Podcasts about Cloud computing

Topics covered in this episode: Better Django management commands with django-click and django-typer PSF Lands a $1.5 million sponsorship from Anthropic How uv got so fast PyView Web Framework Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Better Django management commands with django-click and django-typer Lacy Henschel Extend Django manage.py commands for your own project, for things like data operations API integrations complex data transformations development and debugging Extending is built into Django, but it looks easier, less code, and more fun with either django-click or django-typer, two projects supported through Django Commons Michael #2: PSF Lands a $1.5 million sponsorship from Anthropic Anthropic is partnering with the Python Software Foundation in a landmark funding commitment to support both security initiatives and the PSF's core work. The funds will enable new automated tools for proactively reviewing all packages uploaded to PyPI, moving beyond the current reactive-only review process. The PSF plans to build a new dataset of known malware for capability analysis The investment will sustain programs like the Developer in Residence initiative, community grants, and infrastructure like PyPI. Brian #3: How uv got so fast Andrew Nesbitt It's not just be cause “it's written in Rust”. Recent-ish standards, PEPs 518 (2016), 517 (2017), 621 (2020), and 658 (2022) made many uv design decisions possible And uv drops many backwards compatible decisions kept by pip. Dropping functionality speeds things up. “Speed comes from elimination. Every code path you don't have is a code path you don't wait for.” Some of what uv does could be implemented in pip. Some cannot. Andrew discusses different speedups, why they could be done in Python also, or why they cannot. I read this article out of interest. But it gives me lots of ideas for tools that could be written faster just with Python by making design and support decisions that eliminate whole workflows. Michael #4: PyView Web Framework PyView brings the Phoenix LiveView paradigm to Python Recently interviewed Larry on Talk Python Build dynamic, real-time web applications using server-rendered HTML Check out the examples. See the Maps demo for some real magic How does this possibly work? See the LiveView Lifecycle. Extras Brian: Upgrade Django, has a great discussion of how to upgrade version by version and why you might want to do that instead of just jumping ahead to the latest version. And also who might want to save time by leapfrogging Also has all the versions and dates of release and end of support. The Lean TDD book 1st draft is done. Now available through both pythontest and LeanPub I set it as 80% done because of future drafts planned. I'm working through a few submitted suggestions. Not much feedback, so the 2nd pass might be fast and mostly my own modifications. It's possible. I'm re-reading it myself and already am disappointed with page 1 of the introduction. I gotta make it pop more. I'll work on that. Trying to decide how many suggestions around using AI I should include. It's not mentioned in the book yet, but I think I need to incorporate some discussion around it. Michael: Python: What's Coming in 2026 Python Bytes rewritten in Quart + async (very similar to Talk Python's journey) Added a proper MCP server at Talk Python To Me (you don't need a formal MCP framework btw) Example one: latest-episodes-mcp.png Example two: which-episodes-mcp.webp Implmented /llms.txt for Talk Python To Me (see talkpython.fm/llms.txt ) Joke: Reverse Superman

The industry has pivoted from scripting to automation to orchestration – and now to systems that can reason. Today we explore what AI agents mean for infrastructure with Chris Wade, Co-Founder and CTO of Itential. We also dive into the brownfield reality, the potential for vendor-specific LLMs trained on proprietary knowledge, and advice for the... Read more »

Your cloud SSD is sitting there, bored, and it would like a job. Today we're putting it to work with DiskCache, a simple, practical cache built on SQLite that can speed things up without spinning up Redis or extra services. Once you start to see what it can do, a universe of possibilities opens up. We're joined by Vincent Warmerdam to dive into DiskCache. Episode sponsors Talk Python Courses Python in Production Links from the show diskcache docs: grantjenks.com LLM Building Blocks for Python course: training.talkpython.fm JSONDisk: grantjenks.com Git Code Archaeology Charts: koaning.github.io Talk Python Cache Admin UI: blobs.talkpython.fm Litestream SQLite streaming: litestream.io Plash hosting: pla.sh Watch this episode on YouTube: youtube.com Episode #534 deep-dive: talkpython.fm/534 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Philip Johnston is co-founder and CEO of Starcloud, a company building data centers in space to solve AI's power crisis. Starcloud has already launched the first NVIDIA H100 GPU into orbit and is partnering with cloud providers like Crusoe to scale orbital computing infrastructure.As AI demand accelerates, data centers are running into a new bottleneck: access to reliable, affordable power. Grid congestion, interconnection delays, and cooling requirements are slowing the deployment of new AI data centers, even as compute demand continues to surge. Traditional data centers face 5-10 year lead times for new power projects due to permitting, interconnection queues, and grid capacity constraints.In this episode, Philip explains why Starcloud is building data centers in orbit, where continuous solar power is available and heat can be rejected directly into the vacuum of space. He walks through Starcloud's first on-orbit GPU deployment, the realities of cooling and radiation in space, and how orbital data centers could relieve pressure on terrestrial power systems as AI infrastructure scales.Episode recorded on Dec 11, 2025 (Published on Jan 13, 2026)In this episode, we cover: [04:59] What Starcloud's orbital data centers look like (and how they differ from terrestrial facilities)[06:37] How SpaceX Starship's reusable launch vehicles change space economics[10:45] The $500/kg breakeven point for space-based solar vs. Earth [14:15] Why space solar panels produce 8x more energy than ground-based arrays [21:19] Thermal management: Cooling NVIDIA GPUs in a vacuum using radiators [25:57] Edge computing in orbit: Real-time inference on satellite imagery [29:22] The Crusoe partnership: Selling power-as-a-service in space [31:21] Starcloud's business model: Power, cooling, and connectivity [34:18] Addressing critics: What could prevent orbital data centers from workingKey Takeaways:Starcloud launched the first NVIDIA H100 GPU into orbit in November 2024 Space solar produces 8x more energy per square meter than terrestrial solar Breakeven launch cost for orbital data centers: $500/kg Current customers: DOD and commercial Earth observation satellites needing real-time inference Target: 10 gigawatts of orbital computing capacity by early 2030s Enjoyed this episode? Please leave us a review! Share feedback or suggest future topics and guests at info@mcj.vc.Connect with MCJ:Cody Simms on LinkedInVisit mcj.vcSubscribe to the MCJ Newsletter*Editing and post-production work for this episode was provided by The Podcast Consultant

Neo4j's Ajay Singh discusses future shifts in AI and why knowledge graphs may be the missing layer in your Gen AI strategy.Topics Include:Ajay Singh from Neo4j discusses graph intelligence platform serving 80+ Fortune 100 companies.Financial services firms use Neo4j knowledge graphs to detect fraud rings and accounts.IT companies build digital twins of infrastructure to analyze attack surfaces and vulnerabilities.Knowledge graphs provide richer context for Gen AI agents beyond what vector search offers.Gaming company achieved 10x faster insights and 92% reduction in analyst data gathering.Transportation company improved tariff code workflow from 50% abandonment to 95% completion rate.Neo4j has partnered with AWS since 2013, running on AWS infrastructure and Marketplace.Customers combine Neo4j with AWS Bedrock and SageMaker to build agentic AI applications.Neo4j evolved from late-stage AWS collaboration to early-stage joint customer solution development approach.Success requires business-first mindset over technology-first to avoid POCs that never reach production.Effective Gen AI needs semantic layers and knowledge graphs, not just throwing documents at LLMs.Future agents will tackle outcome-based objectives requiring explainability, security, and proper LLM operations.Participants:Ajay Singh – Global Vice President, Neo4jSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Topics covered in this episode: port-killer How we made Python's packaging library 3x faster CodSpeed Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: port-killer A powerful cross-platform port management tool for developers. Monitor ports, manage Kubernetes port forwards, integrate Cloudflare Tunnels, and kill processes with one click. Features:

Executives from March Networks explain how Amazon Bedrock transformed petabytes of surveillance video into economically viable solutions that unlock untapped business value.Topics Include:March Networks CEO and CPO discuss video surveillance for enterprise banks and retailers globallyCompany serves 10,000 customers with 250,000 installations worldwide since 2003 from Ottawa headquartersBanking customer operates across 25 countries centralizing video operations on one standardized platformSingle enterprise customer manages 65 petabytes of distributed data across March Networks recordersAWS partnership enables five-to-ten-year cloud transition starting with economical DeepGlacier storage solutionsAmazon Bedrock powers AI Smart Search analyzing snapshots for searchable business intelligence insightsEnterprise video data remains largely untapped for retail traffic patterns and operational efficiencyOne retailer processes three million daily POS transactions across 6,000 locations synchronized with video2025 brought AI Smart Search launch enabling natural language queries across entire operationsCloud storage became economically viable using Glacier after traditional quotes reached millions annuallyFraudsters exploit 90-180 day retention windows by waiting six months to file lawsuits2026 vision emphasizes consultative selling for efficiency gains supported by strong AWS partnershipParticipants:Peter Strom – President & Chief Executive Officer, March NetworksJeff Corrall – Chief Product Officer, March NetworksSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

In this special encore episode from AWS re:Invent, AWS CEO Matt Garman joins Acquired podcast co-hosts Ben Gilbert and David Rosenthal for an in-depth conversation on AI, agents, and the future of business. Listen in as Garman shares his leadership journey from AWS intern to CEO, discusses why inference is becoming a fundamental building block for developers, and reveals how AI is enabling smaller teams to deliver exponentially more value. He also explores the organizational shifts enterprises must make to stay competitive, the evolution of agentic AI, and why agility and speed remain critical regardless of technological change.To catch the full interview session featuring additional speakers, Max Neukirchen (J.P. Morgan Payments), Greg Peters (Netflix), and Aravind Srivinas (Perplexity), click here to watch on YouTube -> https://www.youtube.com/watch?v=2ExjNvGYDiU.

Today on Talk Python, the creators behind FastAPI, Flask, Django, Quart, and Litestar get practical about running apps based on their framework in production. Deployment patterns, async gotchas, servers, scaling, and the stuff you only learn at 2 a.m. when the pager goes off. For Django, we have Carlton Gibson and Jeff Triplet. For Flask, we have David Lord and Phil Jones, and on team Litestar we have Janek Nouvertné and Cody Fincher, and finally Sebastián Ramírez from FastAPI is here. Let's jump in. Episode sponsors Talk Python Courses Python in Production Links from the show Carlton Gibson - Django: github.com Sebastian Ramirez - FastAPI: github.com David Lord - Flask: davidism.com Phil Jones - Flask and Quartz(async): pgjones.dev Yanik Nouvertne - LiteStar: github.com Cody Fincher - LiteStar: github.com Jeff Triplett - Django: jefftriplett.com Django: www.djangoproject.com Flask: flask.palletsprojects.com Quart: quart.palletsprojects.com Litestar: litestar.dev FastAPI: fastapi.tiangolo.com Coolify: coolify.io ASGI: asgi.readthedocs.io WSGI (PEP 3333): peps.python.org Granian: github.com Hypercorn: github.com uvicorn: uvicorn.dev Gunicorn: gunicorn.org Hypercorn: hypercorn.readthedocs.io Daphne: github.com Nginx: nginx.org Docker: www.docker.com Kubernetes: kubernetes.io PostgreSQL: www.postgresql.org SQLite: www.sqlite.org Celery: docs.celeryq.dev SQLAlchemy: www.sqlalchemy.org Django REST framework: www.django-rest-framework.org Jinja: jinja.palletsprojects.com Click: click.palletsprojects.com HTMX: htmx.org Server-Sent Events (SSE): developer.mozilla.org WebSockets (RFC 6455): www.rfc-editor.org HTTP/2 (RFC 9113): www.rfc-editor.org HTTP/3 (RFC 9114): www.rfc-editor.org uv: docs.astral.sh Amazon Web Services (AWS): aws.amazon.com Microsoft Azure: azure.microsoft.com Google Cloud Run: cloud.google.com Amazon ECS: aws.amazon.com AlloyDB for PostgreSQL: cloud.google.com Fly.io: fly.io Render: render.com Cloudflare: www.cloudflare.com Fastly: www.fastly.com Watch this episode on YouTube: youtube.com Episode #533 deep-dive: talkpython.fm/533 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Topics covered in this episode: ty: An extremely fast Python type checker and LSP Python Supply Chain Security Made Easy typing_extensions MI6 chief: We'll be as fluent in Python as we are in Russian Extras Joke Watch on YouTube About the show Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: ty: An extremely fast Python type checker and LSP Charlie Marsh announced the Beta release of ty on Dec 16 “designed as an alternative to tools like mypy, Pyright, and Pylance.” Extremely fast even from first run Successive runs are incremental, only rerunning necessary computations as a user edits a file or function. This allows live updates. Includes nice visual diagnostics much like color enhanced tracebacks Extensive configuration control Nice for if you want to gradually fix warnings from ty for a project Also released a nice VSCode (or Cursor) extension Check the docs. There are lots of features. Also a note about disabling the default language server (or disabling ty's language server) so you don't have 2 running Michael #2: Python Supply Chain Security Made Easy We know about supply chain security issues, but what can you do? Typosquatting (not great) Github/PyPI account take-overs (very bad) Enter pip-audit. Run it in two ways: Against your installed dependencies in current venv As a proper unit test (so when running pytest or CI/CD). Let others find out first, wait a week on all dependency updates: uv pip compile requirements.piptools --upgrade --output-file requirements.txt --exclude-newer "1 week" Follow up article: DevOps Python Supply Chain Security Create a dedicated Docker image for testing dependencies with pip-audit in isolation before installing them into your venv. Run pip-compile / uv lock --upgrade to generate the new lock file Test in a ephemeral pip-audit optimized Docker container Only then if things pass, uv pip install / uv sync Add a dedicated Docker image build step that fails the docker build step if a vulnerable package is found. Brian #3: typing_extensions Kind of a followup on the deprecation warning topic we were talking about in December. prioinv on Mastodon notified us that the project typing-extensions includes it as part of the backport set. The warnings.deprecated decorator is new to Python 3.13, but with typing-extensions, you can use it in previous versions. But typing_extesions is way cooler than just that. The module serves 2 purposes: Enable use of new type system features on older Python versions. Enable experimentation with type system features proposed in new PEPs before they are accepted and added to the typing module. So cool. There's a lot of features here. I'm hoping it allows someone to use the latest typing syntax across multiple Python versions. I'm “tentatively” excited. But I'm bracing for someone to tell me why it's not a silver bullet. Michael #4: MI6 chief: We'll be as fluent in Python as we are in Russian "Advances in artificial intelligence, biotechnology and quantum computing are not only revolutionizing economies but rewriting the reality of conflict, as they 'converge' to create science fiction-like tools,” said new MI6 chief Blaise Metreweli. She focused mainly on threats from Russia, the country is "testing us in the grey zone with tactics that are just below the threshold of war.” This demands what she called "mastery of technology" across the service, with officers required to become "as comfortable with lines of code as we are with human sources, as fluent in Python as we are in multiple other languages." Recruitment will target linguists, data scientists, engineers, and technologists alike. Extras Brian: Next chapter of Lean TDD being released today, Finding Waste in TDD Still going to attempt a Jan 31 deadline for first draft of book. That really doesn't seem like enough time, but I'm optimistic. SteamDeck is not helping me find time to write But I very much appreciate the gift from my fam Send me game suggestions on Mastodon or Bluesky. I'd love to hear what you all are playing. Michael: Astral has announced the Beta release of ty, which they say they are "ready to recommend to motivated users for production use." Blog post Release page Reuven Lerner has a video series on Pandas 3 Joke: Error Handling in the age of AI Play on the inversion of JavaScript the Good Parts

In this episode of the Crazy Wisdom podcast, host Stewart Alsop interviews Marcin Dymczyk, CPO and co-founder of SevenSense Robotics, exploring the fascinating world of advanced robotics and AI. Their conversation covers the evolution from traditional "standard" robotics with predetermined pathways to advanced robotics that incorporates perception, reasoning, and adaptability - essentially the AGI of physical robotics. Dymczyk explains how his company builds "the eyes and brains of mobile robots" using camera-based autonomy algorithms, drawing parallels between robot sensing systems and human vision, inner ear balance, and proprioception. The discussion ranges from the technical challenges of sensor fusion and world models to broader topics including robotics regulation across different countries, the role of federalism in innovation, and how recent geopolitical changes are driving localized high-tech development, particularly in defense applications. They also touch on the democratization of robotics for small businesses and the philosophical implications of increasingly sophisticated AI systems operating in physical environments. To learn more about SevenSense, visit www.sevensense.ai.Check out this GPT we trained on the conversationTimestamps00:00 Introduction to Robotics and Personal Journey05:27 The Evolution of Robotics: From Standard to Advanced09:56 The Future of Robotics: AI and Automation12:09 The Role of Edge Computing in Robotics17:40 FPGA and AI: The Future of Robotics Processing21:54 Sensing the World: How Robots Perceive Their Environment29:01 Learning from the Physical World: Insights from Robotics33:21 The Intersection of Robotics and Manufacturing35:01 Journey into Robotics: Education and Passion36:41 Practical Robotics Projects for Beginners39:06 Understanding Particle Filters in Robotics40:37 World Models: The Future of AI and Robotics41:51 The Black Box Dilemma in AI and Robotics44:27 Safety and Interpretability in Autonomous Systems49:16 Regulatory Challenges in Robotics and AI51:19 Global Perspectives on Robotics Regulation54:43 The Future of Robotics in Emerging Markets57:38 The Role of Engineers in Modern WarfareKey Insights1. Advanced robotics transcends traditional programming through perception and intelligence. Dymczyk distinguishes between standard robotics that follows rigid, predefined pathways and advanced robotics that incorporates perception and reasoning. This evolution enables robots to make autonomous decisions about navigation and task execution, similar to how humans adapt to unexpected situations rather than following predetermined scripts.2. Camera-based sensing systems mirror human biological navigation. SevenSense Robotics builds "eyes and brains" for mobile robots using multiple cameras (up to eight), IMUs (accelerometers/gyroscopes), and wheel encoders that parallel human vision, inner ear balance, and proprioception. This redundant sensing approach allows robots to navigate even when one system fails, such as operating in dark environments where visual sensors are compromised.3. Edge computing dominates industrial robotics due to connectivity and security constraints. Many industrial applications operate in environments with poor connectivity (like underground grocery stores) or require on-premise solutions for confidentiality. This necessitates powerful local processing capabilities rather than cloud-dependent AI, particularly in automotive factories where data security about new models is paramount.4. Safety regulations create mandatory "kill switches" that bypass AI decision-making. European and US regulatory bodies require deterministic safety systems that can instantly stop robots regardless of AI reasoning. These systems operate like human reflexes, providing immediate responses to obstacles while the main AI brain handles complex navigation and planning tasks.5. Modern robotics development benefits from increasingly affordable optical sensors. The democratization of 3D cameras, laser range finders, and miniature range measurement chips (costing just a few dollars from distributors like DigiKey) enables rapid prototyping and innovation that was previously limited to well-funded research institutions.6. Geopolitical shifts are driving localized high-tech development, particularly in defense applications. The changing role of US global leadership and lessons from Ukraine's drone warfare are motivating countries like Poland to develop indigenous robotics capabilities. Small engineering teams can now create battlefield-effective technology using consumer drones equipped with advanced sensors.7. The future of robotics lies in natural language programming for non-experts. Dymczyk envisions a transformation where small business owners can instruct robots using conversational language rather than complex programming, similar to how AI coding assistants now enable non-programmers to build applications through natural language prompts.

Python in 2025 is in a delightfully refreshing place: the GIL's days are numbered, packaging is getting sharper tools, and the type checkers are multiplying like gremlins snacking after midnight. On this episode, we have an amazing panel to give us a range of perspectives on what matter in 2025 in Python. We have Barry Warsaw, Brett Cannon, Gregory Kapfhammer, Jodie Burchell, Reuven Lerner, and Thomas Wouters on to give us their thoughts. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Talk Python Courses Links from the show Python Software Foundation (PSF): www.python.org PEP 810: Explicit lazy imports: peps.python.org PEP 779: Free-threaded Python is officially supported: peps.python.org PEP 723: Inline script metadata: peps.python.org PyCharm: www.jetbrains.com JetBrains: www.jetbrains.com Visual Studio Code: code.visualstudio.com pandas: pandas.pydata.org PydanticAI: ai.pydantic.dev OpenAI API docs: platform.openai.com uv: docs.astral.sh Hatch: github.com PDM: pdm-project.org Poetry: python-poetry.org Project Jupyter: jupyter.org JupyterLite: jupyterlite.readthedocs.io PEP 690: Lazy Imports: peps.python.org PyTorch: pytorch.org Python concurrent.futures: docs.python.org Python Package Index (PyPI): pypi.org EuroPython: tickets.europython.eu TensorFlow: www.tensorflow.org Keras: keras.io PyCon US: us.pycon.org NumFOCUS: numfocus.org Python discussion forum (discuss.python.org): discuss.python.org Language Server Protocol: microsoft.github.io mypy: mypy-lang.org Pyright: github.com Pylance: marketplace.visualstudio.com Pyrefly: github.com ty: github.com Zuban: docs.zubanls.com Jedi: jedi.readthedocs.io GitHub: github.com PyOhio: www.pyohio.org Watch this episode on YouTube: youtube.com Episode #532 deep-dive: talkpython.fm/532 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Anthropic's Tobias Harrison Noonan shares the enterprise AI playbook: why coding leads to broader AI adoption, practical tips for getting started, and why you shouldn't wait for perfection.Topics Include:Tobias from Anthropic's Applied AI team discusses enterprise AI adoption trends and insights.Anthropic founded four years ago balancing AI safety mission with world's most intelligent models.Remarkable velocity: Claude 3.7 and Claude Code both shipped just in 2025 alone.Three-layer partnership: foundation models, enterprise capabilities, and end-user platforms like Claude Code.Anthropic leads in agentic coding for eighteen months, now number one enterprise AI market share.Claude Opus 4.5 launched last week, again tops software engineering benchmark for complex tasks.Claude Code enables thirty-hour autonomous coding sessions, ships features five times faster than before.Next frontier expands beyond coding into data-heavy knowledge work like financial and legal analysis.AI adoption maturity curve: employee workflows, internal processes, core products, then AI-native products.Thomson Reuters started with Claude Code for development team doing code modernization and refactoring.They expanded to Claude.ai for sales, marketing, and finance teams after seeing tangible ROI.Built Claude into core products including co-counsel legal platform and fraud prevention systems strategically.Today Thomson Reuters has eight different product lines powered by Claude across their portfolio.AWS partnership offers safe, secure, scalable deployment from POC to production in existing environments.Don't wait for perfection: AI today is dumbest it'll ever be, start prototyping now.Participants:Tobias Harrison-Noonan: Member of Technical Staff, AnthropicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

From all of us at Cloud Realities, MERRY CHRISTMAS!!!! Back in our December 2022 Christmas special, we explored the far reaches of reality, asking whether we live in a simulation and if that even matters. Now, we return to that question with fresh perspectives and new challenges…In this last Cloud Realities podcast of 2025, Dave, Esmee and Rob return to the simulation with Anders Indset, philosopher, author, and long-time friend of the show, revisiting a question that's been quietly running underneath everything we've discussed since 2022: If reality itself is information and what does that mean for being human? TLDR:00:58 – It's Christmas!08:32 – Major announcement and reflections on the Cloud Realities podcast journey15:32 – Celebrating three big wins: B2B Marketing Awards (Best Content, Best Customer Retention) and The Drum (Best Creative Audio)22:55 – Is there a next thing?23:30 – Welcoming Anders Indset, who shares his vision for practical philosophy and the future of human/AI co-evolution32:02 – Exploring the Quantum Economy and the Singularity Paradox58:10 – Deep dive into the Simulation Hypothesis, revisiting the 2022 discussion and Rob is again confused...01:27:45 – Anders enjoying Christmas in the Norwegian wilderness01:29:40 – Edit pointGuestAnders Indset: https://www.linkedin.com/in/andersindset/ or andersindset.comAdditional information: thequantumeconomy.com and tomorrowmensch.comHostsDave Chapmanger: https://www.linkedin.com/in/chapmandr/Esmee van de Gluhwein: https://www.linkedin.com/in/esmeevandegiessen/Rob Snowmananahan: https://www.linkedin.com/in/rob-kernahan/ProductionDr Mike van Der Buabbles: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapmanger: https://www.linkedin.com/in/chapmandr/ SoundBen Jingle: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Snow:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini

Topics covered in this episode: Has the cost of building software just dropped 90%? More on Deprecation Warnings How FOSS Won and Why It Matters Should I be looking for a GitHub alternative? Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. HEADS UP: We are taking next week off, happy holiday everyone. Michael #1: Has the cost of building software just dropped 90%? by Martin Alderson Agentic coding tools are collapsing “implementation time,” so the cost curve of shipping software may be shifting sharply Recent programming advancements haven't been that great of a true benefit: Cloud, TDD, microservices, complex frontends, Kubernetes, etc. Agentic AI's big savings are not just code generation, but coordination overhead reduction (fewer handoffs, fewer meetings, fewer blocks). Thinking, product clarity, and domain decisions stay hard, while typing and scaffolding get cheap. Is it the end of software dev? Not really, see Jevons paradox: when production gets cheaper, total demand can rise rather than spending simply falling. (Historically: the efficiency of coal use led to the increased consumption of coal) Pushes back on “only good for greenfield” by arguing agents also help with legacy code comprehension and bug-fixing. I 100% agree. #Legacy code for the win. Brian #2: More on Deprecation Warnings How are people ignoring them? yep, it's right in the Python docs: -W ignore::DeprecationWarning Don't do that! Perhaps the docs should give the example of emitting them only once -W once::::DeprecationWarning See also -X dev mode , which sets -W default and some other runtime checks Don't use warn, use the @warnings.deprecated decorator instead Thanks John Hagen for pointing this out Emits a warning It's understood by type checkers, so editors visually warn you You can pass in your own custom UserWarning with category mypy also has a command line option and setting for this --enable-error-code deprecated or in [tool.mypy] enable_error_code = ["deprecated"] My recommendation Use @deprecated with your own custom warning and test with pytest -W error Michael #3: How FOSS Won and Why It Matters by Thomas Depierre Companies are not cheap, companies optimize cost control. They do this by making purchasing slow and painful. FOSS is/was a major unlock hack to skip procurement, legal, etc. Example is months to start using a paid “Add to calendar” widget! It “works both ways”: the same bypass lowers the barrier for maintainers too, no need for a legal entity, lawyers, liability insurance, or sales motion. Proposals that “fix FOSS” by reintroducing supply-chain style controls (he name-checks SBOMs and mandated processes) risk being rejected or gamed, because they restore the very friction FOSS sidesteps. Brian #4: Should I be looking for a GitHub alternative? Pricing changes for GitHub Actions The self-hosted runner pricing change caused a kerfuffle. It's has been postponed But… if you were to look around, maybe pay attention to These 4 GitHub alternatives are just as good—or better Codeburg, BitBucket, GitLab, Gitea And a new-ish entry, Tangled Extras Brian: End of year sale for The Complete pytest Course Use code XMAS2025 for 50% off before Dec 31 Writing work on Lean TDD book on hold for holidays Will pick up again in January Michael: PyCharm has better Ruff support now out of the box, via Daniel Molnar This is from the release notes of 2025.3: "PyCharm 2025.3 expands its LSP integration with support for Ruff, ty, Pyright, and Pyrefly.” If you check out the LSP section it will land you on this page and you can go to Ruff. The Ruff doc site was also updated. Previously it was only available external tools and a third party plugin, this feels like a big step. Fun quote I saw on ExTwitter: May your bug tracker be forever empty. Joke: Try/Catch/Stack Overflow Create a super annoying linkedin profile - From Tim Kellogg, submitted by archtoad

Straight from re:Invent 2025, technology leaders from C3 AI, nCino, New Relic and Vercel reveal learnings, best practices and predictions for the future of Agentic AI.Topics Include:Four technology executives introduce their companies' AI innovations in fintech, cloud, enterprise software, and observability.Vercel built agents for code reviews, infrastructure optimization, and across finance, sales, and support functions.C3.ai deploys enterprise AI applications from scratch to production in six months for Fortune 500s.New Relic provides observability for AI systems and built agents that resolve infrastructure issues in real-time.Vercel's agents improve code quality by incorporating security and framework best practices into AI-generated output.C3.ai partnered with Department of Defense to autonomously produce mission-critical intelligence assessment reports from data.Industry shifted from copilots everywhere to agents that actually own outcomes and land the plane.New Relic moved beyond natural language translation to agents that execute actions and resolve issues autonomously.Panel debates whether Model Context Protocol or broader ecosystem approaches better enable agent interoperability and communication.Autonomy requires accountability: agent decisions must be explainable with traceable steps and replay capabilities built-in.Governance and security should be prerequisites for acceleration, not impediments—a critical mental model shift needed.Many enterprises struggle with process bottlenecks preventing them from harnessing high-quality agents despite having technology.Financial services must carefully balance where human discretion remains essential versus where agent autonomy justified.Will Jung envisions deeply continuous context enabling banks to deliver truly personalized insights without appearing creepy.Suraj Krishnan predicts agents will own outcomes by 2026, coordinating tools and other agents to achieve goals.Participants:Panelist: Merel Witteveen, SVP of Operations, C3.aiPanelist: Will Jung, Chief Technology Officer, nCinoPanelist: Suraj Krishnan, GVP of Engineering, New RelicPanelist: Aparna Sinha, Senior Vice President, Product, VercelModerator: Olawale Oladehin, Managing Director, NAMER Technology Segments (Enterprise, ISV, DNB, and Model Providers), Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Have you ever thought about getting your small product into production, but are worried about the cost of the big cloud providers? Or maybe you think your current cloud service is over-architected and costing you too much? Well, in this episode, we interview Michael Kennedy, author of "Talk Python in Production," a new book that guides you through deploying web apps at scale with right-sized engineering. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Christopher Trudeau - guest host: www.linkedin.com Michael's personal site: mkennedy.codes Talk Python in Production Book: talkpython.fm glances: github.com btop: github.com Uptimekuma: uptimekuma.org Coolify: coolify.io Talk Python Blog: talkpython.fm Hetzner (€20 credit with link): hetzner.cloud OpalStack: www.opalstack.com Bunny.net CDN: bunny.net Galleries from the book: github.com Pandoc: pandoc.org Docker: www.docker.com Watch this episode on YouTube: youtube.com Episode #531 deep-dive: talkpython.fm/531 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Nolan and Malini join Shaown Nandi, AWS Director of AGS Technology and Subhash Vanga, Director of Solutions Architecture. They recap re:Invent 2025 announcements and discuss how AI and new technology is continuing to drive individual and organizational change for everyone. Top re:Invent 2025 Announcementshttps://aws.amazon.com/blogs/aws/top-announcements-of-aws-reinvent-2025/AWS Hosts: Nolan Chen & Malini ChatterjeeEmail Your Feedback: rethinkpodcast@amazon.com

In this last episode of the special AI mini-series, we now explore the human side of transformation, where technology meets purpose and people remain at the center. From future jobs and critical thinking to working with C-level leaders, how human intervention and high-quality data drive success in an AI-powered world.This week Dave, Esmee , Rob sit down with Johanna Hutchinson, CDO at BAE systems about why data matters, the rise of Sovereign AI, and the skills shaping the intelligence age. TLDR00:55 Introduction of Johanna Hutchinson02:09 Explaining the State of AI mini-series with Craig06:01 Conversation with Johanna34:20 Weaving today's data tapestries with AI40:20 Going to a rave GuestJohanna Hutchinson: https://www.linkedin.com/in/johanna-hutchinson-95b95568/ HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/with co-host Craig Suckling: https://www.linkedin.com/in/craigsuckling/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini

Markus Will, heise-online-Chefredakteur Dr. Volker Zota und Malte Kirchner sprechen in dieser Ausgabe der #heiseshow unter anderem über folgende Themen: - Aus vom Aus: Haben Verbrenner doch eine Zukunft? – Das für 2035 geplante Aus für Verbrenner-Fahrzeuge ist gekippt – doch die Situation ist trotzdem kompliziert. Ökonomen warnen vor einer Aufweichung der Klimaziele. Was bedeutet das für die Automobilindustrie? Welche Rolle spielen E-Fuels und alternative Antriebe? Und hat der Verbrenner durch die aktuelle Entwicklung wirklich eine Überlebenschance? - Kein Betrug unter dieser Nummer: Telekom startet Abwehrsystem – Die Telekom hat ein neues System gegen Betrugsanrufe gestartet. Vodafone hat sowas schon länger. Wie funktioniert die Technik hinter dem Schutz vor gefälschten Rufnummern? Welche Erfolge lassen sich bereits verzeichnen? Und reicht das aus, um Verbraucher effektiv vor Telefonbetrug zu schützen? - Das war 2025: Unser Blick zurück auf das Tech-Jahr – Von KI-Durchbrüchen und Zöllen bis zu regulatorischen Kämpfen – 2025 war ein bewegtes Jahr in der Tech-Welt. Wir sprechen über unsere persönlichen Highlight-Themen des Jahres. Außerdem wieder mit dabei: ein Nerd-Geburtstag, das WTF der Woche und knifflige Quizfragen.

Four enterprise AI leaders from Box, Snorkel AI, Sumo Logic, and Talkdesk peel away the hype and share battle-tested strategies for implementing agentic AI at scale.Topics Include:Carol Potts introduces panel featuring AI leaders from Box, Snorkel AI, Sumo Logic, and TalkdeskDiego Dugatkin explains Box serves 120,000 enterprise customers with 1.5 exabytes of secure cloud contentKui Jia shares Sumo Logic processes petabytes daily across 10 AWS regions for intelligent operationsYunjing Ma describes Talkdesk's evolution from contact center to customer experience automation through agentic AIDennis Panos positions Snorkel AI as leader in embedding human knowledge into data-centric applicationsDiego reveals Box uses AI internally for faster development and externally for metadata extraction automationKui explains security teams face overwhelming volumes, sometimes 1,000 signals daily, many AI-generated attacksSumo Logic announces SOC analyst agent in customer beta and query agent in general availabilityYunjing details Talkdesk's multi-agent hierarchy architecture powered by unified TalkDesk Data Cloud platformFour key areas identified: discovery of opportunities, building knowledge-powered agents, optimization, and measurementDennis emphasizes starting with trusted data foundation before adding generative AI capabilities to avoid hallucinationsDiego stresses governance importance: AI guardrails plus traditional data security create comprehensive protection frameworkKui warns POC-to-production gap requires intentional design: different latency, accuracy, and security requirements at scaleYunjing shares customer success: 80,000 daily calls, 11,000 documents, 97% accuracy despite complex compliance rulesKey success factors include prompt engineering optimization and real-time data processing mechanism improvementsDiego advises learning AI tools end-to-end: from ideation through functional demos without traditional prototyping delaysDennis recommends robust evaluation frameworks across system components, similar to software unit testing approachesYunjing reinforces data processing optimization and governance remain essential alongside exciting agentic AI capabilitiesKui urges immediate action: technology evolves rapidly, perfect solutions don't exist, customer focus builds trustFinal advice centers on treating AI as digital teammate, not replacement, enhancing productivity and creativityPlatform partnerships like AWS Bedrock solve heavy lifting, allowing teams to focus on core differentiatorsParticipants:Diego Dugatkin - Chief Product Officer, BoxDennis Panos - Head of Enterprise AI, SnorkelAIKui Jia - VP AI Engineering, Sumo LogicYunjing Ma - VP of Engineering, AI, TalkdeskModerator: Carol Potts - General Manager, ISV Sales Segment, North America, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

In this episode of Hands-On IT, Landon Miles explores the history of servers and enterprise IT infrastructure, from early mainframe computers to cloud computing, Linux servers, virtualization, containers, and AI-driven data centers.This episode connects decades of server evolution into a clear, accessible story, focusing on the people, technologies, and ideas that shaped modern computing. From IBM's System/360 and minicomputers, to Unix and Linux, virtualization, cloud platforms like AWS and Azure, and container orchestration with Docker and Kubernetes, this episode explains how servers became the foundation of today's digital world.Topics covered include: • Server history and early computing systems • IBM mainframes and enterprise computing • Minicomputers and distributed computing • Unix, Linux, and open-source software • Virtualization and data center efficiency • Cloud computing and hyperscale infrastructure • Docker, Kubernetes, and cloud-native architecture • AI workloads, GPUs, and modern server hardwareLandon also highlights key figures in computing history, including Grace Hopper, Ken Olsen, Linus Torvalds, Dave Cutler, Diane Greene, and Jeff Bezos, and explains how their work still influences IT operations today.This episode is part of our December Best Of series, featuring some of our favorite moments and episodes from the past year.Originally aired March 20, 2025.

On November 19th, 2025, National College of Ireland in (NCI) collaboration with Citi proudly announced the official kick-off of the Citi upStart programme for the 2025/26 academic year. The initiative, designed to foster innovation and entrepreneurship among postgraduate students, saw Citi organisers, mentors, NCI students, academics, and new partners gather for the launch event. Activate mentorship This year's programme features 165 NCI postgraduate students who took part in a series of rigorous in-house idea-development workshops facilitated by NCI academic staff. This intensive process saw 60 students progress to team formation, advancing the most promising proposals which were then presented via elevator pitches at the event. Addressing participants and mentors, Dr Prag Sharma, Director, Future of Finance Think tank, former Global Head of AI CoE at Citi expressed his admiration for the nascent ideas, and provided crucial advice on AI's role: "AI is a tool for you to use, alongside the other tools you have acquired through college and your working life. AI augments our skills; so, become experts in using it to accelerate your capabilities." Following the pitches, a "speed dating" session allowed mentors from various Citi departments to connect with student teams, exploring project proposals and identifying alignment with their skills and insights. Dr Anu Sahni, Programme Director for the MSc in AI for Business, Data Analytics, and Knowledge Transfer Champion at National College of Ireland underscored the transformative power of mentorship: "Having the guidance and support of an experienced mentor can provide a mentee with a broad range of personal and professional benefits, including gaining practical advice and encouragement, as well being exposed to new ideas, and new ways of thinking, and now having another big organisation, Mphasis onboard to support this initiative, we will definitely see a remarkable amount of value added to an already innovative collaboration." New supports This year's cohort has already benefited from additional supports, including valuable insights into innovative solution development from Georgina Lupu Florian and Adrian Florian of Wolfpack Digital. Pritesh Tiwari, CEO of Data Science Wizards (itself a spin-out company from NCI MSc in Data Science), provided guidance on idea building and validation, while Swapnil Parashar, Director of Software Engineering at Oracle Cloud, shared industry perspectives on innovation. New partnership A?significant development for this year's programme is the new strategic partnership withMphasis, a global AI-led, platform-driven technology solutions provider. Mphasis will support participating student teams through project guidance and will sponsor awards and prizes for the winners at the upcoming Dragons' Den event. Rohit Jayachandran, Head of Banking & Financial Services at Mphasis, said: "Our long-standing partnership with Citi has opened the door to impactful collaborations, such as Dragons' Den. At Mphasis, we see immense potential in the next generation of technologists, and working with Citi upStart allows us to nurture that potential and fuel innovation for the future. Additionally, Mphasis' philosophy, "AI Without Intelligence Is Artificial", aligns perfectly with the programme's focus on intelligent application of technology." The ten participating teams, comprised of master's students in Cloud Computing, Data Analytics, AI, AI for Business, Fintech, or Cybersecurity, are developing a diverse range of impactful ideas. These include "Finpals," an AI-driven solution for automating credit risk analysis; "Lendloop," a peer-to-peer lending platform; "Medinova AI" and "Medtrix," both focused on enhancing healthcare access and patient support; "Phantom," an all-in-one Irish tourism app; and "Venture Forge," which aims to innovate within the Carbon Credits Market using blockchain technology. You can read more about the teams and their projects here on the NCI we...

Topics covered in this episode: Deprecations via warnings docs PyAtlas: interactive map of the top 10,000 Python packages on PyPI. Buckaroo Extras Joke Watch on YouTube About the show Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Deprecations via warnings Deprecations via warnings don't work for Python libraries Seth Larson How to encourage developers to fix Python warnings for deprecated features Ines Panker Michael #2: docs A collaborative note taking, wiki and documentation platform that scales. Built with Django and React. Made for self hosting Docs is the result of a joint effort led by the French

Deovrat Kajwadkar is the Director of Strategic Deal Pricing and Monetization at Google Cloud, where he sits at the center of some of the most complex commercial decisions in modern tech. With a background in management consulting at McKinsey and deep experience in cloud and AI monetization, Deovrat brings a rare inside view of how pricing actually works when products are platforms, costs are dynamic, and value is constantly evolving. In this conversation, Deovrat and Mark Stiving unpack why pricing is not just a "number-setting" function but the grade of how well everything else in the business is working. They explore the difference between platforms and solutions, why value-based pricing becomes harder as offerings become more flexible, and how AI is changing both how pricing is done and what pricing even means.   Why You Have to Check Out Today's Podcast: Learn why pricing sits at the heart of cloud and AI economics, touching product, strategy, sales, and profitability all at once. Understand how platforms, solutions, and AI fundamentally change value-based pricing, and why cost, competition, and outcomes all matter—at different layers of the stack. Discover why "pulling the dollar lever" is the most expensive move, and what smarter pricing leaders focus on first.   "Pulling the dollar lever is easy—but it's also very expensive. I'd rather pull every other lever first." — Deovrat Kajwadkar   Topics Covered: 01:40 – Cloud Pricing as a Central Role. Deovrat explains why pricing sits at the center of Google Cloud's commercial decisions—connecting product strategy, growth, profitability, and customer value. 05:09 – Cloud Computing for Enterprises. A clear, non-technical explanation of cloud computing for enterprise customers, from infrastructure and platforms to software and AI—and why pricing each layer is different. 08:48 – Value-Based Pricing Challenges. Mark and Deovrat discuss why value-based pricing is especially difficult for platforms, where customers use the same products in very different ways. 13:04 – Value-Based Pricing Strategies. A practical framework for pricing across the cloud stack: cost- and competition-based pricing at the lower layers, and outcome-driven pricing as offerings move closer to customer solutions. 18:10 – AI's Impact on Pricing Strategies. How AI is changing pricing on multiple fronts—what gets priced, how costs behave, and how quickly products and value propositions evolve. 22:34 – AI in Pricing Strategies. Deovrat breaks down how AI can support pricing decisions, from customer analysis and renewals to analytics and decision support—while stressing the importance of clean data foundations. 24:12 – AI Value Delivery Challenges. Why delivering real AI value is harder than building the technology itself, and how change management and business adoption affect pricing and monetization. 27:30 – Pricing Advice for Business Impact. Deovrat's closing advice: great pricing leaders expand their skill set beyond pricing fundamentals—and pull every lever before resorting to raising prices.   Key Takeaways: "Pricing touches almost everything—it's the heart of a company's economics." — Deovrat Kajwadkar "The more commoditized the offering, the more cost and competition matter." — Deovrat Kajwadkar "As you move closer to business outcomes, value-based pricing becomes possible—but harder." — Deovrat Kajwadkar "AI changes pricing, but it doesn't eliminate the fundamentals." — Deovrat Kajwadkar   People / Resources Mentioned: Google Cloud – Cloud platform spanning infrastructure, AI models, developer tools, and industry solutions. McKinsey & Company – Deovrat's consulting background, shaping his strategic view of pricing and technology. AI Models & Agentic Workflows – Referenced in the context of pricing analytics, automation, and decision support.   Connect with Deovrat Kajwadkar: LinkedIn: https://www.linkedin.com/in/deovrat-kajwadkar   Connect with Mark Stiving: LinkedIn: https://www.linkedin.com/in/stiving/ Email: mark@impactpricing.com  

For years, building interactive widgets in Python notebooks meant wrestling with toolchains, platform quirks, and a mountain of JavaScript machinery. Most developers took one look and backed away slowly. Trevor Manz decided that barrier did not need to exist. His idea was simple: give Python users just enough JavaScript to unlock the web's interactivity, without dragging along the rest of the web ecosystem. That idea became anywidget, and it is quickly becoming the quiet connective tissue of modern interactive computing. Today we dig into how it works, why it has taken off, and how it might change the way we explore data. Episode sponsors Seer: AI Debugging, Code TALKPYTHON PyCharm, code STRONGER PYTHON Talk Python Courses Links from the show Trevor on GitHub: github.com anywidget GitHub: github.com Trevor's SciPy 2024 Talk: www.youtube.com Marimo GitHub: github.com Myst (Markdown docs): mystmd.org Altair: altair-viz.github.io DuckDB: duckdb.org Mosaic: uwdata.github.io ipywidgets: ipywidgets.readthedocs.io Tension between Web and Data Sci Graphic: blobs.talkpython.fm Quak: github.com Walk through building a widget: anywidget.dev Widget Gallery: anywidget.dev Video: How do I anywidget?: www.youtube.com PyCharm + PSF Fundraiser: pycharm-psf-2025 code STRONGER PYTHON Watch this episode on YouTube: youtube.com Episode #530 deep-dive: talkpython.fm/530 Episode transcripts: talkpython.fm Theme Song: Developer Rap

AI is transforming software development—redefining roles, creativity, and community, while challenging developers to embrace ambiguity, orchestrate specialized agents, and stay human through empathy and curiosity. Will AI make developers more creative, or will we forget how the machine really works under the hood?This week Dave, Esmee , Rob sit down with Scott Hanselman, VP Developer Community at Microsoft for a wildly energetic, deeply human, and brilliantly practical conversation about how AI is reshaping software development and what that means for creativity, careers, and all industries. TLDR00:30 – Scott Hanselman introduced as a special guest from Microsoft Ignite 2025.02:16 – Scott discusses how AI is fundamentally redesigning all industries.09:50 – Don't anthropomorphize AI, I want the computer from Star Trek!15:30 – Delegation: contrasting the roles of humans and agents.18:30 – The importance of supporting early career growth and learning.26:30 – Why specificity matters in AI and coding.35:30 – Making AI delightful and fun.45:30 – Always put humans first in AI development.46:00 – Each morning I think about lunch. GuestScott Hanselman: https://www.hanselman.com/The Hanselminutes Podcast: https://www.hanselman.com/podcasts with over 1025 podcasts! HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini

AI is fueling a boom in data centers, and the world's biggest hyperscalers are pouring billions into building up their capacity.  But risks of an AI bubble and circular deals involving companies like OpenAI and Microsoft are worrying investors. Learn more about data center growth in 2026 and other sector outlooks: moodys.com/outlooks Host: Paloma San Valentin, Managing Director, North America Corporate Finance, Moody's Ratings  Guests: John Medina, Senior Vice President, Moody's Ratings; Raj Joshi, Senior Vice President, Moody's Ratings Related Research: Artificial Intelligence – Global - 2026 Outlook - Risks are rising in a shifting AI landscape 08 Dec 2025Artificial Intelligence - Global - OpenAI's huge footprint is a risk for the AI value chain 05 Dec 2025Data Centers – US - Broadening array of financing approaches attract new capital as data centers scale up 03 Dec 2025  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this year-end episode, William and Eyvonne recap their experiences at AutoCon 4 in Austin, Texas. They discuss the conference’s new multi-track format, including Eyvonne’s presentation in the leadership track on why technical projects fail. The conversation dives into how AI tools like Google Gemini can augment – not replace – human creativity, from research... Read more »

Rubrik's GM of AI Dev Rishi, explains how 85% of enterprises are building agentic AI but lack frameworks to govern agents with production system access - and how Rubrik solves this gap!Topics Include:Dev Rishi explains Rubrik's evolution from data backup to cyber resilience company.Rubrik shifted focus after 2018 when ransomware became the primary business continuity threat.Recent investments center on AI features and security for enterprise data infrastructure.Rubrik's foundation understands organizational data, metadata, and identity access across all systems.Predabase acquisition brought generative AI and LLM platform capabilities into Rubrik's infrastructure.Rubrik Agent Cloud launched to address enterprise AI security and governance needs.180 enterprise conversations revealed AI risk frameworks block ROI, not technology challenges.Agents enable 10x productivity but create 10x damage potential in shorter timeframes.Most organizations struggle enforcing AI policies across AWS Bedrock, OpenAI, and third-party platforms.Agent Undo feature recovers from destructive AI actions using healthy backup snapshots.Three pillars for AI security: define policies, enforce across platforms, enable recovery.2026 will see enterprises shift from pilot agents to managing dozens in production.Participants:Dev Rishi – General Manager of AI, RubrikConnect with Rubrik and learn more here: https://www.rubrik.com/lp/events-hubSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Topics covered in this episode: PEP 798: Unpacking in Comprehensions Pandas 3.0.0rc0 typos A couple testing topics Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: PEP 798: Unpacking in Comprehensions After careful deliberation, the Python Steering Council is pleased to accept PEP 798 – Unpacking in Comprehensions. Examples [*it for it in its] # list with the concatenation of iterables in 'its' {*it for it in its} # set with the union of iterables in 'its' {**d for d in dicts} # dict with the combination of dicts in 'dicts' (*it for it in its) # generator of the concatenation of iterables in 'its' Also: The Steering Council is happy to unanimously accept “PEP 810, Explicit lazy imports” Brian #2: Pandas 3.0.0rc0 Pandas 3.0.0 will be released soon, and we're on Release candidate 0 Here's What's new in Pands 3.0.0 Dedicated string data type by default Inferred by default for string data (instead of object dtype) The str dtype can only hold strings (or missing values), in contrast to object dtype. (setitem with non string fails) The missing value sentinel is always NaN (np.nan) and follows the same missing value semantics as the other default dtypes. Copy-on-Write The result of any indexing operation (subsetting a DataFrame or Series in any way, i.e. including accessing a DataFrame column as a Series) or any method returning a new DataFrame or Series, always behaves as if it were a copy in terms of user API. As a consequence, if you want to modify an object (DataFrame or Series), the only way to do this is to directly modify that object itself. pd.col syntax can now be used in DataFrame.assign() and DataFrame.loc() You can now do this: df.assign(c = pd.col('a') + pd.col('b')) New Deprecation Policy Plus more - Michael #3: typos You've heard about codespell … what about typos? VSCode extension and OpenVSX extension. From Sky Kasko: Like codespell, typos checks for known misspellings instead of only allowing words from a dictionary. But typos has some extra features I really appreciate, like finding spelling mistakes inside snake_case or camelCase words. For example, if you have the line: *connecton_string = "sqlite:///my.db"* codespell won't find the misspelling, but typos will. It gave me the output: *error: `connecton` should be `connection`, `connector` ╭▸ ./main.py:1:1 │1 │ connecton_string = "sqlite:///my.db" ╰╴━━━━━━━━━* But the main advantage for me is that typos has an LSP that supports editor integrations like a VS Code extension. As far as I can tell, codespell doesn't support editor integration. (Note that the popular Code Spell Checker VS Code extension is an unrelated project that uses a traditional dictionary approach.) For more on the differences between codespell and typos, here's a comparison table I found in the typos repo: https://github.com/crate-ci/typos/blob/master/docs/comparison.md By the way, though it's not mentioned in the installation instructions, typos is published on PyPI and can be installed with uv tool install typos, for example. That said, I don't bother installing it, I just use the VS Code extension and run it as a pre-commit hook. (By the way, I'm using prek instead of pre-commit now; thanks for the tip on episode #448!) It looks like typos also publishes a GitHub action, though I haven't used it. Brian #4: A couple testing topics slowlify suggested by Brian Skinn Simulate slow, overloaded, or resource-constrained machines to reproduce CI failures and hunt flaky tests. Requires Linux with cgroups v2 Why your mock breaks later Ned Badthelder Ned's taught us before to “Mock where the object is used, not where it's defined.” To be more explicit, but probably more confusing to mock-newbies, “don't mock things that get imported, mock the object in the file it got imported to.” See? That's probably worse. Anyway, read Ned's post. If my project myproduct has user.py that uses the system builtin open() and we want to patch it: DONT DO THIS: @patch("builtins.open") This patches open() for the whole system DO THIS: @patch("myproduct.user.open") This patches open() for just the user.py file, which is what we want Apparently this issue is common and is mucking up using coverage.py Extras Brian: The Rise and Rise of FastAPI - mini documentary “Building on Lean” chapter of LeanTDD is out The next chapter I'm working on is “Finding Waste in TDD” Notes to delete before end of show: I'm not on track for an end of year completion of the first pass, so pushing goal to 1/31/26 As requested by a reader, I'm releasing both the full-so-far versions and most-recent-chapter Michael: My Vanishing Gradient's episode is out Django 6 is out Joke: tabloid - A minimal programming language inspired by clickbait headlines

Matt Yanchyshyn, AWS Marketplace and Partner Services VP, reveals how AI agents are transforming enterprises worldwide while Atlassian and Netskope leaders share strategies for scaling up Agentic AI marketplace deals.Topics Include:Matt Yanchyshyn of AWS opens with massive shift to multi-agent production systemsEnterprise software seeing huge AI adoption: 33% will include AI by year endAutomated agents now handle Matt's daily workflow, prioritizing emails and messages autonomouslyReal business transformation across financial reporting, demand forecasting, and automated incident managementAWS Marketplace team productivity up 31%, deploying software 27% faster with agentsNew agent mode for Marketplace uses autonomous data collection improving customer experiencesSuccess requires proper data governance with fine-grained access controls for safe operationsQ Developer and Qiro CLI integrate seamlessly into developer workflows without disruptionAWS maintains 400+ MCP servers, shared spec farms enabling teams to collaborate effectivelyEmbedded experts and principal engineers spread agent knowledge and measure productivity closelyAndy Horwitz notes security leads Marketplace growth, primarily through private offer expansionNetskope's new DSPM product addresses AI data security, driving strong customer adoption momentumEnterprise customers now ask if vendors are AWS badged, deals 41-58% largerAndy advises ISVs: prepare sales teams thoroughly, focus co-sell, secure executive buy-inBill Hustad emphasizes distinct marketplace strategy, seller training, and ruthless operational tracking for successParticipants:Bill Hustad - Global Head of Channel and GTM Ecosystems, AtlassianAndy Horwitz – SVP, Global Partner Ecosystems, NetskopeMatt Yanchyshyn – VP, AWS Marketplace & Partner Services, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Live from the iconic Venetian in Las Vegas, we're rolling out an exclusive mini-series dedicated to AWS re:Invent 2025!Tune in as we sit down with AWS visionaries and take the pulse of the industry on everything shaping the future, Cloud innovation, GenAI, Agents, and the hottest trends making waves.And because what happens in Vegas doesn't always stay in Vegas, we'll spill the latest news, insider buzz, and a little Strip-side gossip to keep things spicy. Dave, Esmee, and Rob continue their discussion with Scott Mullins, MD Financial Services at AWS, on how the sector is rapidly embracing cloud, AI, automation, and real-time data to drive agility and stay compliant. TLDR00:30 – Meet Scott Mullins and hear about his re:Invent experience05:00 – Deep dive conversation with Scott25:56 – Fiiction with The Jetsons GuestScott Mullins: https://www.linkedin.com/in/escottmullins/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini

Live from the iconic Venetian in Las Vegas, we're rolling out an exclusive mini-series dedicated to AWS re:Invent 2025!Tune in as we sit down with AWS visionaries and take the pulse of the industry on everything shaping the future, Cloud innovation, GenAI, Agents, and the hottest trends making waves.And because what happens in Vegas doesn't always stay in Vegas, we'll spill the latest news, insider buzz, and a little Strip-side gossip to keep things spicy. Dave, Esmee, and Rob wrap up their final AWS re:Invent 2025 conversation with Mustafa Isik, Chief Technologist for Sovereignty at AWS, discussing digital sovereignty and its growing regional importance. They close the event with reflections from Matthew Gillard, co-founder of Cuidado Connect and co-host of Cloud Dialogues, along with insights from the team. TLDR01:29 – Meet Mustafa Isik and hear his keynote highlights04:05 – In-depth discussion with Mustafa31:35 – Exploring the line between science fiction and science fact36:26 – Introduction to Matthew Gillard38:55 – Matt shares his re:Invent reflections from a developer's perspective52:12 – The team looks back on re:Invent 20251:00:02 – The team's take on science fiction versus science fact GuestsMustafa Isik: https://www.linkedin.com/in/codesurgeon/Matt Gillard: https://www.linkedin.com/in/mattgillard/ https://cloud-dialogues.com/HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini

Raviteja Yelamanchili shares how Scale AI transformed banking cycles from one year to real-time and why your most valuable enterprise data isn't being collected.Topics Include:Scale evolved from data annotations company to enterprise AI solutions providerHealthcare system transformed patient transcriptions into value using reinforcement learning researchBlank slate customer problems allow Scale to experiment with latest methodsMany customers propose solutions before explaining their actual underlying business problemsBiggest AI misconception: technology will replace jobs rather than augment productivityDon't wait for perfect AI—start learning through iteration and evolution nowBanking credit cycle transformed from one-year process to real-time strategic insightsScale deploys flexibly across EC2, EKS, or Bedrock based on customer requirementsEnterprises want business value generation more than academic research papers aloneNext 12-24 months focus: making data consumable and leveraging unused datasetsTribal knowledge from experienced SMEs represents most valuable yet uncollected dataAgent-based learning captures expertise through feedback loops on Scale's SGP platformParticipants:Raviteja Yelamanchili - Head of Solution Engineering, Scale AISee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Join FPC Executive Director and CEO Reed Luhtanen as he goes off the rails with Craig Ramsey of ACI Worldwide. Reed and Craig spend time separating the noise in the market from the things that are really moving the needle, and they talk about the upcoming final race of the Formula 1 season. 

Live from the iconic Venetian in Las Vegas, we're rolling out an exclusive mini-series dedicated to AWS re:Invent 2025!Tune in as we sit down with AWS visionaries and take the pulse of the industry on everything shaping the future, Cloud innovation, GenAI, Agents, and the hottest trends making waves.And because what happens in Vegas doesn't always stay in Vegas, we'll spill the latest news, insider buzz, and a little Strip-side gossip to keep things spicy. Dave, Esmee, and Rob kick off their conversation with Tanuja Randery, Managing Director for Europe, the Middle East & Africa (EMEA), diving into cloud innovation and the call to re:Accelerate Europe. TLDR00:49 – Introduction to Tanuja Randery03:29 – Keynote highlights with Tanuja and a deep-dive conversation31:00 – Imaginary tech and Star Trek GuestTanuja Randery: https://www.linkedin.com/in/tanuja-randery/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini

Live from the iconic Venetian in Las Vegas, we're rolling out an exclusive mini-series dedicated to AWS re:Invent 2025!Tune in as we sit down with AWS visionaries and take the pulse of the industry on everything shaping the future, Cloud innovation, GenAI, Agents, and the hottest trends making waves.And because what happens in Vegas doesn't always stay in Vegas, we'll spill the latest news, insider buzz, and a little Strip-side gossip to keep things spicy.Dave, Esmee, and Rob bring a double-feature conversation on industry innovation—first with Rob Boetticher, Global Technology Leader for Automotive and Manufacturing, followed by Howard Gefen, GM of the Energy and Utilities Industry Business Unit at AWS. TLDR00:42 – Rob Boetticher & Howard Gefen introduced02:00 – Rob's keynote highlights07:52 –  The future of automotive innovation with Rob23:32 – Tech fiction examples25:59 – Howard Gefen introduced28:00 – Howard's keynote highlights31:04 – Howard on the future of Energy and Utilities50:14 – Tech fiction examples GuestRob Boetticher: https://www.linkedin.com/in/robert-boetticher/Howard Gefen: https://www.linkedin.com/in/hgefen/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini

A lot of people building software today never took the traditional CS path. They arrived through curiosity, a job that needed automating, or a late-night itch to make something work. This week, David Kopec joins me to talk about rebuilding computer science for exactly those folks, the ones who learned to program first and are now ready to understand the deeper ideas that power the tools they use every day. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON NordStellar Talk Python Courses Links from the show David Kopec: davekopec.com Classic Computer Science Book: amazon.com Computer Science from Scratch Book: computersciencefromscratch.com Computer Science from Scratch at NoStartch (CSFS30 for 30% off): nostarch.com Watch this episode on YouTube: youtube.com Episode #529 deep-dive: talkpython.fm/529 Episode transcripts: talkpython.fm Theme Song: Developer Rap

In this sponsored episode recorded live at AutoCon 4 in Austin, we sit down with Peter Sprygada, Chief Architect at Itential, to discuss Itential’s on-stage announcement of FlowAI. Peter shares his journey from network engineering skeptic to AI advocate, explaining how Itential securely connects AI agents to infrastructure with enterprise-grade governance and traceability. We dive... Read more »

Live from the iconic Venetian in Las Vegas, we're rolling out an exclusive mini-series dedicated to AWS re:Invent 2025!Tune in as we sit down with AWS visionaries and take the pulse of the industry on everything shaping the future, Cloud innovation, GenAI, Agents, and the hottest trends making waves.And because what happens in Vegas doesn't always stay in Vegas, we'll spill the latest news, insider buzz, and a little Strip-side gossip to keep things spicy. Dave, Esmee, and Rob continue their conversation with Tim Murnin, Head of Industry & Partner Strategy at AWS, exploring the evolving role of the CIO, adoption delays, and how trends vary across different sectors. TLDR00:36 – Welcome back with Tim Murnin and the team's highlights from the AWS re:Invent 2025 keynote08:04 – In-depth conversation with Tim, exploring key insights32:05 – Where fact meets fiction, including a look at the flying carGuestTim Murnin: https://www.linkedin.com/in/timmurnin/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini

Live from the iconic Venetian in Las Vegas, we're rolling out an exclusive mini-series dedicated to AWS re:Invent 2025!Tune in as we sit down with AWS visionaries and take the pulse of the industry on everything shaping the future, Cloud innovation, GenAI, Agents, and the hottest trends making waves. And because what happens in Vegas doesn't always stay in Vegas, we'll spill the latest news, insider buzz, and a little Strip-side gossip to keep things spicy. Dave, Esmee, and Rob start their conversation with Chandra Pinapala, Director Global Strategic Partners, to explore why strong partnerships are essential for success in Cloud and AI. TLDR00:40 – Back in Las Vegas with highlights from the AWS re:Invent 2025 keynote12:07 – Meet Chandra Pinapala and dive deep into the conversation35:10 – A playful leap into the world of fiction GuestChandra Pinapala: https://www.linkedin.com/in/chandrapinapala/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini

In a keynote address from re:Invent, McKinsey & Company's Lareina Yee shares fascinating data, trends and best practices on AI adoption, the future of skillsets, and leadership insights that are needed for AI transformation at scale.Topics Include:Over 80% of companies have adopted AI in at least one business function currently.Despite heavy investment, 62% of companies remain in experimental or pilot phases with AI.Only 7% of organizations have achieved full-scale AI implementation, up from 2% earlier this year.Agentic AI has proliferated rapidly across functions from knowledge management to manufacturing in one year.Between 45% and 5% of companies have implemented AI agents across different business functions today.AI's productivity potential represents $4.4 trillion in economic value beyond just cost savings opportunities.Innovation ranks as the number one goal for AI investments, ahead of cost reduction priorities.Employee satisfaction, customer satisfaction, and competitive differentiation drive AI adoption alongside revenue growth and cost.High AI performers view implementation as total enterprise transformation, not just technology deployment projects.Leading companies spend 4.9 times more budget on AI investments compared to average performing organizations.Traditional software stacks evolved to SaaS, now transforming into AI-ready tech stacks within one generation.Job outlook remains mixed: 32% expect losses, 13% expect increases, 43% see no major change.Since 2023, significant skill shifts show increased demand for software development and business intelligence capabilities.AI fluency has increased seven times as the most sought-after skill across all job types.AI fluency means using AI in everyday work, not building models or creating large language models.Skills like driving records, coaching, customer service, and management remain harder to automate with current AI.Transactional, data-driven repetitive tasks like inventory management and invoicing face highest automation exposure currently.Historical technology revolutions like electricity created six to eight jobs for every one job displaced.New roles like prompt engineering emerge, requiring skills like effective questioning rather than technical coding.Participants:Lareina Yee - Director of Technology Research, McKinsey & CompanySee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Topics covered in this episode: Advent of Code starts today Django 6 is coming Advanced, Overlooked Python Typing codespell Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Advent of Code starts today A few changes, like 12 days this year, which honestly, I'm grateful for. See also: elf: Advent of Code CLI helper for Python Michael #2: Django 6 is coming Expected December 2025 Django 6.0 supports Python 3.12, 3.13, and 3.14 Built-in support for the Content Security Policy (CSP) standard is now available, making it easier to protect web applications against content injection attacks such as cross-site scripting (XSS). The Django Template Language now supports template partials, making it easier to encapsulate and reuse small named fragments within a template file. Django now includes a built-in Tasks framework for running code outside the HTTP request–response cycle. This enables offloading work, such as sending emails or processing data, to background workers. Email handling in Django now uses Python's modern email API, introduced in Python 3.6. This API, centered around the email.message.EmailMessage class Brian #3: Advanced, Overlooked Python Typing get_args, TypeGuard, TypeIs, and more goodies Michael #4: codespell Learned from this PR for the Talk Python book. Fix common misspellings in text files. It's designed primarily for checking misspelled words in source code (backslash escapes are skipped), but it can be used with other files as well. It does not check for word membership in a complete dictionary, but instead looks for a set of common misspellings. Therefore it should catch errors like "adn", but it will not catch "adnasdfasdf". It shouldn't generate false-positives when you use a niche term it doesn't know about. Extras Brian: Is mkdocs maintained? Hatch 1.16 Michael: Follow up on tach from Gerben Dekker: tach has been unmaintained for a bit but is not anymore. It was the main product from Gauge which is a Y combinator startup that pivoted to something unrelated and abandoned tach. However, https://github.com/DetachHead forked it but now got access to the main repo and has committed to maintaining it. ruff analyze graph is fully independent of tach - we actually started to look into alternatives for tach when it became unmaintained and then found ruff analyze graph. For our use case, with just a bit of manipulation on top of ruff analyze graph we replaced our use of deptry (which was slower - and I try to be careful depending on one-man projects). A Review of Michael Kennedy's book, “Talk Python in Production” - Thanks Doug Joke: NoaaS

AWS Principal Solutions Architect Wallace Printz explains how agents are reshaping SaaS business models, pricing strategies, and technical architectures.Topics Include:Wallace Printz discusses agentic workloads transforming SaaS with largest AWS customersNew interaction models include generative UI, voice agents, and proactive workAgents extending SaaS products to interact with external systems and businessesVirtual teammates enabling cross-department collaboration and upskilling non-expert users effectivelyMonetization strategies evolving as predictable costs become variable with agentsThree patterns: dedicated agents, shared agents, and multi-tenant personalized agentsMulti-tenant agents enable hyper-personalized experiences using individual tenant context enrichmentAgent-centric business strategy requires real assessment beyond AI hype cycleAgent orchestration complexity grows with multiple specialized agents interacting togetherTenant isolation requires JWT tokens and AWS Bedrock Agent Core identityCost-per-tenant management needs LLM throttling, tiering, and unified control planeMulti-tenancy creates sticky personalized experiences; AWS white paper releasing soonParticipants:Wallace Printz - Principal Solution Architect, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

In this episode, I'm talking with Vincent Warmerdam about treating LLMs as just another API in your Python app, with clear boundaries, small focused endpoints, and good monitoring. We'll dig into patterns for wrapping these calls, caching and inspecting responses, and deciding where an LLM API actually earns its keep in your architecture. Episode sponsors Seer: AI Debugging, Code TALKPYTHON NordStellar Talk Python Courses Links from the show Vincent on X: @fishnets88 Vincent on Mastodon: @koaning LLM Building Blocks for Python Co-urse: training.talkpython.fm Top Talk Python Episodes of 2024: talkpython.fm LLM Usage - Datasette: llm.datasette.io DiskCache - Disk Backed Cache (Documentation): grantjenks.com smartfunc - Turn docstrings into LLM-functions: github.com Ollama: ollama.com LM Studio - Local AI: lmstudio.ai marimo - A Next-Generation Python Notebook: marimo.io Pydantic: pydantic.dev Instructor - Complex Schemas & Validation (Python): python.useinstructor.com Diving into PydanticAI with marimo: youtube.com Cline - AI Coding Agent: cline.bot OpenRouter - The Unified Interface For LLMs: openrouter.ai Leafcloud: leaf.cloud OpenAI looks for its "Google Chrome" moment with new Atlas web browser: arstechnica.com Watch this episode on YouTube: youtube.com Episode #528 deep-dive: talkpython.fm/528 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Industry leaders from Boomi, Demandbase and Smarsh share hard-won lessons on balancing AI creativity with guardrails, why data quality trumps frameworks, and deploying AI at scale.Topics Include:Three industry leaders share experiences building AI solutions at Boomi, Demandbase, and Smarsh.Smarsh manages trillion communications for financial services, detecting bad actors across multiple channels.Boomi built agent studio, garden, and control tower while spawning 33,000 internal agents.Chris Timmerman used vibe coding to build embeddable Boomi in five months solo.Companies balance creativity with guardrails, starting with IT policies before unleashing innovation.Internal adoption driven by empowering teams to build their own solutions versus top-down.Demandbase saw 70% adoption within six months through grassroots approach and local champions.Measuring success proves challenging, comparable to tracking Excel usage rather than specific KPIs.Companies focus on outcomes like touch-free bug fixes and support metrics versus raw usage.Biggest lesson: Data quality and context determine success more than agentic frameworks.Need scaling framework from low-risk UX improvements to high-risk automation with appropriate guardrails.Industry created fatigue by overpromising; should have started smaller with realistic expectations.Participants:Chris Timmerman – Vice President, Global Services Delivery, BoomiHarshal Dedhia – Vice President of AI, DemandbaseBrandon Carl - Executive Vice President of AI and Product Strategy, SmarshAllison Johnson - AMER Technology Partnerships Leader, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Recorded live at AutoCon4, William Collins and Eyvonne Sharp join forces with John Capobianco for some in the moment thoughts and reflections on the AutoCon experience – from the in-person connections to the workshops to the stage presentations.  John gives us the inside story on his very own workshop and the latest version releases in... Read more »

Topics covered in this episode: PEP 814 – Add frozendict built-in type From Material for MkDocs to Zensical Tach Some Python Speedups in 3.15 and 3.16 Extras Joke About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #0: Black Friday is on at Talk Python What's on offer: An AI course mini bundle (22% off) 20% off our entire library via the Everything Bundle (what's that? ;) ) The new Talk Python in Production book (25% off) Brian: This is peer pressure in action 20% off The Complete pytest Course bundle (use code BLACKFRIDAY) through November or use save50 for 50% off, your choice. Python Testing with pytest, 2nd edition, eBook (50% off with code save50) also through November I would have picked 20%, but it's a PragProg wide thing Michael #1: PEP 814 – Add frozendict built-in type by Victor Stinner & Donghee Na A new public immutable type frozendict is added to the builtins module. We expect frozendict to be safe by design, as it prevents any unintended modifications. This addition benefits not only CPython's standard library, but also third-party maintainers who can take advantage of a reliable, immutable dictionary type. To add to existing frozen types in Python. Brian #2: From Material for MkDocs to Zensical Suggested by John Hagen A lot of people, me included, use Material for MkDocs as our MkDocs theme for both personal and professional projects, and in-house docs. This plugin for MkDocs is now in maintenance mode The development team is switching to working on Zensical, a static site generator to overcome some technical limitations with MkDocs. There's a series of posts about the transition and reasoning Transforming Material for MkDocs Zensical – A modern static site generator built by the creators of Material for MkDocs Material for MkDocs Insiders – Now free for everyone Goodbye, GitHub Discussions Material for MkDocs still around, but in maintenance mode all insider features now available to everyone Zensical is / will be compatible with Material for Mkdocs, can natively read mkdocs.yml, to assist with the transition Open Source, MIT license funded by an offering for professional users: Zensical Spark Michael #3: Tach Keep the streak: pip deps with uv + tach From Gerben Decker We needed some more control over linting our dependency structure, both internal and external. We use tach (which you covered before IIRC), but also some home built linting rules for our specific structure. These are extremely easy to build using an underused feature of ruff: "uv run ruff analyze graph --python python_exe_path .". Example from an app I'm working on (shhhhh not yet announced!) Brian #4: Some Python Speedups in 3.15 and 3.16 A Plan for 5-10%* Faster Free-Threaded JIT by Python 3.16 5% faster by 3.15 and 10% faster by 3.16 Decompression is up to 30% faster in CPython 3.15 Extras Brian: LeanTDD book issue tracker Michael: No. 4 for dependencies: Inverted dep trees from Bob Belderbos Joke: git pull inception

AI Revolution, Cloud Growth, and the Virtual Cell. Brandon Weichert reports on how AI is driving massive growth in cloud computing, exemplified by Amazon's surging shares and AWS growth, reaching paces "we haven't seen since 2022." Weichert dismisses fears of an "AI crash" as fear-mongering rooted in ignorance and past market bubbles, arguing that AI is sparking new sectors and enhancing productivity across industries. He details the cutting-edge application of AI in creating a "virtual cell"—computer models that simulate cell functions to speed up drug discovery, understand disease mechanisms, and inform scientific investigation. 1951