Podcasts about MongoDB

Python typing got fast enough to feel invisible. Pyrefly is a new, open source type checker and IDE language server from Meta, written in Rust, with a focus on instant feedback and real-world DX. Today, we will dig into what it is, why it exists, and how it plays with the rest of the typing ecosystem. We have Abby Mitchell, Danny Yang, and Kyle Into from Pyrefly here to dive into the project. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Abby Mitchell: linkedin.com Danny Yang: linkedin.com Kyle Into: linkedin.com Pyrefly: pyrefly.org Pyrefly Documentation: pyrefly.org Pyrefly Installation Guide: pyrefly.org Pyrefly IDE Guide: pyrefly.org Pyrefly GitHub Repository: github.com Pyrefly VS Code Extension: marketplace.visualstudio.com Introducing Pyrefly: A New Type Checker and IDE Experience for Python: engineering.fb.com Pyrefly on PyPI: pypi.org InfoQ Coverage: Meta Pyrefly Python Typechecker: infoq.com Pyrefly Discord Invite: discord.gg Python Typing Conformance (GitHub): github.com Typing Conformance Leaderboard (HTML Preview): htmlpreview.github.io Watch this episode on YouTube: youtube.com Episode #523 deep-dive: talkpython.fm/523 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Imagine an engineer who's gone from writing code to building a venture-backed startup—now creating AI-powered tools tailored for fashion brands in New York. That's Harish Chandramowli, Co-Founder of Flaire. His journey is a compelling example of the kind of leadership, innovation, and resilience we highlight on the Breakfast Leadership Show. With a twelve-year engineering career at organizations like MongoDB, Bloomberg, and Johns Hopkins, Harish made the leap into entrepreneurship by co-founding Flaire—an ERP platform that fuses artificial intelligence with user-centered design for retail. What makes Harish's story stand out is his ability to blend deep technical expertise with the gritty, hands-on realities of scaling a business. Whether he's designing smarter code-review workflows (like Greptile, which dramatically reduces dev feedback cycles) or jumping into client sales conversations, Harish brings a unique perspective. He's learned firsthand how to build high-performing remote teams rooted in trust, and how small, strategic process bets can drive sustainable growth. LinkedIn: https://www.linkedin.com/in/scharish/ Website: https://Flairesoftware.com This episode's partner is MRPeasy.  Link to sign up:  https://try.mrpeasy.com/rzhgcr9jcov5   The AI-powered MRP software for small manufacturers Ideal for companies with 10 - 200 employees MRPeasy is a seriously powerful yet easy-to-use manufacturing software. It gives you everything you need to manage your manufacturing and distribution.  

Send us a textThis week, we're rewinding one of our most talked-about episodes! Richmond Alake, Developer Advocate at MongoDB, joins us to explore how databases power the future of AI. From RAG best practices to the truth behind AGI hype, Richmond breaks down what it takes to build systems that scale — and think.Show Notes02:05 Meet Rich Alake 03:57 A Developer Advocate at MongoDB 05:57 Passions and Fate! 08:52 AI Hype 13:14 Oh No… AGI Again 17:30 What Makes an AI Database? 20:42 Use Cases 25:41 RAG Best Practices 27:40 The Role of Databases 30:05 Why MongoDB Does It Better 32:43 What's Next 36:13 Advice on Continuous Learning 38:44 Where to Find RichConnect with Richmond:

Send us a textThis week, we're rewinding one of our most talked-about episodes! Richmond Alake, Developer Advocate at MongoDB, joins us to explore how databases power the future of AI. From RAG best practices to the truth behind AGI hype, Richmond breaks down what it takes to build systems that scale — and think.Show Notes02:05 Meet Rich Alake 03:57 A Developer Advocate at MongoDB 05:57 Passions and Fate! 08:52 AI Hype 13:14 Oh No… AGI Again 17:30 What Makes an AI Database? 20:42 Use Cases 25:41 RAG Best Practices 27:40 The Role of Databases 30:05 Why MongoDB Does It Better 32:43 What's Next 36:13 Advice on Continuous Learning 38:44 Where to Find RichConnect with Richmond:

Today we're turning tiny tips into big wins. Khuyen Tran, creator of CodeCut.ai, has shipped hundreds of bite-size Python and data science snippets across four years. We dig into open-source tools you can use right now, cleaner workflows, and why notebooks and scripts don't have to be enemies. If you want faster insights with fewer yak-shaves, this one's packed with takeaways you can apply before lunch. Let's get into it. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Khuyen Tran (LinkedIn): linkedin.com Khuyen Tran (GitHub): github.com CodeCut: codecut.ai Production-ready Data Science Book (discount code TalkPython): codecut.ai Why UV Might Be All You Need: codecut.ai How to Structure a Data Science Project for Readability and Transparency: codecut.ai Stop Hard-coding: Use Configuration Files Instead: codecut.ai Simplify Your Python Logging with Loguru: codecut.ai Git for Data Scientists: Learn Git Through Practical Examples: codecut.ai Marimo (A Modern Notebook for Reproducible Data Science): codecut.ai Text Similarity & Fuzzy Matching Guide: codecut.ai Loguru (Python logging made simple): github.com Hydra: hydra.cc Marimo: marimo.io Quarto: quarto.org Show Your Work! Book: austinkleon.com Watch this episode on YouTube: youtube.com Episode #522 deep-dive: talkpython.fm/522 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Experienced CISOs from MongoDB and Gusto reveal proven frameworks for translating complex cybersecurity metrics into board-friendly presentations that drive decision-making.Topics Include:Security leaders discuss challenges of presenting technical cybersecurity topics to boardsMongoDB CISO presents three times in six months, Gusto director five timesThree-angle metrics framework: environmental threats, prevention quality, and detection/response speed capabilitiesBoard members switch contexts frequently, requiring extensive education and simplified heat mapsRepeatable presentation models help board members follow consistent data across meetingsAudit committees get different depth than general board updates on programsNew technologies like AI require educating boards on risks versus opportunitiesFoundational security principles like zero trust remain constant regardless of technologySecurity buzzwords need translation appendices since board members forget technical definitionsFinancial services background helps translate cyber risks into dollar amounts boards understandThird-party penetration testing provides independent validation but requires vendor rotation strategiesLimited 30-minute board time means trusting security leaders' vendor diligence decisionsFirst-time CISOs should educate on threat landscape then tailor strategy to companyBalance discussing shiny new technologies with essential foundational security blocking and tacklingAI implementation spans customer features, infrastructure security, and augmenting security capabilities internallyParticipants:Sean Josephson - Sr. Director of Information Security, GustoJulien Soriano – Sr. Vice President, CISO, MongoDBGee Rittenhouse - Vice President, Security Services, Amazon Web ServicesFurther Links:Gusto: Website – LinkedInMongoDB: Website – LinkedIn – AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Harish Chandramowli grew up in a small town in India. The goal was simple early on - study well, go to university, and get a job. After undergrad, he realized he can do so much more, eventually coming stateside to get his masters, and meet a ton of really smart people over the last 10 years. Outside of tech, he is a broadway show fanatic, seeing 1-2 on a regular basis. He also follows Manchester United, which can be difficult watching the lose on the regular.Harish used to work for MongoDB, and spent some time on call and in the weeds. At that time, he realized how much data is used by a business. When he eventually supported the fashion industry, specifically the back office, he wanted to build a solution to make the lives of those back office individuals as easy as possible.This is the creation story of Flaire.SponsorsFull ScalePaddle.comSema SoftwarePropelAuthPostmanMeilisearchLinkshttps://www.flairesoftware.com/https://www.linkedin.com/in/scharish/Support this podcast at — https://redcircle.com/code-story-insights-from-startup-tech-leaders/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Jake and Michael discuss all the latest Laravel releases, tutorials, and happenings in the community.Show linksA New Local Error Page in Laravel 12.29 Infinite Scroll in Inertia v2.2 Laravel MCP Beta is Released Filament v4.1 is here! PrettyPHP is an opinionated code formatter for PHP Meet LaraUtilX: A Utility Toolkit Every Laravel Developer Needs Powerful Debugging for PHP & Laravel with LaraDumps Laravel Starter Kit by Nuno Maduro A Laravel Package to Integrate with Google Gemini Build Terminal UIs in PHP With ANSI Kit TutorialsDebugging and Logging in Laravel ApplicationsIntroduction to MongoDB & Laravel-MongoDB SetupThe Hidden Cost of MySQL Defaults in Laravel AppsLivewire Session Properties for Persistent Component StateLivewire wire:click.prevent for Form HandlingTesting Your Reporting System with Laravel Factories and AssertionsProfiling Laravel: How to Find Hidden Performance KillersLaravel Collection Pluck Method Gains Closure Transformation PowerLaravel Configuration Arrays Made Simpler with Config::collection()Laravel Custom Validation Rules for Enhanced Data Integrity

In this episode, host Shannon Peavey welcomes the one and only Elena Verna. But wait, it's not the illustrious, highly sought-after growth expert herself, but her AI agent, powered by SuperMe. “She” shares deep knowledge from her expansive body of work in growth from Miro to Amplitude to Loveable and shares why company stage matters when thinking through a growth strategy.Chapters:1:50: Elena defines PLG3:45  Skills for aspiring growth PMs 4:20  Choosing the right success metrics 5:58  Why company stage matters to growth strategy7:10  How companies can get started with growth8:12  Stories from SurveyMonkey, Miro and Amplitude10:15 Hitting the ground running at Lovable11:20 Refining the ICP13:00 Collaborating cross-team14:00 Personal reflectionsWhere to find Elena Verna:LinkedIn: https://www.linkedin.com/in/elenaverna/Elena's SuperMe AI Agent: https://www.superme.ai/elenaResources:Elena Verna's Substack: https://www.elenaverna.com/SuperMe https://www.superme.ai/Lovable https://lovable.dev/Miro https://miro.com/SurveyMonkey https://www.surveymonkey.com/Amplitude https://amplitude.com/Sanity.io https://www.sanity.io/MongoDB https://www.mongodb.com/

English is now an API. Our apps read untrusted text; they follow instructions hidden in plain sight, and sometimes they turn that text into action. If you connect a model to tools or let it read documents from the wild, you have created a brand new attack surface. In this episode, we will make that concrete. We will talk about the attacks teams are seeing in 2025, the defenses that actually work, and how to test those defenses the same way we test code. Our guides are Tori Westerhoff and Roman Lutz from Microsoft. They help lead AI red teaming and build PyRIT, a Python framework the Microsoft AI Red Team uses to pressure test real products. By the end of this hour you will know where the biggest risks live, what you can ship this quarter to reduce them, and how PyRIT can turn security from a one time audit into an everyday engineering practice. Episode sponsors Sentry AI Monitoring, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Tori Westerhoff: linkedin.com Roman Lutz: linkedin.com PyRIT: aka.ms/pyrit Microsoft AI Red Team page: learn.microsoft.com 2025 Top 10 Risk & Mitigations for LLMs and Gen AI Apps: genai.owasp.org AI Red Teaming Agent: learn.microsoft.com 3 takeaways from red teaming 100 generative AI products: microsoft.com MIT report: 95% of generative AI pilots at companies are failing: fortune.com A couple of "Little Bobby AI" cartoons Give me candy: talkpython.fm Tell me a joke: talkpython.fm Watch this episode on YouTube: youtube.com Episode #521 deep-dive: talkpython.fm/521 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

An airhacks.fm conversation with Ronald Dehuysser (@rdehuyss) about: JobRunner evolution from open source to processing 1 billion jobs daily, carbon-aware job processing using European energy grid data ( ENTSO-E ) for scheduling jobs during renewable energy peaks, correlation between CO2 emissions and energy prices for cost optimization, JobRunner Pro vs Open Source features including workflows and multi-tenancy support, bytecode analysis using ASM for lambda serialization, JSON serialization for job state persistence, support for relational databases and MongoDB with potential S3 and DynamoDB integration, distributed processing with master node coordination using heartbeat mechanism, scale-to-zero architecture possibilities using AWS EventBridge Scheduler, Java performance advantages showing 35x faster than python in benchmarks, cloud migration patterns from on-premise to serverless architectures, criticism of kubernetes complexity and lift-and-shift cloud migrations, cost-driven architecture approach using AWS Lambda and S3, quarkus as fastest Java runtime for cloud deployments, infrastructure as code using AWS CDK with Java, potential WebAssembly compilation for Edge Computing, automatic retry mechanisms with exponential backoff, dashboard and monitoring capabilities, medical industry use case with critical cancer result processing, professional liability insurance for software errors, comparison with executor service for non-critical tasks, scheduled and recurring job support, carbon footprint reduction through intelligent scheduling, spot instance integration for cost optimization, simplified developer experience with single JAR deployment, automatic table creation and data source detection in Quarkus, backwards compatibility requirements for distributed nodes, future serverless edition possibilities Ronald Dehuysser on twitter: @rdehuyss

"Escolha uma área e fique ali. É o tempo que vai dar espaço para a multidisciplinariedade. Tente criar algo com aquilo" - Felipe Nunes No sexto episódio do Hipsters.Talks, PAULO SILVEIRA , CVO do Grupo Alun, conversa com FELIPE NUNES, senior sales engineer da NEO4J, sobre bancos de dados de grafos e como eles estão revolucionando a forma de trabalhar com dados. Uma conversa sobre como os grafos democratizam o acesso aos dados e potencializam a inteligência artificial. Prepare-se para um episódio cheio de conhecimento e inspiração! Espero que aproveitem :) Sinta-se à vontade para compartilhar suas perguntas e comentários. Vamos adorar conversar com vocês!

From Security Systems to Scaling Startups: Meet the Engineer-Turned-CEO Powering Fashion's Digital Backbone This week, we interview Harish Chandramowli, the brilliant mind behind Flaire a lightweight, intuitive ERP system that's quietly transforming how fashion brands manage inventory, purchasing, and operations. Before stepping into the world of fashion tech, Harish built his reputation in elite engineering circles leading cloud infrastructure teams at MongoDB, securing sensitive systems at Bloomberg, and co-founding India's first P2P bike-sharing platform, Ridengine. With over a decade of technical leadership under his belt, he's now steering a venture-backed startup in New York that bridges deep tech with business empathy.Flaire isn't just software, it's a founder-led, customer-first movement that's reshaping how emerging brands scale with clarity and control. And Harish isn't your typical CEO. He codes, jumps on sales calls, rolls out productivity tools like Greptile, and builds remote-first teams with care and culture in mind.In this interview, we go beyond the product. We unpack his immigrant journey, his childhood curiosity, and how he found the courage to shift from code to customer balancing resilience, reinvention, and the business of listening.

A couple years ago, Charlie Marsh lit a fire under Python tooling with Ruff and then uv. Today he's back with something on the other side of that coin: pyx. Pyx isn't a PyPI replacement. Think server, not just index. It mirrors PyPI, plays fine with pip or uv, and aims to make installs fast and predictable by letting a smart client talk to a smart server. When the client and server understand each other, you get new fast paths, fewer edge cases, and the kind of reliability teams beg for. If Python packaging has felt like friction, this conversation is traction. Let's get into it. Episode sponsors Six Feet Up Talk Python Courses Links from the show Charlie Marsh on Twitter: @charliermarsh Charlie Marsh on Mastodon: @charliermarsh Astral Homepage: astral.sh Pyx Project: astral.sh Introducing Pyx Blog Post: astral.sh uv Package on GitHub: github.com UV Star History Chart: star-history.com Watch this episode on YouTube: youtube.com Episode #520 deep-dive: talkpython.fm/520 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

In this short segment of the Revenue Builders Podcast, John McMahon and John Kaplan are joined by Meghan Gill, who spent 17 years scaling MongoDB. Meghan shares her approach to building credibility in sales operations, enabling leaders to think with a business mindset, and creating a management operating rhythm that empowers organizations to scale effectively. From fixing broken reporting to establishing trust and building a cadence that fosters championship-level performance, this conversation is a masterclass in how RevOps drives long-term success.KEY TAKEAWAYS[00:01:00] Sales leaders often excel at recruiting and closing deals but must learn how to leverage information effectively.[00:02:12] Credibility begins with fixing the basics—clean reporting builds trust and opens the door to deeper strategic input.[00:03:00] A strong cadence inside an organization enables consistency and peak performance, much like a championship sports team.[00:04:21] Multiple cadences exist at different levels—frontline managers focus on recruiting and pipeline, while leadership focuses on forecasting and long-term planning.[00:05:52] Sales operations can provide insights that validate or challenge a CRO's instincts, helping identify hidden issues.[00:07:08] Weekly metric reviews create accountability and ensure readiness, cascading discipline throughout the sales organization.QUOTES[00:00:48] “The greatest sales ops organizations aren't internal affairs—they're like coaches, helping sales leaders think with a business intent.”00:02:29] “Don't come in too hot. Solve the first basic problems, earn trust, and then earn the right to be at the table.”[00:03:35] “The cadence wasn't punitive—it became enabling. It was something you sought after, like being part of a championship team.”[00:05:22] “By the fifth day of the first month, forecasts roll up. By the 10th, something else happens—there's a time element to cadence that drives discipline.”[00:07:29] “It started with me. I had to understand the metrics and be prepared, which set a standard that cascaded throughout the organization.”Listen to the full conversation through the link below.https://revenue-builders.simplecast.com/episodes/scaling-sales-operations-with-meghan-gillEnjoying the podcast? Sign up to receive new episodes straight to your inbox:https://hubs.li/Q02R10xN0Check out John McMahon's book here:Amazon Link: https://a.co/d/1K7DDC4Check out Force Management's Ascender platform here: https://my.ascender.co/Ascender/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Today on Talk Python: What really happens when your data work outgrows your laptop. Matthew Rocklin, creator of Dask and cofounder of Coiled, and Nat Tabris a staff software engineer at Coiled join me to unpack the messy truth of cloud-scale Python. During the episode we actually spin up a 1,000 core cluster from a notebook, twice! We also discuss picking between pandas and Polars, when GPUs help, and how to avoid surprise bills. Real lessons, real tradeoffs, shared by people who have built this stuff. Stick around. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Talk Python Courses Links from the show Matthew Rocklin: @mrocklin Nat Tabris: tabris.us Dask: dask.org Coiled: coiled.io Watch this episode on YouTube: youtube.com Episode #519 deep-dive: talkpython.fm/519 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

In this episode of HTML All The Things, Mike sits down with Jesse Hall, Staff Developer Advocate at MongoDB and creator of the popular codeSTACKr platform. Jesse shares his journey from working at Geek Squad to becoming a self-taught developer, educator, and now an advocate at one of the biggest players in the database space. They discuss the principles that make technical concepts “click” for beginners, how to help teams move from relational-first thinking to designing flexible MongoDB schemas, and the pitfalls to avoid when working with document databases. The conversation also dives into MongoDB's role in the AI landscape, including Jesse's “AI in Two Lines” approach and what it really takes to go from toy chatbots to robust agentic systems. Show Notes: https://www.htmlallthethings.com/podcast/from-geek-squad-to-mongodb-advocate-w-jesse-hall Powered by CodeRabbit - AI Code Reviews: https://coderabbit.link/htmlallthethings Use our Scrimba affiliate link (https://scrimba.com/?via=htmlallthethings) for a 20% discount!! Full details in show notes.

How confident are you when your test suite goes green? If you're honest, probably not 100% confident - because most bugs come from scenarios we never thought to test. Traditional testing only catches the problems we anticipate, but the 3am pager alerts? Those come from the unexpected interactions, timing issues, and edge cases we never imagined.In this episode, Will Wilson from Antithesis takes us deep into the world of autonomous testing. They've built a deterministic hypervisor that can simulate entire distributed systems - complete with fake AWS services - and intelligently explore millions of possible states to find bugs before production. Think property-based testing, but for your entire infrastructure stack. The approach is so thorough they've even used it to find glitches in Super Mario Brothers (seriously).We explore how deterministic simulation works at the hypervisor level, why traditional integration tests are fundamentally limited, and how you can write maintainable tests that actually find the bugs that matter. If you've ever wished you could test "what happens when everything that can go wrong does go wrong," this conversation shows you how that's finally becoming possible.---Support Developer Voices on Patreon: https://patreon.com/DeveloperVoicesSupport Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/joinAntithesis: https://antithesis.com/Antithesis testing with Super Mario: https://antithesis.com/blog/sdtalk/...and with Metroid: https://antithesis.com/blog/2025/metroid/MongoDB: https://www.mongodb.com/etcd (Linux Foundation): https://etcd.io/Facebook Hermit: https://github.com/facebookexperimental/hermitRR (Record-Replay Debugger): https://rr-project.org/T-SAN (Thread Sanitizer): https://clang.llvm.org/docs/ThreadSanitizer.htmlToby Bell's Strange Loop Talk on JPL Testing: https://www.youtube.com/results?search_query=toby+bell+strange+loop+jplAndy Weir - Project Hail Mary: https://www.goodreads.com/book/show/54493401-project-hail-maryAndy Weir - The Martian: https://www.goodreads.com/book/show/18007564-the-martianAntithesis Blog (Nintendo Games Testing): https://antithesis.com/blog/Kris on Bluesky: https://bsky.app/profile/krisajenkins.bsky.socialKris on Mastodon: http://mastodon.social/@krisajenkinsKris on LinkedIn: https://www.linkedin.com/in/krisjenkins/

In this episode of the East Coast Elite series, we sit down with Liam Mulcahy, Operating Partner at Kleiner Perkins. Having worked with over 100 startups, from first-ever sales rep to operating partner, Liam shares his unfiltered playbook for success in the chaotic world of early-stage companies. We cover how to identify the right opportunities, what a founder-led sales motion looks like, the red flags to watch for in an interview, and the mindset needed to thrive in a high-risk, high-reward environment. Liam also shares his famous cardboard cutout story that landed him a job at MongoDB, a company he helped take public.

In this episode we are joined by Kenneth Auchenberg, Partner at AlleyCorp — one of New York's most prolific early-stage funds known for incubating companies like MongoDB, Business Insider, and Radical AI.Kenneth's journey from coding at 16 in Copenhagen to shaping global developer ecosystems at Stripe and Microsoft gives him a unique lens into the next generation of software businesses — and the rise of AI agents.

In this episode, Will Wilson, CEO and co-founder of Antithesis, explores Deterministic Simulation Testing (DST) with host Sriram Panyam. Wilson was part of the pioneering team at FoundationDB that developed this revolutionary testing approach, which was later acquired by Apple in 2015. After seeing that even sophisticated organizations lacked robust testing for distributed systems, Wilson co-founded Antithesis in 2018 to make DST commercially available. Deterministic simulation testing runs software in a fully controlled, simulated environment in which all sources of non-determinism are eliminated or controlled. Unlike traditional testing or chaos engineering, DST operates in a separate environment from production, allowing for aggressive fault injection without risk to live systems. The key breakthrough is perfect reproducibility -- any bug found can be recreated exactly using the same random seed. Antithesis built "The Determinator," a custom deterministic hypervisor that simulates entire software stacks including virtual hardware, networking, and time. The system can compress years of stress testing into shorter timeframes by running simulations faster than wall-clock time. All external interfaces that could introduce non-determinism (network calls, disk I/O, system time) are mocked or controlled by the simulator. The approach has proven effective with major organizations including MongoDB, Palantir, and Ethereum. For Ethereum's critical "Merge" upgrade in 2022, Antithesis found and helped fix several serious bugs that could have been catastrophic for the live network. The platform typically finds bugs that traditional testing methods miss entirely -- such as those arising from rare race conditions, complex timing issues, and unexpected system interactions. This episode is sponsored by Monday Dev

Scalestack is revolutionizing go-to-market operations through intelligent automation, helping enterprise revenue teams eliminate what CEO Elio Narciso calls the "manual work tax" - the 72% of time sales reps spend on tedious data tasks instead of engaging with customers. With $3.1 million in funding and enterprise customers including MongoDB, Redis, and Astronomer, Scalestack has built an agentic orchestration platform that transforms how large organizations manage their revenue data. In this conversation, Narciso shares how his team discovered the massive ROI hidden in back-office automation and why the future belongs to companies that can seamlessly blend human strategy with machine execution. Topics Discussed: The concept of "manual work tax" and its impact on sales productivity  Why 95% of AI investments in enterprises are failing to produce results  Scalestack's evolution from automation platform to agentic workflow orchestration  The company's enterprise-first approach and deployment strategy with large customers  How Scalestack landed MongoDB as an early customer through targeted outbound  The role of podcasting as an ABM strategy for enterprise sales  Scalestack's vision to replace traditional CRMs with intelligent systems of action GTM Lessons For B2B Founders: Target the back-office before the front-office: While many AI companies rush to automate customer-facing roles like SDRs, Narciso emphasizes that the real ROI lies in back-office automation. He cites an MIT study showing that 95% of AI investments fail when focused on last-mile customer interactions, while back-office process automation delivers measurable results. B2B founders should prioritize automating the tedious work that doesn't directly touch customers but enables better customer engagement. Enterprise customers require co-creation, not just deployment: Scalestack's success with MongoDB, Redis, and other large customers came through what Narciso calls "deployment engineers" - essentially building custom solutions collaboratively. He draws inspiration from Palantir's model of developing technology alongside customers. This approach requires significant upfront investment but creates defensible technology that can be productized for the broader market. B2B founders targeting enterprise should be prepared to invest in customer success resources that can handle complex, bespoke implementations. Use customer language to refine your messaging: Narciso completely redid Scalestack's website based on language extracted from hundreds of customer calls and podcast interviews. He emphasizes that "customers always have the best words" because they've lived the pain most deeply. Rather than relying on internal assumptions about positioning, B2B founders should systematically capture and analyze how customers describe their problems and desired outcomes. Cold email still works with enterprise buyers when done strategically: Scalestack's first major customer, MongoDB, came from a cold email to their SVP of Sales Ops. The key was targeting someone (employee #8 at MongoDB) who had an entrepreneurial mindset and curiosity about learning from vendors. Narciso's insight: enterprise operators often want to learn from startups tackling similar problems, whether to buy the solution or implement it internally. B2B founders should research target prospects' backgrounds and approach those with startup experience or operational curiosity. Podcasting as ABM for enterprise sales: Narciso uses his "Revenue Engine Masters" podcast strategically as an account-based marketing tool, targeting specific people at target companies rather than focusing on broad reach. After recording nearly 20 episodes, he's seeing inbound interest and using the content to extract messaging insights. The podcast also strengthens relationships with prospects and customers who participate. B2B founders should consider podcasting not as a mass-market strategy but as a high-touch relationship-building tool for their ideal customer profile.   //   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 

Twenty years after a scrappy newsroom team hacked together a framework to ship stories fast, Django remains the Python web framework that ships real apps, responsibly. In this anniversary roundtable with its creators and long-time stewards: Simon Willison, Adrian Holovaty, Will Vincent, Jeff Triplet, and Thibaud Colas, we trace the path from the Lawrence Journal-World to 1.0, DjangoCon, and the DSF; unpack how a BSD license and a culture of docs, tests, and mentorship grew a global community; and revisit lessons from deployments like Instagram. We talk modern Django too: ASGI and async, HTMX-friendly patterns, building APIs with DRF and Django Ninja, and how Django pairs with React and serverless without losing its batteries-included soul. You'll hear about Django Girls, Djangonauts, and the Django Fellowship that keep momentum going, plus where Django fits in today's AI stacks. Finally, we look ahead at the next decade of speed, security, and sustainability. Episode sponsors Talk Python Courses Python in Production Links from the show Guests Simon Willison: simonwillison.net Adrian Holovaty: holovaty.com Will Vincent: wsvincent.com Jeff Triplet: jefftriplett.com Thibaud Colas: thib.me Show Links Django's 20th Birthday Reflections (Simon Willison): simonwillison.net Happy 20th Birthday, Django! (Django Weblog): djangoproject.com Django 2024 Annual Impact Report: djangoproject.com Welcome Our New Fellow: Jacob Tyler Walls: djangoproject.com Soundslice Music Learning Platform: soundslice.com Djangonaut Space Mentorship for Django Contributors: djangonaut.space Wagtail CMS for Django: wagtail.org Django REST Framework: django-rest-framework.org Django Ninja API Framework for Django: django-ninja.dev Lawrence Journal-World: ljworld.com Watch this episode on YouTube: youtube.com Episode #518 deep-dive: talkpython.fm/518 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

There is no resistance above current level for Nasdaq and with good support below the risk/reward still seems very attractive as Nasdaq is heading for 25.000 points. In this week's podcast I look a bit into what may change the Nasdaq trajectory and why Rocket Lab [ RKLB ] may climb 1000% over next 16 months. Last week I pointed at MongoDB as an interesting stock and it has not disappointed moving up 50% over the week. In this week's podcast I highlight another stock which I think has strong future potential based on the same arguments as I had for MongoDB.The $1000 challenge keep setting new records as it now sits at $4.584. The bet into NIO is really starting to pay off and at the end of the podcast you will get this weeks insights and decisions for the $1000 challenge.Tune in!

In this episode of the Revenue Builders Podcast, hosts John McMahon and John Kaplan are joined by Meghan Gill to discuss the pivotal role of sales operations in scaling a company from $100 million to a multi-billion-dollar enterprise. Drawing on her 15 years at MongoDB, Megan shares valuable insights on evolving RevOps functions, the complexities of comp planning, the integration of AI in sales, and the importance of maintaining a robust management operating rhythm. The conversation covers a breadth of topics, including the transition to a consumption-based model, the challenges and strategies in aligning sales and client success teams, and best practices for selecting and consolidating sales tools. Megan emphasizes the necessity of detailed planning and communication, as well as the need to balance protecting the company with serving the sales organization effectively.ADDITIONAL RESOURCESConnect with Meghan Gill:https://www.linkedin.com/in/meghanpgill/Download the CRO Strategy Checklist: https://hubs.li/Q03f8LmX0Watch Force Management's Panel Discussion on AI in Sales Leadership: https://hubs.ly/Q03rlW4Z0Enjoying the podcast? Sign up to receive new episodes straight to your inbox: https://hubs.li/Q02R10xN0HERE ARE SOME KEY SECTIONS TO CHECK OUT[00:02:41] Evolution of Sales Operations[00:03:58] Field Operations and Territory Planning[00:06:45] Rev Ops vs. Sales Ops[00:08:20] Effective Territory Management[00:18:08] Metrics and KPIs in Sales Ops[00:22:55] Building a Successful Sales Ops Team[00:33:54] Deep Dive into Sales Ops Challenges[00:34:22] Diagnosing Sales Problems[00:35:05] Trust but Verify: Ensuring Data Integrity[00:37:36] Balancing Protection and Service in Leadership[00:39:51] Choosing the Right Sales Tools[00:43:50] The Role of AI in Sales[00:51:21] Compensation Plans and Their Complexities[01:01:25] Lessons from Scaling MongoDBHIGHLIGHT QUOTES[00:26:06] "The hardest part, to be honest, is getting the data right, because nobody has a perfect CRM with perfectly scrubbed data."[00:35:37] "Every analysis that I've done throughout my years running sales ops is very counterintuitive. It's like the fewer accounts you have, the more productive you are because you can really focus and narrow in."[01:32:06] "People with AI experience and leverage on how to do these roles are going to replace people that don't do that. And I see that happening really, really fast."[01:41:50] "Keep it simple. You want to have one, maybe two elements in the comp plan... Any more than that, they're not gonna know where to focus."

Unser Partner Scalable Capital ist der einzige Broker, den du brauchst. Inklusive Trading-Flatrate, Zinsen und Portfolio-Analysen. Alle weiteren Infos gibt's hier: scalable.capital/oaws.Aktien + Whatsapp = Hier anmelden. Lieber als Newsletter? Geht auch.Das Buch zum Podcast? Jetzt lesen.Der Kalender zum Podcast? Jetzt kaufen. Porsche will neuen Chef. Rheinmetall hat neue Fabrik und vielleicht bald neue Tochter. Canada Goose mit neuem Eigentümer? MondoDB, Snowflake und Kohl's überzeugen mit Zahlen. CrowdStrike nicht so. Cambricon wächst über 4.000%. Schadet das NVIDIA? Geholfen hat es nicht. Zumindest nicht dabei, die Erwartungen zu pulverisieren. Trump Media (WKN: A3CYXD) schickt Cronos zum Mond. Metaplanet will mehr Geld. Immer mehr Biotechs wollen Krypto-Geld. Und in Venezuela scheint Krypto zu helfen. Diesen Podcast vom 28.08.2025, 3:00 Uhr stellt dir die Podstars GmbH (Noah Leidinger) zur Verfügung.

How the Fed's about-face on interest rates will impact the market. Plus, avoid this common mistake when shorting stocks… The AT&T (T)/EchoStar (SATS) deal… Has Eli Lilly (LLY) bottomed? … And Nvidia's (NVDA) earnings. In this episode: MongoDB's earnings are a warning to other software companies [3:43] Rate cuts are coming: What it means for the market [9:03] Shorting stocks? Avoid this common mistake [16:48] The AT&T/EchoStar spectrum deal: Are the stocks buys? [22:44] Has Eli Lilly finally bottomed? [31:12] Nvidia's earnings report: Key things to watch [38:47] I've changed my tune on AMD [42:27] The latest details on the Curzio One Wealth Forum! [52:14] Editor's note: November 9-11, we're hosting our first-ever Curzio One Wealth Forum—an intimate, two-day event exclusively for Curzio One members—at the legendary Pier Sixty-Six in Fort Lauderdale, Florida.  --Curzio One members can get the details and register here: https://secure.curzioresearch.com/checkout/conference-tickets.php/?utm_source=Libsyn --Not a Curzio One member? Learn more about our most elite membership—and add your name to the waitlist—here: https://www.curzioresearch.com/curzio-one-wait-list/?utm_source=Libsyn Did you like this episode? Get more Wall Street Unplugged FREE each week in your inbox. Sign up here: https://curzio.me/syn_wsu Find Wall Street Unplugged podcast… --Curzio Research App: https://curzio.me/syn_app --iTunes: https://curzio.me/syn_wsu_i --Stitcher: https://curzio.me/syn_wsu_s --Website: https://curzio.me/syn_wsu_cat Follow Frank… X: https://curzio.me/syn_twt Facebook: https://curzio.me/syn_fb LinkedIn: https://curzio.me/syn_li

Carl Quintanilla, Jim Cramer and David Faber led off the show with what to expect from Nvidia when the world's most valuable company releases its quarterly results after Wednesday's close of trading. According to CNBC sources, Fed governor Lisa Cook could file a lawsuit to overturn her firing by President Trump as soon as today in federal court. Also in focus: MongoDB and Kohl's among the stocks soaring on earnings news, shares of EchoStar double after its $23 billion spectrum deal with AT&T this week, President Trump hits India with 50% tariffs, NFL star Travis Kelce launches his new American Eagle Outfitters clothing line after his engagement to Taylor Swift.  Squawk on the Street Disclaimer

Carl Quintanilla, Mike Santoli and David Faber interviewed Sen. Elizabeth Warren at the top of the show, discussing President Trump's firing of Fed Governor Lisa Cook, as well as her thoughts on the government's 10% stake in Intel. The anchors also discussed the potential overblown fears of the slowdown for software after shares of MongoDB shares surged more than 30% on their earnings print. Also in the mix: CNBC's Diana Olick discussed her new piece on how mortgage fraud might be less widespread than people think.

Some software names got an earnings boost ahead of Nvidia's (NVDA) market moving report after the bell. Jenny Horne talks about the heavy bullish commentary from MongoDB's (MDB) leadership after the company posted a massive beat. Okta Inc. (OKTA) rallied on its own beat and raise, a reversal from the cybersecurity firm's last earnings. ======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

In der heutigen Folge sprechen die Finanzjournalisten Anja Ettel und Philipp Vetter über den Swiftie-Push für Ralph Lauren, gute Nachrichten von Eli Lillys Abnehmpille und das bange Warten auf die Nvidia-Zahlen. Außerdem geht es um Novo Nordisk, AT&T, EchoStar, MongoDB, Okta, BASF, Commerzbank, BNP Paribas, Socitété Générale, Crédit Agricole, Axa, Procter&Gamble, SPDR MSCI Europe Consumer Staples ETF (WKN: A1191N), Nestlé, Unilever, L'Oreal, Anheuser Busch InBev, Amundi STOXX Europe 600 Consumer Staples ETF (WKN: LYX02J) und iShares MSCI EU Consumer Staples ETF (WKN: A2QBZ2). Die Tickets zum Finance Summit am 17. September bekommt ihr 40 Euro günstiger – aber nur mit dem exklusiven Code AAA2025, der ihr unter dem folgenden Link eingeben müsst: https://veranstaltung.businessinsider.de/BN5aLV Außerdem könnt ihr unter diesem Link euer Depot hochladen – und mit etwas Glück wird kein Geringerer als Christian W. Röhl euer Depot beim Summit checken und optimieren. https://form.jotform.com/Product_Unit/formular-finance-summit-depot-check Wir freuen uns an Feedback über aaa@welt.de. Noch mehr "Alles auf Aktien" findet Ihr bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts und AAA-Newsletter. Hier bei WELT: https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html. Der Börsen-Podcast Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte! https://linktr.ee/alles_auf_aktien Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

In this episode of The Playbook Universe, we sit down with Paul Cap, Chief Revenue Officer at MongoDB, to explore the core leadership principles and sales execution strategies that have driven one of the most explosive growth stories in tech. Paul shares his personal path from finance into sales, the pivotal mindset shifts that helped him lead at scale, and the mission-first approach that keeps MongoDB thriving. We dive into building high-performance teams, the early indicators of future CRO talent, and what separates great companies from the rest. Whether you're a first-line manager or a seasoned sales leader, this conversation delivers hard-earned lessons from the frontlines.

Former Atlanta Fed President Dennis Lockhart weighs in on Fed policy and the latest around Lisa Cook. Steve Kovach breaks down MongoDB and Okta earnings results. Courtney Reagan analyzes PVH's latest quarterly performance. BofA's Jill Carey Hall explores small-cap opportunities with the Fed potentially cutting rates. Bespoke Co-Founder Paul Hickey provides comprehensive market analysis while Guy Adami delivers Fast Money's first look at market movers. Wells Fargo's Aaron Rakers offers an essential Nvidia earnings preview ahead of the chip giant's highly anticipated results. 

My guest today is Harish Chandramowli, Co-founder & CTO of Flair software.In this conversation, Harish talks about his journey from his early university days in India at Amrita University to leading roles in major companies like Bloomberg and MongoDB. He articulates his shift to a niche field combining software engineering with security, his experience at Johns Hopkins University, and his eventual move into cloud security engineering. Harish shares insightful narratives about his founding a small startup and the creation and development of Flair, a fashion tech platform, highlighting the challenges and triumphs he encountered. Topics include his approach to managing remote teams, dealing with the pressures of startup life, the challenges of prioritization, and maintaining a work-life balance. Harish also discusses the importance of understanding customer needs and integrating AI and security in product development.Some of the topics covered are:Introduction and Early CareerGraduate Studies and Early Professional ExperienceCareer at Bloomberg and MongoDBStartup Journey and MongoDB ExperienceTransition to Flair and Early ChallengesInsights on Security and AIBuilding Flair and Remote Team ManagementEmpowering Engineers Through Customer InteractionChallenges of Managing Remote TeamsRetention and Team DynamicsBalancing Startup Pressures and Personal GrowthNavigating the Fashion Industry's Legal LandscapeBuilding Global Products from IndiaStaying Grounded Amidst Startup ChallengesHarish Chandramowli is a second-time founder who started his career in deeply technical roles—building cloud infrastructure and security at MongoDB. Over time, he evolved from shipping code to selling ideas—learning the language of customers, diving into sales-led discovery, and translating that into product strategy. Today, Harish blends technical depth with commercial instinct to build tools that solve real operational pain with clarity and impact

Agentic AI programming is what happens when coding assistants stop acting like autocomplete and start collaborating on real work. In this episode, we cut through the hype and incentives to define “agentic,” then get hands-on with how tools like Cursor, Claude Code, and LangChain actually behave inside an established codebase. Our guest, Matt Makai, now VP of Developer Relations at DigitalOcean, creator of Full Stack Python and Plushcap, shares hard-won tactics. We unpack what breaks, from brittle “generate a bunch of tests” requests to agents amplifying technical debt and uneven design patterns. Plus, we also discuss a sane git workflow for AI-sized diffs. You'll hear practical Claude tips, why developers write more bugs when typing less, and where open source agents are headed. Hint: The destination is humans as editors of systems, not just typists of code. Episode sponsors Posit Talk Python Courses Links from the show Matt Makai: linkedin.com Plushcap Developer Content Analytics: plushcap.com DigitalOcean Gradient AI Platform: digitalocean.com DigitalOcean YouTube Channel: youtube.com Why Generative AI Coding Tools and Agents Do Not Work for Me: blog.miguelgrinberg.com AI Changes Everything: lucumr.pocoo.org Claude Code - 47 Pro Tips in 9 Minutes: youtube.com Cursor AI Code Editor: cursor.com JetBrains Junie: jetbrains.com Claude Code by Anthropic: anthropic.com Full Stack Python: fullstackpython.com Watch this episode on YouTube: youtube.com Episode #517 deep-dive: talkpython.fm/517 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Python's data stack is getting a serious GPU turbo boost. In this episode, Ben Zaitlen from NVIDIA joins us to unpack RAPIDS, the open source toolkit that lets pandas, scikit-learn, Spark, Polars, and even NetworkX execute on GPUs. We trace the project's origin and why NVIDIA built it in the open, then dig into the pieces that matter in practice: cuDF for DataFrames, cuML for ML, cuGraph for graphs, cuXfilter for dashboards, and friends like cuSpatial and cuSignal. We talk real speedups, how the pandas accelerator works without a rewrite, and what becomes possible when jobs that used to take hours finish in minutes. You'll hear strategies for datasets bigger than GPU memory, scaling out with Dask or Ray, Spark acceleration, and the growing role of vector search with cuVS for AI workloads. If you know the CPU tools, this is your on-ramp to the same APIs at GPU speed. Episode sponsors Posit Talk Python Courses Links from the show RAPIDS: github.com/rapidsai Example notebooks showing drop-in accelerators: github.com Benjamin Zaitlen - LinkedIn: linkedin.com RAPIDS Deployment Guide (Stable): docs.rapids.ai RAPIDS cuDF API Docs (Stable): docs.rapids.ai Asianometry YouTube Video: youtube.com cuDF pandas Accelerator (Stable): docs.rapids.ai Watch this episode on YouTube: youtube.com Episode #516 deep-dive: talkpython.fm/516 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

What happens when a cybersecurity engineer walks into a fashion boutique? For Harish Chandramowli, it sparked an idea that's now helping small fashion brands save time, money, and sanity. A chance observation in a New York store became a mission to untangle problems in inventory, communication, and operations many brands struggle with. In this episode, I speak with Harish, founder of Flair Software, about how he went from working at Bloomberg and MongoDB to building a platform that fixes the messy back-office problems fashion brands face. Harish explains why seasonal inventory is a high-stakes game, how communication breakdowns can cost thousands, and why he built his solution to integrate with Shopify instead of competing against it. Tune in now to learn more. --- Listen to the podcast here: From Cybersecurity to Fashion Tech with Harish Chandramowli Welcome to Action's Antidotes, your antidote to the mindset that keeps you settling for less. We have a lot of technological advances, a lot of digital technology, and a lot of the efforts around it have been used primarily around digital products, primarily around some of the platforms and everything else, but there's also an aspect that I'm hopeful around that really takes some of the digital technology that we have and uses it to enhance the physical products and the actual life that we have outside of our computers in real life. My guest today, Harish Chandramowli, is the founder of Flaire Software and he has some interesting solutions for the fashion industry and other kind of inventory-related pursuits. ---   Harish, welcome to the program.   It's a pleasure to be here.    Thank you for joining us. Now, first of all, kind of have your feet in both worlds, whether it be kind of our technological world as well as the world of fashion, the world of some of these in-real-life types of pursuits. Tell me a bit about your story, where you started and how you came up with the idea, what you observed that led to Flaire Software.   Yeah. Just taking a step back, I am not from fashion industry. It's all pretty new to me. I did my master's in cyber security actually in Johns Hopkins, then I worked as security engineer in a bunch of very data-related platforms like Bloomberg, MongoDB. And MongoDB was my last gig where I primarily started as cloud security engineer but moved on to like an Atlas dedicated team where you see how lot of different people use databases. And, interestingly, there are a lot of retail companies using databases very heavily. That made me more and more curious on how software is being used in retail industry and why database is like one of the biggest line expenditures. On top of that, when I was looking into ERPs, Oracle is one of the biggest player in the ERP market, which made me even more curious on what this space is. What happens around here? Why is a database company spending so much on an ERP, on like a data workflow?    Yeah.   This kind of made me curious but, again, it was more like I don't think I was into fashion or any of those things. I went to this store called ONS in Soho. It's a great store you should check out if you are ever in like downtown area in New York.    What's the store called again?   ONS.   Okay.   Orange, Naples, San Diego. So if you go to Soho and like downtown in the fashion districts, you will notice a lot of these small, small brands which is not your typical H&Ms or Zara.   Yeah.    So I was there, I was actually listening to their team meetings, talking a lot with their founder. I was looking at how they are operating in the back office. The first thing that stood out to me is that fashion as a whole uses a lot of software. One aspect of it which we are all familiar with is designing the fashion, like the threading, modeling and like the cut and everything. Another easier to relate option is like e-commerce site, where you list,

Episode Summary:AWS Morning Brief for the week of August 18th, 2025, with Corey Quinn. Links: Firefly's 2025 IaC Best Practices Guidea billion dollars in savings highlights why I'm wrongDemystifying Amazon Bedrock Pricing for a Chatbot AssistantImproving Your Visibility to AWS Sales: A Practical Guide for PartnersAnthropic's Claude Sonnet 4 in Amazon Bedrock Expanded Context WindowAmazon EC2 Single GPU P5 instances are now generally available Announcing Extended Support for Amazon DocumentDB (with MongoDB compatibility) version 3.6CVE-2025-8904 - Issue with Amazon EMR Secret Agent componentAmazon DynamoDB now supports more frequent throughput mode updates from provisioned to on-demand capacity Validate radiology reports using Amazon NovaAmazon FSx for OpenZFS now supports Internet Protocol Version 6 (IPv6)AWS Resource Explorer now Supports Filtering for Multiple ValuesAWS IAM Identity Center introduces support for user background sessions with Amazon SageMaker Studio Amazon FSx for NetApp ONTAP now supports decreasing your SSD storage capacity AWS Security Incident Response now supports membership coverage for individual AWS organizational unitsUnderstanding AWS Savings Plan Recommendations: Payer vs. Linked Account Views 

When your only tool is a hammer - everything looks like a nail.2 of these database I'm sure you've heard and 2 might be completely new to you.Let's go past MongoDB and SQL to learn what tool is best for what job and what's the database choice for AI in 2025.If you're interested in learning SQL, check out this episode: https://open.spotify.com/show/69BHCbRAl6rHT9LlNhFWUySend us a textShameless Plugs

What if your code was crash-proof? That's the value prop for a framework called Temporal. Temporal is a durable execution platform that enables developers to build scalable applications without sacrificing productivity or reliability. The Temporal server executes units of application logic called Workflows in a resilient manner that automatically handles intermittent failures, and retries failed operations. We have Mason Egger from Temporal on to dive into durable execution. Episode sponsors Posit PyBay Talk Python Courses Links from the show Just Enough Python for Data Scientists Course: talkpython.fm Temporal Durable Execution Platform: temporal.io Temporal Learn Portal: learn.temporal.io Temporal GitHub Repository: github.com Temporal Python SDK GitHub Repository: github.com What Is Durable Execution, Temporal Blog: temporal.io Mason on Bluesky Profile: bsky.app Mason on Mastodon Profile: fosstodon.org Mason on Twitter Profile: twitter.com Mason on LinkedIn Profile: linkedin.com X Post by @skirano: x.com Temporal Docker Compose GitHub Repository: github.com Building a distributed asyncio event loop (Chad Retz) - PyTexas 2025: youtube.com Watch this episode on YouTube: youtube.com Episode #515 deep-dive: talkpython.fm/515 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Rob Zuber sits down with Tara Hernandez, VP of Developer Productivity at MongoDB and former Netscape engineer who helped create early continuous integration systems, to explore strategic frameworks for build vs. buy decisions in modern software delivery.Hernandez shares insights from scaling MongoDB's proprietary CI system—processing 10 engineer years of compute daily—and reveals how organizations can evaluate when custom infrastructure drives competitive advantage versus when strategic partnerships accelerate growth. Her perspective on navigating the evolving landscape of CI/CD tooling offers actionable guidance for engineering leaders balancing innovation with operational efficiency.Have someone in mind you'd like to hear on the show? Reach out to us on X at @CircleCI!

In this event, Shane McAllister will cover how Albert Podusenko got introduced to MongoDB and in 2016 decided to start a company using MongoDB as primary database behind their server, handling everything: From model states and real-time event generation to maintaining episodes and storing historical data.In this show we'll talk about:How to make a product out of research.Walk through it's journey that culminated with the creation of Lazy Dynamics.Show how they utilize MongoDB with demos and examples.

In this episode of Tech Talks Daily, I sat down with Boris Bialek, VP and Field CTO at MongoDB, for a conversation that moved well beyond databases. As AI continues to accelerate across sectors, MongoDB is positioning itself at the intersection of modern data architecture and intelligent application development. Boris shared how his team is simplifying AI adoption for enterprises, with a clear focus on real-world outcomes, developer productivity, and global inclusion. We began by exploring MongoDB's recent acquisition of Voyage AI. This move extends MongoDB's native capabilities into vector search, embeddings, and re-rankers, allowing developers to build AI-powered applications more efficiently. Boris explained how MongoDB is removing the complexity from AI integration by providing a unified API, collapsing what used to be 18 disconnected tools into a streamlined developer experience. But the discussion wasn't just about technology. Boris brought a passionate focus to the issue of financial inclusion. We talked about how AI can enable alternative credit scoring for the 27 percent of adults globally who remain unbanked. By analyzing behavioral signals such as mobile payment histories or utility data, AI can help unlock microcredit opportunities for individuals and small businesses in underserved regions. Boris shared use cases from PicPay in Brazil, M-Pesa in Africa, and Proxtera in Singapore, each demonstrating how AI and MongoDB are enabling new forms of digital trust. We also tackled the organizational and technical hurdles to enterprise AI adoption. From fears about hallucinations to managing constant model updates, Boris described how MongoDB is building systems that prioritize transparency, auditability, and scale. With its document model and integrated tooling, MongoDB offers a stable foundation for companies navigating fast-moving AI transformations. For developers, the platform now includes learnmongodb.com and quick-skill badges designed to make AI approachable and hands-on. And with the upcoming release of Boris's new book, there's more to come on how businesses can move from pilot experiments to production-grade solutions. How is your organization rethinking its data strategy to make AI work at scale?

Jessica Zwaan and Joris Luijke joined us to break down the what, why, and how to create an employee journey map. We talked about why People teams should be designing for moments and not just processes, why journey mapping should start small, and why 80% of employee moments fall flat.---- Sponsor Links:

Every year the core developers of Python convene in person to focus on high priority topics for CPython and beyond. This year they met at PyCon US 2025. Those meetings are closed door to keep focused and productive. But we're lucky that Seth Michael Larson was in attendance and wrote up each topic presented and the reactions and feedback to each. We'll be exploring this year's Language Summit with Seth. It's quite insightful to where Python is going and the pressing matters. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Sentry AI Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Seth on Mastodon: @sethmlarson@fosstodon.org Seth on Twitter: @sethmlarson Seth on Github: github.com Python Language Summit 2025: pyfound.blogspot.com WheelNext: wheelnext.dev Free-Threaded Wheels: hugovk.github.io Free-Threaded Python Compatibility Tracking: py-free-threading.github.io PEP 779: Criteria for supported status for free-threaded Python: discuss.python.org PyPI Data: py-code.org Senior Engineer tries Vibe Coding: youtube.com Watch this episode on YouTube: youtube.com Episode #514 deep-dive: talkpython.fm/514 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Why do people list to this podcast? Sure, they're looking for technical explorations of new libraries and ideas. But often it's to hear the story behind them. If that speaks to you, then I have the perfect episode lined up. I have Barry Warsaw, Paul Everitt, Carol Willing, and Brett Cannon all back on the show to share stories from the history of Python. You'll hear about how import this came to be and how the first PyCon had around 30 attendees (two of whom are guests on this episode!). Sit back and enjoy the humorous stories from Python's past. Episode sponsors Posit Agntcy Talk Python Courses Links from the show Barry's Zen of Python song: youtube.com Jake Vanderplas - Keynote - PyCon 2017: youtube.com Why it's called “Python” (Monty Python fan-reference): geeksforgeeks.org import antigravity: python-history.blogspot.com NIST Python Workshop Attendees: legacy.python.org Paul Everitt open-sources Zope: old.zope.dev Carol Willing wins ACM Software System Award: awards.acm.org Watch this episode on YouTube: youtube.com Episode #513 deep-dive: talkpython.fm/513 Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Maor Shlomo is the founder of Base44, an AI-powered app builder that he bootstrapped to an over $80 million acquisition by Wix in just six months. As a solo founder (with severe ADHD), he hit $1 million ARR just three weeks after launch and grew the product to more than 400,000 users, all while navigating two wars in Israel and never raising a dollar of outside funding.What you'll learn:1. The growth playbook that took Base44 from three friends to 400,000 users without spending any money on marketing2. How he hasn't written a single line of front-end code in three months—and how to structure your code repository to make it easier for AI to write your code3. His AI productivity stack that allowed him to compete against heavily funded competitors4. Why being a solo founder in AI might be the ultimate advantage (and the wedding story that almost killed the business)5. The story of signing the $80M acquisition deal while war broke out with Iran6. How to identify when to sell vs. stay independent (and why Maor chose acquisition despite being highly profitable)7. The counterintuitive product decision that tripled activation by removing a “helpful” feature8. How building in public on LinkedIn drove more growth than any paid channel—Brought to you by:Sauce—Turn customer pain into product revenue: https://sauce.app/lennyDscout—The UX platform to capture insights at every stage: from ideation to production: https://www.dscout.com/Contentsquare—Create better digital experiences: https://contentsquare.com/lenny/—Transcript: ⁠https://www.lennysnewsletter.com/p/the-base44-bootstrapped-startup-success-story-maor-shlomo⁠—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/167384119/my-biggest-takeaways-from-this-conversation—Where to find Maor Shlomo:• X: https://x.com/ms_base44• LinkedIn: https://www.linkedin.com/in/maor-shlomo-1088b4144/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Maor and Base44(08:16) The origin story: how Base44 came to be(14:55) Bootstrapping and solo founding: challenges and insights(22:52) Productivity hacks and tech stack for solo founders(27:23) How to get started using Base44(28:47) Thoughts on raising money(34:05) Distribution in the age of AI(36:09) Ambition and goals(40:05) Growth strategies: from first users to thousands(51:32) Building in public(57:42) The solo founder journey(01:00:23) Community support(01:03:23) Hackathons and partnerships(01:06:42) The importance of velocity in product development(01:08:20) Technical stack and infrastructure insights(01:15:24) Activation lessons(01:18:19) The acquisition journey with Wix(01:25:14) Final thoughts and advice for founders—Referenced:• Base44: https://base44.com/• Retool: https://retool.com/• Tzofim: https://www.israelscouts.org/• Y Combinator: https://www.ycombinator.com/• RescueTime: https://www.rescuetime.com/• Cursor: https://www.cursor.com/• Wix: https://www.wix.com/• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (CEO and co-founder): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/inside-bolt-eric-simons• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Snowflake: https://www.snowflake.com• Yoav Orlev on LinkedIn: https://www.linkedin.com/in/yoav-orlev-4a044b72• WhatsApp: https://www.whatsapp.com/• Amazon: https://www.amazon.com/• Google: https://about.google/• MongoDB: https://www.mongodb.com/• Deloitte: https://www.deloitte.com/• Render: Render.com• Claude 4: https://www.anthropic.com/news/claude-4• Gemini: https://gemini.google.com/app• Cloudflare: https://www.cloudflare.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Do you like to dive into the details and intricacies of how Python executes and how we can optimize it? Well, do I have an episode for you. We welcome back Brandt Bucher to give us an update on the upcoming JIT compiler for Python and why it differs from JITs for languages such as C# and Java. Episode sponsors Posit Talk Python Courses Links from the show Brandt Bucher: github.com/brandtbucher PyCon Talk: What they don't tell you about building a JIT compiler for CPython: youtube.com Specializing, Adaptive Interpreter Episode: talkpython.fm Watch this episode on YouTube: youtube.com Episode #512 deep-dive: talkpython.fm/512 Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy