 24-25 juin 2026 : Agi'Lille 2026 - Lille (France) 24-26 juin 2026 : BreizhCamp 2026 - Rennes (France) 2 juillet 2026 : Azur Tech Summer 2026 - Valbonne (France) 2-3 juillet 2026 : Sunny Tech - Montpellier (France) 3 juillet 2026 : Agile Lyon 2026 - Lyon (France) 6-8 juillet 2026 : Riviera Dev - Sophia Antipolis (France) 2 août 2026 : 4th Tech Summit on Artificial Intelligence & Robotics - Paris (France) 20-22 août 2026 : 4th Tech Summit on AI & Robotics - Paris (France) & Online 4 septembre 2026 : JUG Summer Camp 2026 - La Rochelle (France) 17-18 septembre 2026 : API Platform Conference 2026 - Lille (France) 24 septembre 2026 : PlatformCon Live Day Paris 2026 - Paris (France) 1 octobre 2026 : WAX 2026 - Marseille (France) 1-2 octobre 2026 : Volcamp - Clermont-Ferrand (France) 5-9 octobre 2026 : Devoxx Belgium - Antwerp (Belgium) Nous contacter Pour réagir à cet épisode, venez discuter sur le groupe Google https://groups.google.com/group/lescastcodeurs Contactez-nous via X/twitter https://twitter.com/lescastcodeurs ou Bluesky https://bsky.app/profile/lescastcodeurs.com Faire un crowdcast ou une crowdquestion Soutenez Les Cast Codeurs sur Patreon https://www.patreon.com/LesCastCodeurs Tous les épisodes et toutes les infos sur https://lescastcodeurs.com/

TR is joined by Joseph Lombardi to talk about the Building Thinking Classrooms framework and how it can benefit students in math classes as well as other subjects Show Notes Explain Everything Building Thinking Classrooms Joey's blog post for MCP: "Adding Inquiry to My Modern Classroom Through Building Thinking Classrooms" The Five-E Model Jean Piaget Lev Vygotsky Joey's resource Connect with Joey: [His website](sites.google.com/view/joeylombardi/home) [Follow him on LinkedIn](https://www.linkedin.com/authwall?trk=bf&trkInfo=AQHF4oax2ihHUgAAAZsS5iPYbFfaoC6wX_nmvYAzF0tgys4OjOeQBzWSNR8pzrAsEchKVQhBI5HdnhiSLIm357FLBkiuAARLC6imai2Br3Dedu9rIdtP88JznvLFY92ToFqBbrM=&original_referer=&sessionRedirect=https%3A%2F%2Fwww.linkedin.com%2Fin%2Fjoseph-chaves-lombardi-55260b239) Contact us, follow us online, and learn more: Email us questions and feedback at: podcast@modernclassrooms.org Listen to this podcast on Youtube Modern Classrooms: @modernclassproj on Twitter and facebook.com/modernclassproj Kareem: @kareemfarah23 on Twitter Toni Rose: @classroomflex on Twitter and Instagram The Modern Classroom Project Modern Classrooms Online Course Take our free online course, or sign up for our mentorship program to receive personalized guidance from a Modern Classrooms mentor as you implement your own modern classroom! The Modern Classrooms Podcast is edited by Zach Diamond: Learning to Teach

In this episode of Project Synapse, the hosts discuss how "agentic" AI has rapidly accelerated and become widely distributed, using the explosion of OpenClaw (with claims of ~160,000 instances) as a sign that autonomous agent tools are now in anyone's hands.  Hashtag Trending  would like to thank Meter for their support in bringing you this podcast. Meter delivers a complete networking stack, wired, wireless and cellular in one integrated solution that's built for performance and scale. You can find them at Meter.com/htt They compare the speed and societal impact of current AI progress to COVID-19's early days, arguing the pace may be even more destabilizing. They cover Anthropic's Claude 4.6 and OpenAI's Codex 5.3, including claims that Claude 4.6 helped produce a functional C compiler for about $20,000, and that a Cowork-like tool could be replicated in a day with Codex 5.3 after Claude reportedly took two weeks to build Cowork.  The conversation highlights improved long-context memory performance (needle-in-haystack-style metrics reportedly in the 90% range) and increasingly autonomous behavior such as self-testing, self-correction, and coordinating teams of agents. The hosts then focus on security: MCP (Model Context Protocol) as a widely adopted but "fundamentally insecure" connector requiring broad permissions; the risk of malicious tools/skills and malware in agent ecosystems; and the rise of "shadow AI," where employees or individuals deploy agents without organizational vetting—potentially leaking sensitive data or running up massive token bills.  They discuss incentives that push both humans and models toward fast answers and risky deployment, referencing burnout and an HBR study on rising expectations without proportional hiring. The episode also touches on realism and deepfakes, citing impressive new AI video generation (including a Chinese model "SEEDANCE 2.0" example) and how this erodes trust in what's real.  They conclude with practical advice for organizations—don't just say "no," create safe outlets and governance ("say how")—and briefly discuss wearables/AR, Meta's continued AI efforts (including the Meta AI app and "Vibes"), and the coming integration of AI into always-on devices. Sponsor: Meter, an integrated wired/wireless/cellular networking stack (meter.com/htt). 00:00 Cold Open + Sponsor: Meter Networking Stack 00:18 Welcome to Project Synapse (and immediate chaos) 00:57 'Something Big Is Happening': AI feels like COVID-speed disruption 02:57 OpenClaw goes viral: 160k instances and easy DIY clones 04:03 Claude Code 'Cowork' on Windows… and why it's broken 06:47 Rebuilding Cowork in a day with OpenAI Codex 5.3 08:18 Why Opus 4.6 feels like a step-change: memory, autonomy, agent teams 11:24 Model leapfrogging + the end of 'can AI write code?' debates 14:45 Hallucinations, 'I don't know,' and self-correction in modern models 18:42 Autonomous agents in practice: cron-like loops, tool use, and fallout 21:00 MCP security: powerful connectors, scary permissions, and 500 zero-days 24:33 Shadow AI & skill marketplaces: the app-store malware analogy 32:02 Incentives drive risk: move fast culture, confident wrong answers, burnout 34:16 AI Agents Boost Productivity… and Raise the Bar at Work 35:14 Warnings of a Coming AI-Driven Crash (and Why We're Not Steering Away) 36:28 "I Quit to Write Poetry": Existential Dread & On the Beach Vibes 37:21 Tech Safety Is Reactive: Seatbelts, Crashes, and the AI Double-Edged Sword 39:42 Fast-Moving Threats: Agents Hacking Infrastructure & Security Debt 40:54 From Doom to Adaptation: Using the Same Tools to Survive the Disruption 42:21 Why We're Numb to AI Warnings + The 'Free Energy' Thought Experiment 46:43 AGI Is Already Here? Prompts, Ego, and the 'If It Quacks Like a Duck' Test 48:56 Deepfake Video Leap: Seedance, Perfect Voices, and What's Real Anymore 52:39 Contain the Damage: 'Don't Say No—Say How' and Shadow AI in Companies 54:58 Holodeck on the Horizon: VR + GenAI + Wearables (Meta, Apple, OpenAI/Ive) 59:53 Meta's AI Reality Check: Bots, the Meta AI App, 'Vibes,' and Who's Making Money 01:04:41 Final Wrap + Sponsor Thanks

In this episode of Project Synapse, the hosts discuss how "agentic" AI has rapidly accelerated and become widely distributed, using the explosion of OpenClaw (with claims of ~160,000 instances) as a sign that autonomous agent tools are now in anyone's hands.  Hashtag Trending  would like to thank Meter for their support in bringing you this podcast. Meter delivers a complete networking stack, wired, wireless and cellular in one integrated solution that's built for performance and scale. You can find them at Meter.com/htt They compare the speed and societal impact of current AI progress to COVID-19's early days, arguing the pace may be even more destabilizing. They cover Anthropic's Claude 4.6 and OpenAI's Codex 5.3, including claims that Claude 4.6 helped produce a functional C compiler for about $20,000, and that a Cowork-like tool could be replicated in a day with Codex 5.3 after Claude reportedly took two weeks to build Cowork.  The conversation highlights improved long-context memory performance (needle-in-haystack-style metrics reportedly in the 90% range) and increasingly autonomous behavior such as self-testing, self-correction, and coordinating teams of agents. The hosts then focus on security: MCP (Model Context Protocol) as a widely adopted but "fundamentally insecure" connector requiring broad permissions; the risk of malicious tools/skills and malware in agent ecosystems; and the rise of "shadow AI," where employees or individuals deploy agents without organizational vetting—potentially leaking sensitive data or running up massive token bills.  They discuss incentives that push both humans and models toward fast answers and risky deployment, referencing burnout and an HBR study on rising expectations without proportional hiring. The episode also touches on realism and deepfakes, citing impressive new AI video generation (including a Chinese model "SEEDANCE 2.0" example) and how this erodes trust in what's real.  They conclude with practical advice for organizations—don't just say "no," create safe outlets and governance ("say how")—and briefly discuss wearables/AR, Meta's continued AI efforts (including the Meta AI app and "Vibes"), and the coming integration of AI into always-on devices. Sponsor: Meter, an integrated wired/wireless/cellular networking stack (meter.com/htt). 00:00 Cold Open + Sponsor: Meter Networking Stack 00:18 Welcome to Project Synapse (and immediate chaos) 00:57 'Something Big Is Happening': AI feels like COVID-speed disruption 02:57 OpenClaw goes viral: 160k instances and easy DIY clones 04:03 Claude Code 'Cowork' on Windows… and why it's broken 06:47 Rebuilding Cowork in a day with OpenAI Codex 5.3 08:18 Why Opus 4.6 feels like a step-change: memory, autonomy, agent teams 11:24 Model leapfrogging + the end of 'can AI write code?' debates 14:45 Hallucinations, 'I don't know,' and self-correction in modern models 18:42 Autonomous agents in practice: cron-like loops, tool use, and fallout 21:00 MCP security: powerful connectors, scary permissions, and 500 zero-days 24:33 Shadow AI & skill marketplaces: the app-store malware analogy 32:02 Incentives drive risk: move fast culture, confident wrong answers, burnout 34:16 AI Agents Boost Productivity… and Raise the Bar at Work 35:14 Warnings of a Coming AI-Driven Crash (and Why We're Not Steering Away) 36:28 "I Quit to Write Poetry": Existential Dread & On the Beach Vibes 37:21 Tech Safety Is Reactive: Seatbelts, Crashes, and the AI Double-Edged Sword 39:42 Fast-Moving Threats: Agents Hacking Infrastructure & Security Debt 40:54 From Doom to Adaptation: Using the Same Tools to Survive the Disruption 42:21 Why We're Numb to AI Warnings + The 'Free Energy' Thought Experiment 46:43 AGI Is Already Here? Prompts, Ego, and the 'If It Quacks Like a Duck' Test 48:56 Deepfake Video Leap: Seedance, Perfect Voices, and What's Real Anymore 52:39 Contain the Damage: 'Don't Say No—Say How' and Shadow AI in Companies 54:58 Holodeck on the Horizon: VR + GenAI + Wearables (Meta, Apple, OpenAI/Ive) 59:53 Meta's AI Reality Check: Bots, the Meta AI App, 'Vibes,' and Who's Making Money 01:04:41 Final Wrap + Sponsor Thanks

Send a textAutonomy sounds like progress until the system turns your choices against you. We dive into how AI agents change the risk equation, why “don't trust, verify” now beats “trust but verify,” and what to do when the update button itself becomes the attack vector.We start with the Ivy League leak tied to Harvard and UPenn, where attackers exposed admissions hold notes that map influence rather than credit cards. That context turns routine records into leverage for extortion, social pressure, and geopolitical targeting. From there, we trace the surge of agentic AI in the workplace as employees paste code, legal docs, and sensitive files into chat interfaces. The real accelerant is MCP, the model context protocol that standardizes connections across Google Drive, Slack, databases, and more. Like USB for AI, MCP makes integration simple and powerful, but a single prompt injection can pivot across everything the agent can reach.Security gets messier with supply chain compromise. A China‑nexus campaign allegedly hijacked the Notepad++ update mechanism, handing a bespoke backdoor to developers who did the right thing. We unpack how to keep patching while reducing risk: signed updates, independent checksum checks, tight egress policies for updaters, and strong monitoring around update flows. On the policy front, Rhode Island's vendor transparency rule forces companies to name who buys data. It is a nutrition label for privacy, and it lets users and watchdogs finally connect the dots between friendly interfaces and aggressive brokers.We close with concrete defenses that raise the floor. Move high‑value accounts to FIDO2 hardware keys or platform passkeys to block phishing at the protocol level. Scope agent permissions narrowly, isolate MCP connectors by function, and require explicit approvals for sensitive actions. Log everything an agent touches and review those trails. Autonomy should be earned, minimal, and observable. If AI is going to act on your behalf, it must prove itself at every step.If this conversation helps you think differently about agents, influence mapping, and how to lock down your stack, subscribe, share with a teammate, and leave a quick review telling us the one control you plan to implement this week.Support the show

We discuss the variance of dice in MCP but comparatively how interesting the later part of games due to the unpredictability.

What if the real risk isn't adopting AI agents, but refusing to? James Nettesheim, CISO & Head of Enterprise Technology at Block, argues that principled risk-taking beats playing it safe. James shares Block's journey co-designing the Model Context Protocol with Anthropic and building Goose, their open-source general-purpose agent that enables anyone in the company to write security detections using natural language.James also explores Block's Binary Intelligent Triage system achieving 99.9% accuracy, their data safety levels framework, and practical strategies for balancing autonomous AI capabilities with human oversight. James offers candid insights about implementing AI security principles, the evolution from tool experts to domain experts, and why open source remains fundamental to Block's mission of economic empowerment and technological innovation. Topics discussed:Co-designing of MCP with Anthropic and developing of Goose as an open-source general-purpose AI agentImplementing prompt injection defenses and adversarial AI concepts to harden Goose against malicious instructions and attacksRolling out AI responsibly through data safety levels modeled after CDC bio-contamination protocols for sensitive data handlingDemocratizing detection engineering by enabling anyone at Block to write detections using natural languageAchieving 40% of new detections created with AI assistance through recipes, playbooks, and automated tuning capabilitiesBuilding Binary Intelligent Triage system that analyzes historical alerts and investigations to achieve 99.9% automated triage accuracyBalancing autonomous AI capabilities with human oversight, requiring PR reviews and maintaining accountability for agent-generated codeTransitioning from tool expertise to domain expertise as the future skill set needed for detection and response professionalsBlock's commitment to open source development driven by economic empowerment mission and desire to build accessible financial tools Listen to more episodes: Apple Spotify YouTubeWebsite

Agents will soon retrieve data from MCP servers and offer formatting options you can interact with. The Copilot "preview pane" opens Word, Excel, and PowerPoint alongside your M365 Chat results. Viva Engage introduces a way to hide your colleagues messages from your feed. What else landed this week? 0:00 Welcome 1:55 Open Word, Excel, and PowerPoint Files in Microsoft 365 Copilot Chat - MC1225199 4:03 Microsoft Teams: Teams Live Events is retiring - MC1226495 8:17 Enhancing Model Context Protocol (MCP) based agents with rich interactive UI widgets support - MC1227627 14:00 Viva Engage: New option to hide a user's messages - MC1226225 21:11 Drawn electronic signatures with eSignature for Microsoft 365 - MC1225195 24:09 Change meeting organizer via PowerShell cmdlet in Exchange Online - MC1227623

The news this week highlights shifts in Linux from multiple angles. What's evolving, why it matters, and that moment where the future actually works.Sponsored By:Jupiter Party Annual Membership: Put your support on automatic with our annual plan, and get one month of membership for free! Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love. Support LINUX UnpluggedLinks:

This week we're joined by Dana Lawson, CTO at Netlify. We talk about her journey from the US Army to leading engineering teams at companies like GitHub, New Relic, and now Netlify. We discuss Netlify's evolution from JAMstack to AI-powered developer tools, including Agent Runners and their MCP server. We also explore the concept of "Agent Experience" (AX) as a new paradigm alongside UX and DX, and how hiring practices are evolving in the age of AI.Netlify: https://www.netlify.com/Agent Experience Hub: https://www.netlify.com/agent-experience/agentexperience.ax: https://agentexperience.ax/Agent Runners: https://www.netlify.com/platform/agent-runners/Netlify MCP Server: https://docs.netlify.com/build/build-with-ai/netlify-mcp-server/Dana on LinkedIn: https://www.linkedin.com/in/dglawson/Dana's LeadDev Profile: https://leaddev.com/community/dana-lawsonDana's UXDX Profile: https://uxdx.com/profile/dana-lawson/

Ep 277Western governments BUILT the backdoors China walked through. They are called "lawful intercept" systems.Apple's new iPhone and iPad security feature limits cell networks from collecting precise location data | TechCrunchFlorian Roth: Notepad++ hacked. This is bad. Putty level bad.iPhone 5s Gets New Software Update 13 Years After LaunchWindows 11 ima 1 milijardu aktivnih korisnika.Announcing msgvault: lightning fast private email archive and search system, with terminal UI and MCP server, powered by DuckDB – Wes McKinneyMake Finder Window Columns Resize to Fit Filenames - TidBITSApple Propelled to Record Q1 2026 Financials by iPhone and Services - TidBITSSdW (re-)joins Apple.Steve Moser: I'm not sure which is better news: Alan Dye leaving Apple or Sebastiaan joiningBasic Apple Guy: Nature is healing.Renaud Lienhart: Sounds like one of Steve Lemay's first task after Dye's departure is to try to hire back all the designers who were alienated & departed over the past decade. This is great.Shipping at Inference-Speed | Peter SteinbergerClawdbot / Moltbot / OpenClaw — Personal AI AssistantClawdbot Showed Me What the Future of Personal AI Assistants Looks LikeMoltbookI Spent 40 Hours Researching Clawdbot.Clawd disaster incomingAndrej Karpathy: A few random notes from claude coding quite a bit last few weeks.This white hat is providing over-eager AI builders a much-needed wake up call.ClawCon ?!2 nedelje za C compiler koji radi.i've made a tragic discovery using clawdbot. there simply aren't that many tasks in my personal life that are worth automatingDušan Dž.: Tim robota mi programira u Claude Code. OpenClaw mi radi istraživanje tržišta. Robot-usisivač pere pod. A ja? Ja slažem veš. Nisam se nadao ovakvoj budućnosti.Apple WINS AI because INTEL and MICROSOFT got it wrong.Apple Just Made Its Second-Biggest Acquisition Ever After BeatsXcode 26.3 unlocks the power of agentic codingApple introduces new AirTag with expanded range and improved findability10+ Things to Know About the New AirTag 2The chime has changed from the note "F" to the note "G".Oliur / ASUS just beat Apple to it.ROG Strix 5K XG27JCG 5K-GPU Supported Refresh Rate ListApple has landed the rights to turn ‘MISTBORN' into a film franchise & ‘THE STORMLIGHT ARCHIVE' into a TV series.Researcher builds bizarre 128-byte USB drive the size of a dinner plate using ancient pre-semiconductor magnetic core memory technology — data disappears once it is read, requiring special handlinghollywood.computerZahvalniceSnimano 6.2.2026.Uvodna muzika by Vladimir Tošić, stari sajt je ovde.Logotip by Aleksandra Ilić.Artwork epizode by Saša Montiljo, njegov kutak na Devianartu

Juan and Tim grab a beer and rant about decision intelligence and context graphs, MCP vs Skills, and how companies really have a work problem (not a data/AI problem) and what is the maturity model to get that work doneSee omnystudio.com/listener for privacy information.

On our 500th episode James and Frank celebrate the milestone, reminisce about their mobile‑dev roots, and dig into how AI, the Copilot CLI/SDK and the Model Context Protocol (MCP) are reshaping workflows. Frank demos an MCP‑powered tool that turns app reviews into prioritized GitHub issues and automations — a real example of AI-as-glue — with practical takeaways on prompt engineering, UI extensions, and when to automate versus curate manually. Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us ⭐⭐ Machine transcription available on http://mergeconflict.fm

Mushrooms. So cute. So tasty. So very toxic. Humans have loved and feared mushrooms since before written history. In this episode, Hallie discusses the tumultuous history of this relationship, and a few of the most deadly mushrooms in the world. For patrons of the MCP, this episode is ad-free and extended. Join the MCP Patreon community

Lil AI productivity secret: we've become the duct tape for AI.