In this episode, Kat Cosgrove (SIG Docs Technical Lead, SIG Release Subproject Lead, and Steering Committee member) and Natali Vlatko (SIG Docs Co-Chair, Steering Committee member for the TODO Group, and Open Source Architect at Cisco) join hosts Kaslin Fields and Abdel Sghiouar to discuss the newly published Kubernetes AI usage policy. We dive into the legal and administrative reasoning behind the policy—including why AI tools cannot legally sign the Contributor License Agreement (CLA) or co-author PRs—and explore how maintainers manage the influx of "AI slop" PRs, spam comments, and restricted AI note-taker bots in community meetings. The discussion highlights the balance between human accountability and AI as an enhancer, while sharing actionable advice on how new contributors can sustainably get involved with SIG Docs, issue wrangling, and the Kubernetes Release Team.
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News of the week Apple Native Container Tool for macOS 1.0: Apple has shipped version 1.0 of its native container tool for macOS. Built in Swift specifically for Apple Silicon, it departs from traditional shared-VM setups like Docker Desktop by isolating every single Linux container inside its own dedicated micro-VM using the native macOS Virtualization framework. Read more on Cloud Native Now.
Google OpenRL: Google launched OpenRL, a new open-source project designed to streamline the training and reinforcement learning loops of large language models. The tool brings declarative, Kubernetes-style resource orchestration concepts to the messy process of AI model fine-tuning. Read more on Cloud Native Now.
CNCF Welcomes New Members: At KubeCon CloudNativeCon India, the CNCF announced they added 14 new members, end Users, and non-profit organizations, highlighting the continued growth of the Cloud Native Ecosystem. One of the new members is Loveable, who was a recent guest on the show. We highly recommend you go listen to Episode 268 about the Agent Sandbox. Read the full announcement on PR Newswire.
Is a Pod the Right Deployment Unit for an AI Agent?: Lin Sun from Solo published a community post on the CNCF blog questioning whether the classic Kubernetes Pod primitive is still the best abstraction for hosting autonomous, long-running AI agents and introducing Agent-substrate, a project attempting to bring a solution to the table. Read more on the CNCF Blog.
Links from the interview Kubernetes AI Usage Policy – Read the community's official guidelines and rules for AI-assisted contributions.
TODO Group Steering Committee – A Linux Foundation project bringing OSPO professionals and enthusiasts together.
Contributor License Agreement (CLA) – Standard agreement required for all human contributors, which AI agents cannot legally sign.
Kubernetes SIG Docs – Get involved with the documentation community.
SIG Docs Style Guide – Learn the style guidelines for contributing to Kubernetes docs.
Kubernetes SIG Release – Details on how to get involved with the release cycle.
Links from the post-interview chat Linus Torvalds on AI LinkedIn Post – Torvalds' clarification on using AI as a helper tool rather than writing kernel C++ code.
Devoxx– A popular developer conference in Europe
Prowbot GitHub Repo – Kubernetes' main CI/CD bot handling PR automation.
My guest today is Cisco CEO Chuck Robbins. Cisco is one of those big companies that everyone has heard of but most of us don’t have to interact with very much; they’re not really a consumer brand. But without Cisco's actual routers and switches and silicon — and the software to make those things work — there’s no internet, no cloud, and no AI.
But a data center is a really unpleasant neighbor to have, and there’s robust opposition to new data center builds all over the country. So I had to start by asking what feels, strangely, like one of the most urgent questions of the moment: Should we build data centers in space?
Links:
Nvidia launches space computing, rocketing AI Into orbit | Nvidia
Nvidia’s AI dominance expands to networking | CRN
Amid rising pushback, 2025 data center cancellations surge | Heatmap
Billionaires want data centers everywhere, including space | The Verge
How Ciena keeps the internet online | Decoder
Okta’s CEO is betting big on agent identity | Decoder
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Credits:
Decoder is a production of The Verge and part of the Vox Media Podcast Network.
Decoder is produced by Kate Cox and Nick Statt and edited by Ursa Wright. Our editorial director is Kevin McShane.
The Decoder music is by Breakmaster Cylinder.
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Vijoy Pandey of Outshift by Cisco lays out his vision for an “Internet of Cognition,” where AI agents can share context, build reputation, and collaborate safely at scale. He offers a useful mental model for superintelligence: progress has to scale in two directions — up, through better individual models, and out, through networks of agents and humans thinking together. The conversation explores how distributed, protocol-driven agent systems could give enterprises fine-grained permissions, auditability, and controlled interfaces, in contrast to today’s centralized frontier models. Vijoy also walks through Cisco’s internal CAIPE system of 20 cooperating agents, the open-source AGNTCY project, and a live multi-agent healthcare demo spanning diagnostics, insurance, pharmacy, and scheduling.
LINKS:
AGNTCY Project
Open source multi-agent infrastructure under Linux Foundation governance. Covers discovery, identity, communication, observability. Vijoy walks through the architecture at [00:34:57] and [00:41:17].
Scaling Out Superintelligence Whitepaper
The technical whitepaper detailing the Internet of Cognition architecture, three-layer stack, and cognition state protocols. Referenced at [01:25:40].
Internet of Cognition Interactive Demo
Clickable walkthrough showing per-agent activity, intent, context, and collective reasoning across a multi-agent SRE system. Vijoy demos at [01:26:20].
CAIPE Project (GitHub)
Cloud Native AI Platform Engineer. Multi-agent system with participation from Adobe, AWS, Cisco, Nike. 20 agents, 100+ tool calls, 10+ workflows. Referenced at [00:11:52].
Sponsors:
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CHAPTERS:
(00:00) About the Episode
(04:16) Cisco and networking foundations
(13:34) Jarvis and ASI vision (Part 1)
(18:16) Sponsors: Tasklet | VCX
(21:09) Jarvis and ASI vision (Part 2) (Part 1)
(31:46) Sponsor: Claude
(33:59) Jarvis and ASI vision (Part 2) (Part 2)
(34:00) Practical multi-agent examples
(50:02) Multi-agent plumbing architecture
(01:01:44) Agent identity and TBAC
(01:15:23) Internet of cognition fabric
(01:21:48) Emergent agents and safety
(01:36:52) Outro
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Jeetu Patel is the president and chief product officer at Cisco, where he leads a team of 30,000 people and is playing a central role in the massive AI infrastructure buildout happening right now. Previously, he spent five years as CPO at Box and 17 years running his own startup. Recently Jeetu organized an AI summit featuring industry leaders like Jensen Huang, Sam Altman, Marc Andreessen, and Fei-Fei Li.
We discuss:
1. How Cisco went AI-first across 90,000 employees
2. His six-part framework for building great companies: timing, market, team, product, brand, distribution
3. Why he says he couldn’t have done this job without AI
4. His “right to win” strategic framework
5. His communication framework for preventing “packet loss” across an organization
6. Why he flips “praise in public, criticize in private” and does the exact opposite
7. The important communication lesson his mother taught him
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—
Where to find Jeetu Patel:
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• LinkedIn: https://www.linkedin.com/in/jeetupatel
• Website: https://blogs.cisco.com/author/jeetupatel
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• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/
—
In this episode, we cover:
(00:00) Introduction and welcome
(04:15) Insights from Cisco’s Al summit
(08:45) Transforming Cisco into an Al-first company
(15:33) What Cisco actually does in the Al infrastructure stack
(19:09) The future of Al
(24:36) Raising kids in the AI era
(29:46) “Permission to play” framework
(36:50) Lessons from great CEOs
(42:02) Leading at scale
(50:54) Why Jeetu inverts the ‘praise in public, criticize in private’ rule
(57:45) Surrounding yourself with good human beings
(58:35) Lessons from loss
(01:03:21) Career advice: platforms, hunger, and preparation
(01:10:21) The six-part framework for building great companies
(01:19:05) Lightning round and final thoughts
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In this first of the year ICYMI episode, Jon Krohn selects his favorite moments from January’s SuperDataScience interviews. Listen to why incentivizing workers is the best way to get them to disclose their use of AI tools and pave the way for an AI-forward future, how AI continues to mimic human development in its own evolution, the importance of evaluation in building AI systems, and how to keep your best employees (and also: how to know your value) with guests Sadie St. Lawrence, Ashwin Rajeeva, Sinan Ozdemir, Vijoy Pandey, and Ethan Mollick.
Additional materials: www.superdatascience.com/964
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
Dr. Vijoy Pandey returns to the show to talk to Jon Krohn about Cisco’s work to advance medicine and mitigate the impact of climate change with distributed artificial super-intelligence. Dr. Vijoy Pandey believes in a future where humans and AI agents work together to tackle our biggest challenges. For this to happen, we will need to have multi-agent systems and open-source platforms that let agents work together, avoiding the phenomenon of AI agents being “isolated geniuses” unable to collaborate. He elaborates on what Cisco is doing to close this gap.
This episode is brought to you by the Dell, by Intel, by Fabi and by Scaylor.
Additional materials: www.superdatascience.com/961
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
(03:55) A definition of artificial super-intelligence
(14:03) Distributed learning through Cisco’s Outshift
(21:29) The semantic protocols for sharing intent in a distributed artificial super-intelligence framework
(37:44) The cognitive memory fabric of the distributed artificial super-intelligence framework
(46:24) Using cognitive engines as part of the distributed artificial super-intelligence framework
In this episode of Eye on AI, Craig Smith sits down with Anurag Dhingra, Senior Vice President and General Manager at Cisco, to explore where AI is actually creating value inside the enterprise. Rather than focusing on flashy demos or speculative futures, this conversation goes deep into the invisible layer powering modern AI: infrastructure. Anurag breaks down how AI is being embedded into enterprise networking, security, observability, and collaboration systems to solve real operational problems at scale.
From self-healing networks and agentic AI to edge computing, robotics, and domain-specific models, this episode reveals why the next phase of AI innovation is less about chatbots and more about resilient systems that quietly make everything work better. This episodeis perfect for enterprise leaders, AI practitioners, infrastructure teams, and anyone trying to understand how AI moves from theory into production.
Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI
(00:00) Why AI Only Matters If the Infrastructure Works (01:22) Cisco's Evolution (04:39) Connecting Networks, People, and Experiences at Scale (09:31) How AI Is Transforming Enterprise Networking (12:00) Edge AI, Robotics, and Real-World Reliability (14:18) Security Challenges in an Agent-Driven Enterprise (15:28) What Agentic AI Really Means (Beyond Automation) (20:51) The Rise of Hybrid AI: Cloud Models vs Edge Models (24:30) Why Small, Purpose-Built Models Are So Powerful (29:19) Open Ecosystems and Agent-to-Agent Collaboration (33:32) How Enterprises Actually Adopt AI in Practice (35:58) Building AI-Ready Infrastructure for the Long Term (40:14) AI in Customer Experience and Contact Centers (44:14) The Real Opportunity of AI and What Comes Next
In this November episode of “In Case You Missed It” series, Jon Krohn selects his favorite clips from the month. Hear from Shirish Gupta and Tyler Cox (Episode 939), Vikoy Pandey (Episode 941), Marc Dupuis (Episode 937), and Maya Ackerman (Episode 943) on getting back to human motivation and the importance of evaluating the tools and data we use.
Additional materials: www.superdatascience.com/948
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
Vijoy Pandey imagines a bold new society in which agents and humans make scientific discoveries and complete physical tasks together, and he tells Jon Krohn about his work at AGNTCY, Cisco’s open-source platform for the Internet of Agents. Listen to the episode to hear Vijoy Pandey talk about how a future society in which multi-agents and humans interact may be a real possibility, what TCP/IP is, how to find trustworthy AI agents, and how to get your hands on AGNTCY today!
This episode is brought to you by the Dell, by Intel, by Fabi and by Gurobi.
Additional materials: www.superdatascience.com/941
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
(02:37) All about AGNTCY
(12:04) How an agent-human society might function
(15:19) What an “Internet of Agents” means
(27:17) The future of access management
(41:39) How to trust AI agents
(48:49) How to get started with AGNTCY
AI isn’t just changing software, it’s causing the biggest buildout of physical infrastructure in modern history.
In this episode, Raghu Raghuram (a16z) speaks with Amin Vahdat, VP and GM of AI and Infrastructure at Google, and Jeetu Patel, President and Chief Product Officer at Cisco, about the unprecedented scale of what’s being built — from chips to power grids to global data centers.
They discuss the new “AI industrial revolution,” where power, compute, and network are the new scarce resources; how geopolitical competition is shaping chip design and data center placement; and why the next generation of AI infrastructure will demand co-design across hardware, software, and networking.
The conversation also covers how enterprises will adapt, why we’re still in the earliest phase of this CapEx supercycle, and how AI inference, reinforcement learning, and multi-site computing will transform how systems are built and run.
Resources:
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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Cisco is well known for its data, networking, security, and collaboration products. On today’s episode, Cisco’s president and chief product officer, Jeetu Patel, joins Sam for a discussion about artificial intelligence, a “megatrend” Jeetu sees as perhaps more significant than the development of the internet or the automobile because of its ability to build on past technological advances.
Jeetu and Sam discuss how to manage AI and how to staff for it — Jeetu argues that replacing less experienced or younger workers with technology deprives organizations of key perspectives and new ideas, and instead advocates for developing reverse-mentoring programs inside organizations. Read the episode transcript here.
Guest bio:
Jeetu Patel, Cisco’s president and chief product officer, combines product design and development expertise, operational rigor, and market understanding to create high-growth businesses. He is tasked with building world-class products to solve customers’ problems, and connect and protect every aspect of their organization in the AI era. Previously a general manager at Cisco, he led the strategy and development of its Security and Collaboration businesses.
Before Cisco, Patel was the chief product officer and chief strategy officer at cloud content management company Box. He’s also held roles at EMC, including chief executive of its Syncplicity business unit, CMO for the Information Intelligence Group, and chief strategy officer. He currently serves on the board of JLL, a commercial real estate services company. Jeetu has a bachelor’s degree in information decision sciences from the University of Illinois at Chicago, and lives in the San Francisco Bay Area.
Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
What happens when a startup becomes a giant—and then has to reinvent itself all over again?
In this episode, Martin Casado sits down with Raghu Raghuram (former CEO of VMware) and Jeetu Patel (President and CPO at Cisco) for a deep, tactical conversation on scaling, disruption, and navigating transformation from the inside. They share hard-won lessons from leading two of the most iconic infrastructure companies in tech—through waves like virtualization, cloud, containers, and now AI.
They cover:
How to keep innovation alive inside large companies
Why the best companies operate with a founder’s mindset, even without founders
The difference between selling to buyers vs. practitioners
Why the story is the strategy, and how to tell it at scale
How Cisco is rebuilding its startup DNA in the age of AI
If you're building or leading through a major tech wave, this episode is a playbook.
Timecodes:
0:00 Introduction
2:02 Weapons of Mass Disruption: Abstractions, Business Models, and Cloud
5:57 Cisco’s Missed Cloud Wave & Resetting for Innovation
6:39 Operating Like a Startup: Speed, Scale, and Leadership
10:00 Go-to-Market Challenges: Fencing Off Innovation
11:04 Organic vs. Inorganic Growth: Lessons from VMware
12:04 The 10x Rule and Competing with Incumbents
14:39 Structuring for Disruption: Two-Pizza Teams and Ideal Customer Profiles
18:43 Storytelling as Strategy: Galvanizing Large Organizations
19:42 The AI Wave: Consumerization and Infrastructure Demands
25:34 Founders vs. Operators: Leading Transformations
31:47 Product-Led Organizations: From Sales to Product Focus
34:35 The Future of Infrastructure: AI, Market Size, and Vertical Integration
39:34 Timing, Market, Team, Product, Brand, and Scale
41:19 Authenticity, Opportunity, and Final Thoughts
Resources:
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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Today, we're joined by Vijoy Pandey, SVP and general manager at Outshift by Cisco to discuss a foundational challenge for the enterprise: how do we make specialized agents from different vendors collaborate effectively? As companies like Salesforce, Workday, and Microsoft all develop their own agentic systems, integrating them creates a complex, probabilistic, and noisy environment, a stark contrast to the deterministic APIs of the past. Vijoy introduces Cisco's vision for an "Internet of Agents," a platform to manage this new reality, and its open-source implementation, AGNTCY. We explore the four phases of agent collaboration—discovery, composition, deployment, and evaluation—and dive deep into the communication stack, from syntactic protocols like A2A, ACP, and MCP to the deeper semantic challenges of creating a shared understanding between agents. Vijoy also unveils SLIM (Secure Low-Latency Interactive Messaging), a novel transport layer designed to make agent-to-agent communication quantum-safe, real-time, and efficient for multi-modal workloads.
The complete show notes for this episode can be found at https://twimlai.com/go/737.
John Chambers led Cisco through the rise of the internet—transforming it into the world’s most valuable company at its peak.
On this week’s Grit, the former Cisco CEO unpacks how he scaled the business from $70M to $50B+, pioneered M&A as a growth strategy with 180 acquisitions, and built what many called the best sales force in tech.
Now leading his own venture firm, Chambers shares how he’s backing the next generation of AI-native startups.
Guest: John T. Chambers, Former Cisco Executive Chairman & CEO, JC2 Ventures Founder & CEO
Chapters:
00:00 Trailer
00:45 Introduction
01:45 Track record, relationships, trust
13:21 Acquisitions every year
17:32 Product-focused
24:40 Family, dyslexia, and without shame
30:46 Wang Laboratories
35:59 Ready being CEO
40:17 Reinventing your business
50:08 Numbers don’t lie
54:09 Sales calls and making mistakes
56:20 Adapting leadership style
1:06:32 Best leadership year ever
1:13:35 A busy, exhausting schedule
1:22:07 Candid with me
1:25:21 What “grit” means to John
1:26:43 Outro
Mentioned in this episode: John Doerr, OpenAI, Wang Laboratories, IBM, Microsoft, Google, Amazon, Apple Inc., Meta Platforms, FMC Corporation, DuPont de Nemours, Inc., John Mortgage, Don Valentine, Sequoia Capital, Alcatel Mobile, Lucent Technologies, Inc., Verizon Communications Inc., AT&T Inc., Rick Justice, Pankage Patel, Larry Carter, CNBC, Jim Cramer, George Kurtz, CrowdStrike, Randy Pond, Rebecca Jacoby, Mel Selcher
Links:
Connect with John
X
LinkedIn
Connect with Joubin
X
LinkedIn
Email: grit@kleinerperkins.com
Learn more about Kleiner Perkins
Code reviews can be highly beneficial but tricky to execute well due to the human factors involved, says Adrienne Braganza Tacke, author of *Looks Good to Me: Actionable Advice for Constructive Code Review.* In a recent conversation with *The New Stack*, Tacke identified three challenges teams must address for successful code reviews: ambiguity, subjectivity, and ego.
Ambiguity arises when the goals or expectations for the code are unclear, leading to miscommunication and rework. Tacke emphasizes the need for clarity and explicit communication throughout the review process. Subjectivity, the second challenge, can derail reviews when personal preferences overshadow objective evaluation. Reviewers should justify their suggestions based on technical merit rather than opinion. Finally, ego can get in the way, with developers feeling attached to their code. Both reviewers and submitters must check their egos to foster a constructive dialogue.
Tacke encourages programmers to first review their own work, as self-checks can enhance the quality of the code before it reaches the reviewer. Ultimately, code reviews can improve code quality, mentor developers, and strengthen team knowledge.
Learn more from The New Stack about code reviews:
The Anatomy of Slow Code Reviews
One Company Rethinks Diff to Cut Code Review Times
How Good Is Your Code Review Process?
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Nick delves into the intricacies of technical book writing with authors Adrienne Braganza Tacke and Dylan Hildenbrand. We talk about the process of working with a publisher, coming up with an outline, actually writing the book, and everything that comes after the book is finished.
Join the discussion
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Featuring:
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Nick Nisi – Website, GitHub, Mastodon, X
Show Notes:
Adrienne’s books
Looks Good to Me: Constructive Code Reviews
Coding for Kids: Python: Learn to Code with 50 Awesome Games and Activities
Dylan’s book
SvelteKit Up and Running
Something missing or broken? PRs welcome!
All great teams need to improvise under pressure, but underpinning this should be a set of tried-and-tested playbooks that let you orchestrate and replicate winning strategies. Cisco's John Chambers created a library of living playbooks — covering culture, acquisitions, crises, and more — to astounding effect as he took Cisco from a small tech supplier to the most valuable company on the planet.
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Wayfair describes itself as the “the destination for all things home: helping everyone, anywhere create their feeling of home.” It provides an online platform to acquire home furniture, outdoor decor and other furnishings. It also supports its suppliers so they can use the platform to sell their home goods, explained Natali Vlatko, global lead, open source program office (OSPO) and senior software engineering manager, for Wayfair as the featured guest in Detroit during KubeCon + CloudNativeCon North America 2022.
“It takes a lot of technical, technical work behind the scenes to kind of get that going,” Vlatko said. This is especially true as Wayfair scales its operations worldwide. The infrastructure must be highly distributed, relying on containerization, microservices, Kubernetes, and especially, open source to get the job done.
“We have technologists throughout the world, in North America and throughout Europe as well,” Vlatko said. “And we want to make sure that we are utilizing cloud native and open source, not just as technologies that fuel our business, but also as the ways that are great for us to work in now.”
Open source has served as a “great avenue” for creating and offering technical services, and to accomplish that, Vlatko amassed the requite tallent, she said. Vlatko was able to amass a small team of engineers to focus on platform work, advocacy, community management and internally on compliance with licenses.
About five years ago when Vlatko joined Wayfair, the company had yet to go “full tilt into going all cloud native,” Vlatko said. Wayfair had a hybrid mix of on-premise and cloud infrastructure. After decoupling from a monolith into a microservices architecture “that journey really began where we understood the really great benefits of microservices and got to a point where we thought, ‘okay, this hybrid model for us actually would benefit our microservices being fully in the cloud,” Vlatko said. In late 2020, Wayfair had made the decision to “get out of the data centers” and shift operations to the cloud, which was completed in October, Vlatko said.
The company culture is such that engineers have room to experiment without major fear of failure by doing a lot of development work in a sandbox environment. “We've been able to create production environments that are close to our production environments so that experimentation in sandboxes can occur. Folks can learn as they go without actually fearing failure or fearing a mistake,” Vlatko said. “So, I think experimentation is a really important aspect of our own learning and growth for cloud native. Also, coming to great events like KubeCon + CloudNativeCon and other events [has been helpful]. We're hearing from other companies who've done the same journey and process and are learning from the use cases.”
In this episode of The New Stack’s On the Road show at Open Source Summit in Austin, Julia Ferraioli, open source technical leader at Cisco’s open source programs office, spoke with The New Stack about some alternative ways to define what is and is not ‘open source.’
When someone says, well, that’s ‘technically’ open source, it’s usually to be snarky about a project that meets the legal criteria to be open source, but doesn’t follow the spirit of open source. Ferraioli doesn’t think that the ‘classic’ open source project, like a Kubernetes or Linux, are the only valid models for open source. She gives the sample of a research project — the code might be open sourced specifically so that others can see the code and reproduce the results themselves. However, for the research to remain valid, they it can’t accept any contributions.
“It’s no less open source than others,” Ferraioli said about the hypothetical research project. “If you break things down by purpose, it’s not always that you’re trying to build the robust community.” The social model of open source, Ferraioli says, is about understanding the different use cases for open source, as well as providing a framework for determining what appropriate success metrics could be depending on what the project’s motivations are. And if you’re just doing a project with friends for laughs, well, quantifying fun isn’t going to be easy.
<p>How can you can speed up Python? Have you thought of using a JIT (Just-In-Time Compiler)? This week on the show, we have Real Python author and previous guest Anthony Shaw to talk about his project Pyjion, a drop-in JIT compiler for CPython 3.10.</p>
<p>Anthony has been working on Pyjion over the past year and recently released version 1.0. He talks about how he took over the project from Brett Cannon and Dino Viehland. He covers the background on compilers and assembly that he needed to take on this project. </p>
<p>We discuss where a tool like this can speed up your Python code, and we consider alternative solutions. We also talk about his desire to make the project as deeply compatible with Python code as possible. </p>
<p>Anthony talks about how his dive into writing the <em>CPython Internals</em> book led him into the project. We talk about what type of developer would benefit from exploring the book. </p>
<p>We also cover his recent Real Python article, titled “Advanced Visual Studio Code for Python Developers.” It’s an excellent resource that VS Code users should bookmark to revisit as they grow with the tool.</p>
<div class="alert alert-primary" role="alert">
<p><strong>Spotlight:</strong> <a href="https://realpython.com/products/cpython-internals-book/">CPython Internals Book: Your Guided Tour Through the Python 3 Interpreter</a></p>
<p>Unlock the inner workings of the Python language, compile the Python interpreter from source code, and participate in the development of CPython.</p>
</div>
<p>Topics:</p>
<ul>
<li>00:00:00 – Introduction</li>
<li>00:02:15 – Cloud Developer Advocate at Microsoft</li>
<li>00:04:57 – Pyjion, a drop-in JIT compiler for CPython</li>
<li>00:07:52 – PyCon 2020 & 2021 talks and wanting to take on the project</li>
<li>00:12:46 – How Pyjion uses .NET 6 </li>
<li>00:17:32 – Trying out Pyjion functionality online </li>
<li>00:21:43 – Sponsor: Honeybadger</li>
<li>00:22:28 – Portability of projects using Pyjion</li>
<li>00:29:55 – Focus on compatibility with Python code</li>
<li>00:33:07 – Choosing to make it based on Python 3.10</li>
<li>00:37:45 – What would be prerequisites to work on the project?</li>
<li>00:40:40 – Other ways to help with project</li>
<li>00:44:34 – CPython Internals: Who is the book for?</li>
<li>00:49:46 – What resources do you need to work through the book?</li>
<li>00:52:04 – Spotlight: CPython Internals Book</li>
<li>00:53:21 – Do you use an IDE or code editor?</li>
<li>00:56:12 – Why did you decide to write the book?</li>
<li>00:57:12 – Advanced Visual Studio Code for Python Developers</li>
<li>01:03:20 – What are you excited about in the world of Python?</li>
<li>01:04:03 – What do you want to learn next?</li>
<li>01:05:33 – Thanks and goodbye</li>
</ul>
<p>Show Links:</p>
<ul>
<li><a href="https://github.com/tonybaloney/pyjion">Pyjion - A JIT for Python based upon CoreCLR</a></li>
<li><a href="https://pyjion.readthedocs.io/en/latest/index.html">Pyjion main documentation</a></li>
<li><a href="https://live.trypyjion.com/">live.trypyjion.com</a></li>
<li><a href="https://www.youtube.com/watch?v=I4nkgJdVZFA">Anthony Shaw - Why is Python slow? - YouTube</a></li>
<li><a href="https://www.youtube.com/watch?v=YFeUUdKBrJ8">Restarting Pyjion, a general purpose JIT for Python- is it worth it? - YouTube</a></li>
<li><a href="https://docs.microsoft.com/en-us/dotnet/standard/clr">Common Language Runtime (CLR) overview - .NET | Microsoft Docs</a></li>
<li><a href="https://tonybaloney.github.io/posts/extending-python-with-assembly.html">Writing Python Extensions in Assembly</a></li>
<li><a href="https://link.springer.com/book/10.1007/978-1-4842-5076-1">Beginning x64 Assembly Programming | SpringerLink</a></li>
<li><a href="https://www.pyston.org/">Pyston | Python Performance</a></li>
<li><a href="https://www.pypy.org/">PyPy</a></li>
<li><a href="https://github.com/facebookincubator/cinder">facebookincubator/cinder: Instagram’s performance oriented fork of CPython.</a></li>
<li><a href="https://hypothesis.readthedocs.io/en/latest/">Welcome to Hypothesis! — Hypothesis 6.36.0 documentation</a></li>
<li><a href="https://realpython.com/products/cpython-internals-book/">CPython Internals Book – Real Python</a></li>
<li><a href="https://realpython.com/advanced-visual-studio-code-python/">Advanced Visual Studio Code for Python Developers – Real Python</a></li>
<li><a href="https://github.com/tonybaloney/vscode-pets">vscode-pets: Adds playful pets 🦀🐱🐶 in your VS Code window</a></li>
<li><a href="https://docs.python.org/3.11/whatsnew/3.11.html">What’s New In Python 3.11 — Python 3.11.0a4 documentation</a></li>
<li><a href="https://suif.stanford.edu/dragonbook/">Compilers: Principles, Techniques, and Tools (Dragon Book)</a></li>
</ul>
<p>Level up your Python skills with our expert-led courses:</p>
<ul>
<li><a href="https://realpython.com/courses/finding-perfect-python-code-editor/">Finding the Perfect Python Code Editor</a></li>
<li><a href="https://realpython.com/courses/python-debugging-pdb/">Debugging in Python With pdb</a></li>
<li><a href="https://realpython.com/courses/looping-with-python-enumerate/">Looping With Python enumerate()</a></li>
</ul> <p><a rel="payment" href="https://realpython.com/join">Support the podcast & join our community of Pythonistas</a></p>
About Julia
Julia Ferraioli calls herself an Open Source Archaeologist, focusing on sustainability, tooling, and research. Her background includes research in machine learning, robotics, HCI, and accessibility. Julia finds energy in developing creative demos, creating beautiful documents, and rainbow sprinkles. She’s also a fierce supporter of LaTeX, the Oxford comma, and small pull requests.
Links:
Open Source Stories: https://www.opensourcestories.org
My guest this week is John Chambers. John was the CEO of Cisco from 1995 to 2015 where he helped grow Cisco from $70 million to $40 billion in annual revenue. In this conversation we discuss the best business lesson he learned from long time GE CEO Jack Welch, his key lessons from acquiring over 180 companies with Cisco, pattern recognition and playbooks, capitalizing on market transitions enabled by new technologies, the value of team offsites, and a lot more. I was immediately drawn into John's magnetic personality and it's easy to see how he was so adept at running a 40,000 person company for 2 decades. I hope you enjoy this great conversation with John Chambers.
This episode is brought to you by Microsoft for Startups. Microsoft for Startups is a global program dedicated to helping “enterprise-ready” B2B startups successfully scale their companies. If you’re a founder running a B2B company targeting the enterprise, you should definitely check them out.
This episode is also sponsored by Vanta. Vanta has built software that makes it easier to both get and maintain your SOC 2 report, at a fraction of the normal cost. Founders Field Guide listeners can redeem a $1k off coupon at vanta.com/patrick.
For more episodes go to InvestorFieldGuide.com/podcast.
Sign up for the book club and new email newsletter called “Inside the Episode” at InvestorFieldGuide.com/bookclub.
Follow Patrick on Twitter at @patrick_oshag
Show Notes
(2:04) – (First question) – Why companies need a near death experience
(6:37) – The way his leadership changed between 1999 and 2003
(11:34) – His career before and leading to his time joining Cisco
(17:51) – What Cisco was like when he joined
(21:02) – Role that pattern recognition plays in his management
(24:16) – Lessons learned from the spate of acquisitions they took on under his tenure
(30:46) – Pricing deals and using Cisco’s scale to be successful
(33:09) – Lessons he learned in terms of distribution
(35:10) – What he learned from his relationship with Shimon Peres
(42:08) – His role in helping young entrepreneurs
(46:00) – Transformation on his team building trips to Alaska
(50:42) – Transitions in the world he is focused on right now
(52:542) – Kindest thing anyone has done for John
Learn More
For more episodes go to InvestorFieldGuide.com/podcast.
Sign up for the book club and new email newsletter called “Inside the Episode” at InvestorFieldGuide.com/bookclub.
Follow Patrick on Twitter at @patrick_oshag
<p>Have you wanted to get started with testing in Python? Maybe you feel a little nervous about diving in deeper than just confirming your code runs. What are the tools needed and what would be the next steps to level up your Python testing? This week on the show we have Anthony Shaw to discuss his article on this subject. Anthony is a member of the Real Python team and has written several articles for the site.</p>
<p>We discuss getting started with built-in Python features for testing and the advantages of a tool like pytest. Anthony talks about his plug-ins for pytest, and we touch on the next level of testing involving continuous integration.</p>
<p>Anthony recently finished a talk for PyCon 2020 Online, titled “Why is Python Slow?” He had the idea for the talk while he was working on his upcoming book about the CPython source code. </p>
<p>I also want to give an update on last weeks episode with Kyle Stratis, where we discussed Kyle being let go from his job due to the pandemic. Here’s some good news, Kyle will be joining a Boston startup called Vizit, as a senior data engineer. Congratulations Kyle!</p>
<div class="alert alert-primary" role="alert">
<p><strong>Course Spotlight:</strong> <a href="https://realpython.com/courses/python-print/">The Python <code>print()</code> Function: Go Beyond the Basics</a></p>
<p>This course will get you up to speed with using Python <code>print()</code> effectively. Prepare for a deep dive as you go through the sections. You may be surprised how much <code>print()</code> has to offer!</p>
</div>
<p>Topics:</p>
<ul>
<li>00:00:00 – Introduction</li>
<li>00:01:46 – PyCon 2020 Online Talk - Why is Python slow?</li>
<li>00:04:05 – CPython Internals Book</li>
<li>00:07:08 – Attending Conferences</li>
<li>00:09:01 – Getting Started with Testing in Python</li>
<li>00:12:32 – Unittest</li>
<li>00:17:16 – What does a tool like pytest add?</li>
<li>00:19:53 – pytest plugins</li>
<li>00:21:03 – Anthony’s pytest plugins</li>
<li>00:21:58 – What does coverage mean?</li>
<li>00:25:23 – Test runners </li>
<li>00:27:12 – Testing environments with Tox</li>
<li>00:30:50 – Real Python Video Course Spotlight</li>
<li>00:31:49 – More on continuous integration (CI)</li>
<li>00:37:21 – Recent changes to GitHub</li>
<li>00:38:21 – PSF to move issue tracker to GitHub</li>
<li>00:41:01 – DRY (Don’t Repeat Yourself)</li>
<li>00:43:46 – Benefits of linters and code formatting</li>
<li>00:48:00 – What is a little known part of Python?</li>
<li>00:52:16 – What are you excited about in the world of Python?</li>
<li>00:56:06 – What is something you thought you knew about Python, but were wrong about it?</li>
<li>00:57:27 – Goodbye and thanks</li>
</ul>
<p>Show links:</p>
<ul>
<li><a href="https://www.youtube.com/watch?v=I4nkgJdVZFA">Why is Python slow?: PyCon 2020 Online Talk</a></li>
<li><a href="https://realpython.com/cpython-source-code-guide/">Your Guide to the CPython Source Code: Real Python article</a></li>
<li><a href="https://talkpython.fm/episodes/show/265/why-is-python-slow">TalkPython Podcast Episode #265: Why is Python slow?</a></li>
<li><a href="https://realpython.com/python-testing/">Getting Started With Testing in Python: Real Python article </a></li>
<li><a href="https://docs.pytest.org/en/latest/">pytest: helps you write better programs</a></li>
<li><a href="https://github.com/tonybaloney/pytest-azurepipelines">pytest-azurepipelines: Plugin for pytest that makes it simple to work with Azure Pipelines</a></li>
<li><a href="https://realpython.com/pytest-python-testing/">Effective Python Testing With Pytest</a></li>
<li><a href="https://pypi.org/project/tox/">tox automation project: Command line driven CI frontend</a></li>
<li><a href="https://github.com/features/actions">GitHub Actions: Automate your workflow from idea to production</a></li>
<li><a href="https://realpython.com/python-continuous-integration/">Continuous Integration With Python: An Introduction: Real Python article</a></li>
<li><a href="https://www.youtube.com/watch?v=2R1HELARjUk">Brian K Okken - Multiply your Testing Effectiveness with Parameterized Testing: PyCon 2020 Online Talk</a></li>
<li><a href="https://pragprog.com/book/bopytest/python-testing-with-pytest">Python Testing with pytest: Brian Okken - The Pragmatic Bookshelf</a></li>
<li><a href="https://testandcode.com">Test & Code: Python Testing for Software Engineering: Podcast</a></li>
<li><a href="https://pyfound.blogspot.com/2020/05/pythons-migration-to-github-request-for.html">Python’s migration to GitHub</a></li>
<li><a href="https://realpython.com/python-refactoring/">Refactoring Python Applications for Simplicity: Real Python article</a></li>
<li><a href="https://black.readthedocs.io/en/stable/">Black: The uncompromising code formatter</a></li>
<li><a href="https://pypi.org/project/wily/">Wily: A command-line application for tracking, reporting on complexity of Python tests and applications</a></li>
<li><a href="https://www.python.org/dev/peps/pep-0554/">PEP 554 – Multiple Interpreters in the Stdlib</a></li>
<li><a href="https://blog.python.org">Python Insider: Python core development news and information</a></li>
</ul>
<p>Level up your Python skills with our expert-led courses:</p>
<ul>
<li><a href="https://realpython.com/courses/python-continuous-integration/">Continuous Integration With Python</a></li>
<li><a href="https://realpython.com/courses/test-driven-development-pytest/">Test-Driven Development With pytest</a></li>
<li><a href="https://realpython.com/courses/python-print/">The Python print() Function: Go Beyond the Basics</a></li>
</ul> <p><a rel="payment" href="https://realpython.com/join">Support the podcast & join our community of Pythonistas</a></p>
Rob Salvagno is VP of Corporate Development and Cisco Investments at Cisco, where he is responsible for leading all M&A efforts as well as managing Cisco's strategic venture capital which invests hundreds of millions of dollars annually. At Cisco, Rob led the $1.2 billion acquisition of Meraki, one of the most successful platform acquisitions in Cisco's history, and the $3.7 billion acquisition of AppDynamics, cementing Cisco's place in the business intelligence, analytics and IT operations market. Most recently, Rob engineered the $2.3 billion acquisition of Duo, the leading provider of unified access security and multi-factor authentication delivered through the cloud. Prior to the world of M&A, Rob was a technology investment banker at Donaldson, Lufkin & Jenrette.
In Today's Episode You Will Learn:
1.) How Rob made his way from investment banking to leading the M&A and venture activity for one of the world's largest tech players of the last decade?
2.) How do M&A teams like to get to know startups that they could invest in or acquire? How does Rob like to work with the venture ecosystem? How does Rob think on Paul Graham's comment of "do not talk to corp dev"? What are the nuances here? How does it differ for consumer vs enterprise?
3.) How does Rob define true success when it comes to M&A evaluation? Should corp dev be strategy first or transaction first? What have been Rob's biggest lessons on successful integration? Where do so many go wrong with integration post M&A? What questions can be asked ahead of time to know if integration and culture will be a fit?
4.) How does Rob reflect on his own price sensitivity today? How does Rob feel about the multiples enterprise companies are currently trading at? What have Rob's most successful acquisitions taught him about price and price sensitivity? How does Rob deal with the inherent conflict of investing and also acquiring companies? How does he communicate that to the companies he invests in?
5.) What does the acquisition-decision making process look like at Cisco? How does it differ on a deal by deal basis? What do Cisco do to allow them to move so much faster than any other M&A teams? What have been Rob's lessons on the importance of speed in winning the best transactions?
Items Mentioned In Today's Show:
Rob's Fave Book: The Poisonwood Bible
Rob's Most Recent Acquisitions: CloudCherry, Voicea
As always you can follow Harry, The Twenty Minute VC and Rob on Twitter here!
Likewise, you can follow Harry on Instagram here for mojito madness and all things 20VC.
Topics covered in this episode:
poetry
Anthony pylama and radon
Nina Tools for teaching Python
Dan My favorite tool of 2018: “Black” code formatter by Łukasz Langa
Brett A Web without JavaScript : Russell Keith-Magee at PyCon AU
Async WebDriver implementation for asyncio and asyncio-compatible frameworks
Extras
Joke
See the full show notes for this episode on the website at pythonbytes.fm/100
John Chambers, the former chairman and CEO of Cisco, talks with Recode's Kara Swisher about the future of startups and his book, "Connecting the Dots: Leadership Lessons in a Startup World." In this episode: (01:43) Chambers's 26 years at Cisco and 180 acquisitions; (05:28) Cisco's new leadership and his transition out; (07:57) "We think we’re the leader of innovation in America, we no longer are"; (17:58) The Republican party and uniting the country; (20:40) What the government can do to help startups; (26:18) Damage caused by tech; (28:48) China and India; (33:34) Why Chambers wrote the book; (39:25) Key leadership lessons: Vision, strategy and culture; (44:16) Creating jobs and common problems; (51:01) Entrepreneurship around the U.S. and internationally; (52:57) Immigration and diversity
Learn more about your ad choices. Visit podcastchoices.com/adchoices
Jeetu Patel is Senior Vice President of Platform and Chief Strategy Officer of Box where he leads the Box Platform organization, driving the strategy of the platform business and developer relations. He also oversees the corporate strategy and development organization for Box. Before joining the company, Patel was General Manager and Chief Executive of EMC's Syncplicity business unit. Prior to EMC, Patel was president of Doculabs, a research and advisory firm focused on collaboration and content management across a range of industries.
In Today's Episode You Will Learn:
How Jeetu made his way into the world of SaaS and came to be one of the key executives at Box?
What are Jeetu's 3 tips to startup founders looking to build high performing teams? Why does Jeetu believe that team sizes must always remain small? What are the inflection points in team size when dynamics change?
What does Jeetu argue that founders must pursue really hard problems? What are the benefits of this when hiring new people to the team? How does Jeetu balance between visionary hard problems and unrealistic?
What does Jeetu mean when he says, 'do things that do not scale so you can do things that sustainably scale? What are some examples of how this has been done effectively? Where do most startups go wrong in scaling sustainably?
60 Second SaaStr
What does Jeetu believe that most around him do not?
Fave SaaS reading material?
Why businesses will find the rules of the future very different to the rules of the past?
If you would like to find out more about the show and the guests presented, you can follow us on Twitter here:
Jason Lemkin
Harry Stebbings
SaaStr
Jeetu Patel