Podcasts about Cloud computing

AI is no longer just consuming information, it is reshaping the economics and infrastructure of the internet itself. The challenge now is ensuring that the creators and custodians of trusted data can continue to exist in a world increasingly dominated by machines.This week, Dave and Rob are joined by Stephen Follows, film data analyst, author, publisher and researcher to explore how AI systems are fundamentally changing the economics, architecture and future of the web and why it should worry us all. TLDR00:20 – Introduction to today's topic: AI agents, web scraping and the changing internet01:40 – Hang out: Rob's confusioned by the always-on AI assistants07:55 – Dig in: Privacy, convenience and the growing tension between AI assistance and personal data collection11:55 – Conversation with Stephen Follows about what happened to the film industry website The Numbers45:16 – Is Tom Cruise really taller on screen and favourite movies discussion GuestStephen Follows: https://www.linkedin.com/in/stephenfollows/https://stephenfollows.com/HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/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/ 'Realities Remixed' is an original podcast from Capgemini

From data-center chaos to billion-dollar acquisitions: the real story behind Clio's cloud journey, compliance battles, and rapid AI-driven transformation.Topics Include:AWS-Clio partnership: migrate, modernize, add AI, then co-sellLegal industry ran on WordPerfect, mainframes, and homemade billingClio launched 2008, same year as AWS's first databaseNow serves 400,000+ legal professionals across 130 countriesLanded legal tech's largest-ever acquisition, raised $500M Series GShips code 50-100 times daily in a regulated industryStarted split across a data center, Azure, AWS, some GCPNine years of acquisitions, fundraising, and rapid team growthSharded databases, added regions for compliance and low latencyEngineering team grew from 40 to over 650 peopleLawyers once feared cloud security and data ownership questionsThree principles: data security, system resilience, data regionalityStage one: survival, learning EC2, RDS, S3 basicsStage two: earning trust through SOC 2, PCI complianceAWS became a compliance partner, not just a hostStage three: AI reshapes coding speed and company cultureIntegrating acquisitions scattered across Heroku, GCP, Azure, othersVLUX deal added a billion-document legal case-law databaseRapid acquisition-to-launch playbook: some products shipped in daysStrategy: avoid single AI vendor, preserve maximum optionalityParticipants:Jonathan Watson – Chief Technology Officer, ClioMartin Bazinet – Director of Technology, AWS Canada, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

How many of us can say that they have been farmers, soldiers before running a technology company? Well, Nick Connors can. Nick served his country in Lebanon and now runs the cloud computing business TEKenable.Nick joins Joe to discuss all things cloud computing.

We're back and Season 6 of Realities Remixed starts now! After a summer packed with new ideas, major industry shifts and relentless innovation, Realities Remixed returns with fresh perspectives on the forces transforming business, technology and society.In this season-opening episode, Dave and Rob dive headfirst into the biggest opportunities, toughest challenges and emerging realities facing leaders today. From AI and digital disruption to leadership and the future of work, they set the agenda for a season filled with bold conversations, powerful insights and remarkable guests. TLDR00:22 – We are back after the summer break!03:00 – Hang out: Dave is confused and favorite summer cocktail11:03 – Before we begin, let's review a few important safety considerations13:27 – Dig in: The Trends13:55 – The AI Economy and model behind it19:37 – Adoption lag26:22  – The technology stack is being reset again34:50  – Cybersecurity, sovereignty and trust become strategic priorities39:20 – Summary Part 141:17 – Part 2, The Human experience 47:39 – Society is rebalancing after digital saturation 56:42 – Leadership responsibilities are expanding 59:54 – The next frontier is already emergingHostsDave Chapman:  https://www.linkedin.com/in/chapmandr/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/ 'Realities Remixed' is an original podcast from Capgeminirealitiesremixed@capgemini.com

Experts from Pegasystems and AWS reveal how AI-powered tools now modernize decades-old mainframe systems in weeks instead of years—unlocking trapped data faster than ever.Topics Include:Session covers accelerating mainframe modernization using AWS Transform and Pega BlueprintAgenda: challenges, joint solution, value prop, customer story, rollout mechanismMainframe costs rise 20-30% yearly, straining IT budgets significantlyMonolithic systems create long time-to-market, hurting competitiveness against newer rivalsMainframe data stays locked away, blocking AI adoption and innovationRetiring mainframe skills outpace new workforce training, compounding the problemAI now enables analyzing decades-old code bases within weeks, not yearsAWS Transform extracts business logic; Pega Blueprint visualizes modernized target applicationsFive-step journey: Transform, Pega Foundry, Blueprint, then deployment via Infinity platformThree Transform agents handle code, data, and activity analysis separatelyData analysis covers data lineage and data dictionary schema extractionOutputs feed a knowledge graph, enabling natural language queries anytimeTransform deterministically identifies distinct data paths from mainframe systemsData paths get grouped into business functions, each modernizable independentlyFinal steps extract business logic and generate plain-English requirementsBlueprint agent enriches Transform outputs, enabling intuitive workflow designBlueprint offers runtime previews and is publicly accessible at pega.comPega Infinity platform handles both batch and online mainframe workloadsInsurance company Unum modernized 1.5M lines of COBOL in three monthsExperience-Based Acceleration program delivers modernized, working code within four-to-six weeksParticipants:Surender Kumar – Director, Mainframe Modernization, PegasystemsUjwal Bukka – Sr Partner Solutions Architect, Business Apps, Amazon Web ServicesSourav Sarkar – Sr Worldwide Specialist Solutions Architect, Mainframe & Legacy Modernization, 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/

AI agents aren't just answering questions anymore — they're executing workflows, modifying data, and making autonomous decisions across your most critical systems. As AI agents take on more complex tasks operating at scale and encounter unexpected situations, establishing robust governance and recovery mechanisms becomes increasingly important. Most organizations currently lack the systems needed to manage and address these scenarios effectively.In this episode of the AWS re:Think Podcast, hosts Malini Chatterjee and Jay Sampath sit down with Swami Ramany (GVP, Product Management) and Rob Sadowski (VP, Product & Tech Marketing) from Cohesity to explore the emerging discipline of Agent Resilience — the missing recovery layer for agentic AI at scale. Find further details and demo click HERE Guest: Swami Ramany GVP, Product Management, Cohesity and Rob Sadowski VP, Product & Tech Marketing, CohesityHosts: Malini Chatterjee & Jay Sampath

Derek Champagne talks with Sramana Mitra.Sramana is the founder and CEO of One Million by One Million (1Mby1M), the world's first and only global virtual incubator/accelerator. Its goal is to help a million entrepreneurs globally reach a million dollars in annual revenue, build a trillion dollars in global GDP, and create 10 million jobs.Since its founding in 2010, 1Mby1M has become a powerful platform for democratization of entrepreneurship acceleration.Sramana also developed 1Mby1M's Incubator-in-a-Box methodology for Corporate Incubation that is used by enterprises to manage internal and external innovation endeavors.In 2015, LinkedIn named Sramana one of their Top 10 Influencers alongside Bill Gates and Richard Branson.Sramana has been an entrepreneur and a strategy consultant in Silicon Valley since 1994. Her fields of experience span from hardcore technology disciplines like Artificial Intelligence, Cloud Computing and Semiconductors, to sophisticated consumer marketing industries including e-commerce, fashion and education.As an entrepreneur CEO, Sramana founded three companies: Dais (off-shore software services), Intarka (sales lead generation and qualification software using Artificial Intelligence algorithms; VC: NEA) and Uuma (online personalized store for selling clothes using Expert Systems software; VC: Redwood). Two of these were acquired, while the third received an acquisition offer from Ralph Lauren which the company did not accept.As strategy consultant, Sramana has consulted with over 80 companies, including public companies such as SAP, Cadence Design Systems, Webex, KLA-Tencor, Best Buy, MercadoLibre and Tessera among others. Her work has also included numerous startups and VCs.Sramana has a Masters degree in EECS from MIT and a Bachelors degree in Computer Science and Economics from Smith College.From 2000 to 2004, Sramana chaired the MIT Club of Northern California's entrepreneurship program in Silicon Valley.Learn more at www.1Mby1M.comBusiness Leadership Series Intro and Outro music provided by Just Off Turner: https://music.apple.com/za/album/the-long-walk-back/268386576

Lint the entire CPython code base from scratch. It takes 0.3 seconds. Three blinks of an eye. That is ruff, and it is written in Rust. So are Pydantic, Polars, uv, and Granian. Rust shows up in Python three ways: tools that happen to be Rust, libraries Python imports, and servers that run Python inside Rust. This is Rust for Python developers, not Rust experts. Christopher Trudeau is back on Talk Python to discuss Rust and his latest course Up and Running with Rust. The core rule is that only one thing can own a value at a time. Pass it around freely in Python and the garbage collector cleans up. Do that in Rust and it will not compile. Episode sponsors Sentry Error Monitoring, Code talkpython26 Python in Production Talk Python Courses Links from the show Up and Running with Rust course: training.talkpython.fm Rust: rust-lang.org pydantic: pydantic.dev ruff: docs.astral.sh granian: github.com By example: doc.rust-lang.org rust-lang.org: rust-lang.org rustup.rs: rustup.rs crates.io: crates.io main.rs: main.rs PyO3: github.com https://github.com/ritwiktiwari/awesome-python-rs: github.com ty: docs.astral.sh pyrefly: pyrefly.org uv: github.com polars: pola.rs Watch this episode on YouTube: youtube.com Episode #563 deep-dive: talkpython.fm/563 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Is AI going to kill us all? Frontier systems are producing real security failures, but extinction forecasts are being used to support policies that could consolidate control over AI. Eyvonne and William discuss Jacob Coxon’s high-profile resignation from Anthropic, the gap between real technical risks and speculative extinction narratives, and the commercial incentives driving calls... Read more »

Is AI going to kill us all? Frontier systems are producing real security failures, but extinction forecasts are being used to support policies that could consolidate control over AI. Eyvonne and William discuss Jacob Coxon’s high-profile resignation from Anthropic, the gap between real technical risks and speculative extinction narratives, and the commercial incentives driving calls... Read more »

Topics covered in this episode: Pandas Should Go Extinct Pydantic-pint puts real-world units in your Pydantic models How Libraries Run Rust Inside Python (With PyO3) AWS acquires DuckLabs Extras Joke Watch on YouTube Sponsored by Logfire from Pydantic: pythonbytes.fm/logfire Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too. Finally, if you want an artisanal 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. Calvin #1: Pandas Should Go Extinct Pandas' slowness pushes teams toward "Big Data" tools (Spark, Databricks) they don't actually need — most workloads never hit true Big Data scale Amazon Redshift telemetry: ~95% of tables are under 100GB, ~87% of queries touch 80GB or less — that's "Medium Data," not Big Data Polars and DuckDB fill that gap: single-machine, fast, no cluster required 1 Billion Row Challenge benchmark: Pandas took 4m28s vs. Polars 5.04s and DuckDB 5.19s — DuckDB also used 19x less memory On a real-world NYC taxi dataset (3GB parquet), pure DuckDB ran 2x faster than pure Pandas while using a fraction of the RAM Bonus: Apache Arrow lets you pass data between Pandas/Polars/DuckDB with zero copying, so trying them out doesn't mean a full rewrite Michael #2: Pydantic-pint puts real-world units in your Pydantic models Pydantic-pint bridges Pydantic and Pint so models can validate physical quantities like 4m or 12 meters instead of bare floats. Fields annotated with PydanticPintQuantity parse user input, convert between compatible units, and serialize quantities back out as strings. That closes a real gap for anything consuming API payloads, config files, or sensor data with measurements, letting you enforce units at the validation boundary instead of hoping every caller remembered them. via PyCoder's Weekly newsletter Unit mix-ups have literally crashed spacecraft; now your Pydantic models can refuse them at the door. Annotate a field as Annotated[Quantity, PydanticPintQuantity('km')] and inputs like 12 meters arrive auto-converted to kilometers Validation covers string, numeric, and quantity inputs, and model_dump_json serializes quantities as readable unit strings Installable from PyPI as pydantic-pint, MIT licensed, with docs at pydantic-pint.readthedocs.io Early-stage solo project at version 0.4, so API stability and maintenance are open questions worth discussing Calvin #3: How Libraries Run Rust Inside Python (With PyO3) Pydantic v2's validation core (pydantic-core) is Rust under the hood, built with PyO3 — this post shows how that bridge actually works via a small hand-built JSON parser Four steps to get Rust into Python: write a normal Rust module, annotate with PyO3 macros (#[pyfunction], #[pymodule]), compile/install with maturin, then just import it The parser builds a Rust tree first — Python never touches it until the boundary crossing Key insight: converting the Rust result into Python objects (.into_pyobject) is often the expensive part, not the parsing — 100,000 JSON values means ~100,000 Python objects built after parsing's already done Errors cross the boundary too: Rust's typed errors convert into real Python exceptions (ValueError, FileNotFoundError) via From/?, so callers get clean Python semantics Takeaway for anyone porting Rust in: if you're returning a scalar, don't sweat it; if you're returning a big structure, profile the boundary — that's the real cost, not the algorithm Michael #4: AWS acquires DuckLabs Thank you Dylan McConnell. What does this mean for the DuckDB ecosystem? DuckDB is the open-source in-process analytical SQL engine. MIT licensed. The IP is not owned by any company - it's held by the nonprofit DuckDB Foundation, which was created when the team spun out of CWI Amsterdam. Peter Boncz, the CWI representative on the Foundation board, describes it as the entity that holds all IP of open-source DuckDB. DuckLabs (ducklabs.com) is the company, formerly branded DuckDB Labs. Founded a little over five years ago by Hannes Mühleisen and Mark Raasveldt to give the DuckDB team a stable long-term home, bootstrapped deliberately instead of taking VC, grown to 30+ people in Amsterdam, funded by support and feature-prioritization contracts. It employs the core devs. It does not own DuckDB. DuckLake is one of three projects DuckLabs builds, what they call the Duck Stack: DuckDB, DuckLake, and Quack. DuckLake is the lakehouse format that puts catalog metadata in a SQL database instead of in files on object storage. Quack is newer - an RPC-style protocol that turns DuckDB into a client-server system where both ends are DuckDB instances, slated to stabilize in DuckDB v2.0 in September 2026. MotherDuck is a separate Seattle company, Jordan Tigani's, selling serverless hosted DuckDB. It was started in partnership with DuckDB Labs and has worked closely with Hannes and Mark for four years. It contracted DuckLabs for engineering work and contributes heavily upstream - three of its engineers are among the top 10 outside contributors to DuckDB. It also sells its own DuckLake offering. Customer and collaborator, never owner. What the AWS post changes. Amazon bought the company, not the project. DuckLabs joined AWS effective September 1, with the process concluding August 31, 2026. Hannes and Mark keep leading the team and the project's technical direction, the team stays in Amsterdam, and DuckDB stays MIT under the Foundation. AWS gets the people and a direct line to the roadmap. The license protects your code, not your priorities. Three second-order effects worth tracking: The Foundation board is the real question. It has three directors: Mühleisen, Raasveldt, and Boncz. Two now work for AWS. Commentary on the deal has focused on exactly this - the license protects the code, not the roadmap. The announced counterweight is governance: a technical advisory board on the Foundation, and opening the extension stack so extensions signed by other developers can run in DuckDB. MotherDuck immediately moved into the business DuckLabs vacated. It now sells DuckDB enterprise support, which it had avoided because it didn't want to compete with DuckLabs' business model, and says it has explicit blessing from Hannes and Mark now that they're joining Amazon. It also bought Tower.dev the day before the AWS announcement. Everyone expects an AWS DuckDB service. Tigani says Amazon will likely release one eventually, and welcomes the competition, citing Redshift's failure to slow Snowflake on AWS. The groundwork is already visible: Amazon Quick uses DuckDB to query S3 Tables and has processed over 2.5B queries with it since launching in October 2025. The DuckLake angle is the one to watch. AWS is heavily committed to Iceberg through S3 Tables, and it just acquired the team behind a competing lakehouse format. The stated plan is to use DuckDB, DuckLake, and Quack together to power a new generation of data services, but which format wins internal priority is unannounced. Extras Calvin: astral-sh/uv 0.12.12: code-signed release binaries

Discover how Zuora turned its own billing platform inward to track AI costs down to the individual engineer, giving CFOs the trust and auditability they demand.Topics Include:AWS's Achint Naveen opens, introduces Zuora as a key partnerAudience poll reveals AI monetization is still a struggleZuora's Katherine Shealy introduces the company's AI monetization focusZuora powers monetization for global brands like Twilio, ZoomTheir platform spans CPQ, billing, metering, and revenue recognitionUsage-based pricing has flipped seat-based SaaS models upside downAI companies face a 20-point margin gap versus SaaSCompanies juggling multiple pricing models face major hidden complexityTraditional pricing models are breaking down under AI's dynamic costsZuora's framework aligns teams early through an NPI-style processTheir tech lets companies iterate pricing at engineering speedZuora now tracks its own AI costs internally tooZuora AI runs on AWS Bedrock and AgentCore infrastructureAWS's Achint details the full stack behind Zuora AIAgentCore Memory gives Zuora's agents secure, persistent contextParticipants:Katherine Shealy – Principal Product Marketing Manager, ZuoraAchint Naveen – Sr Account Manager, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Überall schießen sie aus dem Boden. Der Ausbau von Rechenzentren ist keine rein technische Entscheidung mehr, sondern eine politische und gesellschaftliche Frage. Denn es geht weniger darum ob, sondern eher wie wir den digitalen Fortschritt mit lokaler Netzkapazität, den Klimazielen und echter Nachhaltigkeit in Einklang bringen. Ohne leistungsstarke Rechenzentren sind moderne Technologien wie Künstliche Intelligenz, Cloud-Computing, Streaming und autonomes Fahren nicht realisierbar. Sie sind ein Wirtschaftsfaktor und wichtig für die digitale Infrastruktur. Aber bedeuten viele neue Rechenzentren auch mehr digitale Souveränität? Sicher ist: Sie sind energieintensiv. Ihr Wachstum gefährdet die Klimaziele, zudem benötigt die Kühlung viel Wasser und kann eine enorme Lärmbelästigung für die Nachbarschaft verursachen. Es ist also nicht einfach, richtige Entscheidungen zu fällen. Darüber spricht Moderator Ulrich Sonnenschein mit dem Politologen Karsten McGovern, Geschäftsführer der LandesEnergieAgentur Hessen (LEA), mit Ralph Hintemann, Gesellschafter der gemeinnützigen Forschungseinrichtung Borderstep Institut, dem Bürgermeister von Groß-Gerau, Jörg Rüddenklau (SPD), und der hr-Reporterin Pia Stenner. Podcasttipp: 11KM - der tagesschau-Podcast KI-Rechenzentren: Verspielt Deutschland die Zukunft? Rechenzentren sind die Basis für moderne KI-Anwendungen - und werden zur strategischen Zukunftsinfrastruktur. Doch beim nötigen Ausbau hakt es in Deutschland. In dieser 11KM-Folge erzählt uns Gregor Schmalzried vom KI-Podcast des BR, wie weit Deutschland und Europa in Sachen KI-Infrastruktur zurückliegen, welche Rolle digitale Souveränität dabei spielt und warum Länder wie die USA ihr Netz rasant ausbauen. Hier geht's zum KI-Podcast von Gregor Schmalzried und seinen Kolleg:innen: https://www.ardsounds.de/sendung/der-ki-podcast/urn:ard:show:65505255c703e51e/

Bloß weg von US-Diensten? Im Podcast diskutieren wir über digitale Souveränität und stellen Microsoft-365-Alternativen für Privatpersonen, Unternehmen und Behörden vor.

Plus: The Pentagon is in talks to lend $5 billion to AI startup Fluidstack. And former OpenAI executive Fidji Simo joins Nscale's board. Imani Moise hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

How many files does your query read before it reads any data? On some data lakes, you go through JSON and metadata files first, just to learn which Parquet files matter. DuckLake asks one SQL question instead. The metadata lives in a real database. The data stays in plain Parquet. That's the entire format. Pedro Holanda joined DuckDB in 2018, when it was still a research prototype at CWI. He's the lead DuckLake developer. Guillermo Sanchez Dionis works on DuckLake and the new Quack protocol. With Quack as the catalog, DuckLake handles 200 transactions a second under heavy contention. No other open table format comes close. Episode sponsors Six Feet Up Talk Python Courses Links from the show Guests Pedro Holanda: pedroholanda.org Guillermo Sanchez: linkedin.com PhD on progressive indexes: ir.cwi.nl SQLite: www.sqlite.org Litestream: litestream.io boring hardware: talkpython.fm DuckDB: duckdb.org episode 491: talkpython.fm Iceberg: iceberg.apache.org manifesto: ducklake.select DuckLake: ducklake.select spec: ducklake.select this diagram: blobs.talkpython.fm Data inlining: ducklake.select ducklake-dataframe: github.com Polars course: training.talkpython.fm CSV parser: duckdb.org Zero-copy Arrow: duckdb.org ART index: duckdb.org async I/O: duckdb.org v1.0: ducklake.select Git-like branching: ducklake.select Watch this episode on YouTube: youtube.com Episode #562 deep-dive: talkpython.fm/562 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Sophos CSO Simon Reed reveals how attackers now operate like leveraged businesses—and how AI is making both sides of the cyber arms race dramatically more sophisticated.Topics Include:Intro: Simon Reed, CSO at Sophos, joins Kamil Davidov.Sophos defends 625,000+ organizations with AI-native Fusion platform.Sophos MDR runs the world's largest agentic SOC.Simon's journey: cybersecurity since 2001, from graffiti to warfare.Cyber threats framed as constant toxicity, not occasional lightning strikes.Sophos spans small business to enterprise, giving unique threat visibility.Attackers now operate as leveraged, ecosystem-driven businesses, not lone actors.AI dramatically increases attack quality, speed, and sophistication.AWS Local Zones cut latency for Sophos's threat intelligence cloud.IntellX connects every product to real-time global threat data."Good day" means finding novelty before attackers exploit it.Worst days: sudden, unpredictable supply chain compromise scenarios.Sophos updates protection across 600,000 customers within minutes.Decisions made fast, on incomplete data, balancing speed and risk.Sophos has pursued AI and deep learning for eight-plus years.Agentic AI's next phase reduces laborious human security work.Simon prioritizes class-based, automation-scale defenses over budgets.Sophos cut data platform costs 30%, migrated ahead of schedule.Advice: hyper-engage AWS account teams, push for more.Closing story: Sophos helped stop ransomware hitting hospitals during COVID.Participants:Simon Reed – Chief Security Officer, SophosKamil Davidov – Sales Leader Israel ISV-BizApps, 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/

Topics covered in this episode: EuroPython 2026 videos are online The State of Django 2026: Boring is so back htmx 4.0.0 has been released

Vibe coding is accelerating code development within the Enterprise, but at what cost of security? Retool's CEO shares how you can accelerate software development while managing the risks effectively.Topics Include:Internal software runs pharmacies, grocery checkouts, and airport check-ins dailyRetool manages and de-risks environment from insecure codeAI has driven a 10x surge in code volume since 2025More code plus less human review means falling code qualityNon-engineers can now build working apps in minutes flatBut deploying and securing those apps remains genuinely difficultMultiple CIOs found private company data exposed on the internetUncontrolled model choice is quietly driving up company costsAttackers now deploy automated agent swarms, not lone hackersDefense is asymmetric: one flaw in, everything must holdRetool runs inside customers' own cloud, often on AWSA single data choke point enables logging, audits, authorizationGuardrails, not their absence, actually let teams move fasterSecurity audits reveal major gaps in nearly all companies checkedNearly all companies may face a serious hack within 18 monthsParticipants:David Hsu – Founder, CEO, RetoolSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

How many cores does your machine have, 10, 18? Your async Python code uses just one of them. That isn't a bug in asyncio. That's the design, and optimizing event loops to be faster by 20% doesn't change it. So Giovanni Barillari started over. Joe is the creator of Granian, the Rust-based server that powers Talk Python. His new project is TonIO, an async runtime written from scratch for free-threaded Python. Real threads, a handful of primitives instead of asyncio's pile of them, and it flat out refuses to start if the GIL is on. Episode sponsors Sentry Error Monitoring, Code talkpython26 Python in Production Talk Python Courses Links from the show Guest Giovanni Barillari: github.com Granian: github.com Hyper: github.com Free threaded Python: docs.python.org Sort of: labs.quansight.org did a whole course: training.talkpython.fm uvloop: github.com rloop: github.com TonIO: github.com your EuroPython 2026 talk: www.youtube.com Michael's Cutting Python Web App Memory Over 31% Article: mkennedy.codes Watch this episode on YouTube: youtube.com Episode #561 deep-dive: talkpython.fm/561 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Mark Zuckerberg argues that broadly distributed personal AI, or a “superintelligence” in his parlance, can increase prosperity and counter the risks of AI being controlled by a handful of government and corporate entities. Drew Conry-Murray joins Eyvonne and William to engage in a lively roundtable where they examine whether distributing access meaningfully distributes power when... Read more »

Mark Zuckerberg argues that broadly distributed personal AI, or a “superintelligence” in his parlance, can increase prosperity and counter the risks of AI being controlled by a handful of government and corporate entities. Drew Conry-Murray joins Eyvonne and William to engage in a lively roundtable where they examine whether distributing access meaningfully distributes power when... Read more »

Plus: John Ternus officially takes over as Apple CEO. And Anthropic signs $35 billion cloud computing deal backed by Nvidia. Imani Moise hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Topics covered in this episode: OpenAI's Python SDK has migrated to HTTPX2 TMOG - Native Task Manager for macOS, Windows, and Linux wrapture - one wrapper for mocking, tracing, and observability linkedin2md: turn your LinkedIn export into 40+ Markdown files Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Consulting from Six Feet Up Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too. Finally, if you want an artisanal 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. Calvin #1: OpenAI's Python SDK has migrated to HTTPX2 The OpenAI Python SDK has migrated to HTTPX2, the Pydantic-stewarded fork of httpx. Pydantic picked it up citing "limited activity recently" in the original project, promising "a reliably maintained path forward." If you just use the default client, nothing to do. No code changes. The catch is TLS. Quoting the guide: HTTPX "previously verified certificates against the CA bundle provided by certifi. HTTPX2 instead uses the operating-system trust store, and the SDK no longer installs certifi." That "can break certificate verification in minimal container images without system CA certificates, environments using corporate TLS-inspecting proxies, and deployments that relied on a custom or modified certifi bundle." The fix is SSL_CERT_FILE or SSL_CERT_DIR, or pass your own ssl.SSLContext via verify. Deeper integrations need real edits: custom clients, auth handlers, hooks, and request mocking all take HTTPX2 objects now, and plain httpx is no longer pulled in transitively. So import httpx in your own code means declaring it yourself or moving over. Temporary escape hatch: a legacy HTTPX client Michael #2: TMOG - Native Task Manager for macOS, Windows, and Linux A native, deeply instrumented system monitor for macOS, Windows, and Linux, now in public beta - from Plummers' Software, i.e. Dave Plummer, who wrote the original Windows Task Manager and donated it to Microsoft in 1995. Wikipedia Three real native apps: Swift/AppKit on macOS, Win32 on Windows, C++/Qt 6 on Linux, with a shared C++ core keeping metric semantics aligned - no browser shell anywhere. One dense summary: CPU, clocks, thermals, GPU, memory, storage, network, energy, and the processes responsible for the load, all click-through. Per-core honesty: logical processor and NUMA views, P and E cores color-coded, optional kernel time, 60 FPS live meters. Memory with context: pressure, wired, compressed, cached, committed, available, and swap, plus configurable scrolling history. Processes that act like processes: tree view, filtering, sorting, follow mode, and native verbs including service and launchd control. Phosphor themes: light, dark, green, amber, blue, or mono, with color and saturation you tune yourself. Calvin #3: wrapture - one wrapper for mocking, tracing, and observability Graham Dumpleton, author of wrapt and the original New Relic Python agent, has released wrapture. The name is wrapt plus capture. The core idea: wrap real code instead of replacing it, so the real code still runs while you watch every call. Name a method with wrapture.binding(Class, "method"), open a timeline(), and you get a tape of what actually happened. Real return values, real nesting, arguments normalised against real signatures. tape.tree() prints the call graph as it ran. One mechanism, three jobs: monkey patching with a real lifecycle (apply, remove, suspend, plus returns, raises, transforms_args), unit testing that asserts on real call flow instead of a flat MagicMock call list, and ad-hoc tracing of a running app. The testing pitch is error paths. Inject TimeoutError at the payment gateway, then assert the ledger was never written. Stubs and mocks are strict and spec-required, and there is deliberately no bare Mock(). Tracing needs no code at all. A wrapture.toml naming targets and a sink, run with python -m wrapture main.py, and you get a live call tree with timings. It captures ordinary logging calls as nested events, and with the otel extra it exports spans, metrics and correlated logs with W3C trace ids that join across services. Every line of code and docs was AI-written under their direction, and they say so up front. Two weeks from first commit, eleventh alpha, over 1000 tests, 150+ pages of docs. Alpha on PyPI, needs Python 3.12+ and wrapt 2.4.0+. Michael #4: linkedin2md: turn your LinkedIn export into 40+ Markdown files Via Juan Manuel Daza - a Python CLI that unpacks LinkedIn's data-export ZIP into clean, per-category Markdown you can drop straight into an LLM. One command: linkedin2md Complete_LinkedInDataExport.zip, plus o for output dir, -lang en|es, and -pdf. 40+ output files: profile, experience, education, skills, connections, posts, comments, reactions, recommendations, endorsements, job applications, even ad targeting and LinkedIn's inferences about you. Built for LLM analysis: the README pitches NotebookLM, Claude Projects, Obsidian, and Ollama, with example prompts like "what patterns do you see in my career transitions?" PDF resume mode: -pdf renders an A4 CV via weasyprint, and degrades gracefully to Markdown-only if it isn't installed. Dependency note: "pure Python / zero-dep" holds for the Markdown path only - the PDF path needs weasyprint and markdown installed. Install: pipx install linkedin2md recommended, pip in a venv otherwise - 86% Python, 10 releases, v0.3.1 in May. Agentic dev angle: repo ships opencode config and an N3RV subagent pipeline, including a "judgment day" dual-model adversarial PR review. Extras Calvin: EVE Online Migrates to Python 3 Michael: Dinkus by Will McGugan Joke: Tao of Programming: Book 5 Maintenance

In a fascinating panel discussion, executives from Couchbase, SentinelOne and AWS share strategies ensuring the highest adoption and ROI when deploying AI and the pitfalls to avoid along the way.Topics Include:Agentic AI marks shift from clever data to autonomous agentsOrganizations sit at different AI maturity levels, not uniformOnly 31% of adopters see measurable financial impact from AIAdoption friction, not access, is what stalls most AI valueSegment your workforce: innovators, pragmatic majority, and reluctant laggardsGive innovators tools, budget, and freedom before chasing laggardsVisible recognition programs turn early innovators into internal role modelsAI-ready data infrastructure remains the top blocker to real adoptionFuture AI value concentrates at customer-facing, transaction-level touchpointsCoding tools see fast uptake; broader business adoption lags behindAI is quietly rewriting SEO, SEM, and lead-routing strategyAgent trust requires both clean data and strong safety guardrailsHuman-in-the-loop review lets AI handle investigation, humans decide outcomesIn agentic AI, go-to-market partnerships matter more than past tech wavesStrong tech-platform partnerships help smaller vendors punch above their weightMarketplace listings can cut sales cycles from months to weeksBest partnerships form around solving hard problems, not quarterly quotasConfidence gap: only 38% of employees feel AI-readyParticipants:Deirdre Toner – President & Chief Commercial Officer, CouchbaseEran Ashkenazi - Chief Business Officer, SentinelOneConnie de Lange – Director, AWS Strategic Customer & Partner Marketing, North America, Amazon Web ServicesMatt Wood – Chief AI & Technology Officer, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Plus: South Korea will give its entire population free access to homegrown generative AI. And Nvidia is pausing some revenue sharing deals just weeks after announcing them. Danny Lewis hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In 2020, a gastroenterologist in Glasgow did the math on his new research study and came up with 30,000 samples, arriving over two years from three cities and a dozen hospitals. He asked around about how researchers keep track of that. The answer was Microsoft Excel. Shaun Chuah had written some HTML by hand in Notepad back in high school and that was about the whole of his programming experience, so he opened the Django tutorial and started reading. Six years later that app is Foundry120, holding 10 terabytes of clinical and genomics data with an agentic AI running on top of it. Episode sponsors Sentry Error Monitoring, Code talkpython26 Talk Python Courses Talk Python Courses Links from the show Guest Shaun Chuah: github.com Up and Running with Rust Course: talkpython.fm Foundry120: www.foundry120.com Designing Data Intensive Applications: www.oreilly.com Microsoft Foundry: ai.azure.com ChatIBD: www.chatibd.com Blog: shaunchuah.github.io @drshaunchuah: x.com github.com/shaunchuah: github.com Watch this episode on YouTube: youtube.com Episode #560 deep-dive: talkpython.fm/560 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Topics covered in this episode: Web UIs for your reverse proxy Wagtail 8.0 is hot off the presses RISC-V is now officially supported by CPython Django's annual releases make every version an LTS Extras Joke Watch on YouTube About the show Sponsored by Logfire from Pydantic: pythonbytes.fm/logfire Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am 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: Web UIs for your reverse proxy Traefik, nginx, and Caddy all sit in front of a lot of self-hosted infrastructure, and all three are configured by hand-editing files. Three active projects put a control plane on top: Traefik Manager (Python + Flask), Nginx UI (Go + Vue), and caddy/ui (React + Node). All three are additive rather than replacements - none of them take ownership of your config away from you - which is the part that matters when the thing has write access to production routing. Traefik Manager is the Python one: Flask 3.1 and Gunicorn for the control plane, a lightweight Go agent for remote instances, currently v1.10.0 with an Android companion app. Nginx UI is a single Go binary at 11.3k stars, with a block-style config editor, an Ace editor doing LLM completion on nginx syntax, and an MCP server so agents can drive it. caddy/ui runs as two containers next to your existing Caddy, reads and writes your Caddyfile directly, and uses Caddy's /adapt API to validate before reload - no Docker socket required. Each one edits the config the underlying server already reads, so your files stay the source of truth and you can drop the UI without unwinding anything. Undo is a first-class feature across all three - timestamped backups with optional Git history, config version compare and restore, Caddyfile snapshots with one-click rollback. Observability is where they diverge: Traefik Manager does CrowdSec and a visual route map, Nginx UI does server metrics, caddy/ui streams access logs over SSE and pulls p50/p95/p99 off Caddy's Prometheus endpoint. Maturity spread is wide - Nginx UI has 11.3k stars, caddy/ui has 4 and was built in a single Claude session - and caddy/ui ships with auth off by default, so set CADDY_UI_USER and JWT_SECRET before it goes anywhere near a public interface. Calvin #2: Wagtail 8.0 is hot off the presses Link: https://github.com/wagtail/wagtail/releases/tag/v8.0 Custom base page models are now supported, so projects aren't locked into subclassing Wagtail's Page as shipped (Matt Westcott). New v3 REST API handles both read and write CMS operations, a first for Wagtail's API. A global registry for permission policies, plus full customizability for the remaining page views via PageViewSet. AVIF and WebP images are no longer auto-converted to PNG by default, a real behavior change to watch on upgrade. Five security fixes: page admin API restrictions, document identification by SHA1 hash, descendant collections in the Documents/Images API, snippet copy permissions, and the page translation endpoint. Formalized Django 6.1 support, and CI now runs on uv with a lockfile. Sponsor: Logfire from Pydantic Your AI agent failed at 2am. Was it the model? A tool call? The database? Most observability tools can't tell you, because they only see part of your stack. Pydantic Logfire sees all of it. One trace across your agents, LLMs, APIs, and database. Down to the infrastructure: services, Kubernetes, and hosts. It's built on OpenTelemetry, with SDKs for Python, TypeScript, and Rust, and it works with any OTel-compatible language. Every prompt, token count, and cost, right next to your vector searches and API calls. You query everything with Postgres-compatible SQL. And so can your coding agent, through the Logfire MCP server. Stop guessing. Read the trace. Pydantic Logfire. AI, it's still just engineering. Visit pythonbytes.fm/logfire today and sign up today. Get 10M records free every month, no card required. You can even click “Onboard with your coding agent” to copy a prompt to have claude or codex integrate Logfire into your app. Thanks to Pydantic for supporting the show. Calvin #3: RISC-V is now officially supported by CPython Link: https://blog.python.org/2026/08/riscv-now-officially-supported/ CPython added RISC-V as a tier 3 platform under PEP 11, specifically the 64-bit Linux target riscv64-unknown-linux-gnu. RISC-V is an open ISA anyone can implement, unlike x86 and ARM, and its market is projected to quadruple by 2032. The RISE Project donated real RISC-V machines for buildbots; the author's work was funded by a Sovereign Tech Agency fellowship. What changes: the port is now a maintained compatibility target, so CPython changes are less likely to quietly break it. What doesn't: no python.org installers, no binary wheel parity for native extensions. Next up: RISC-V runners in CPython CI for pre-merge feedback, then a push toward tier 2, plus architecture-specific optimizations. The ask is testing. If you have RISC-V hardware, build CPython, run your test suite, file what breaks. Tier 3 is the weakest support tier. PEP 11 tier 3 requires a core developer contact and a buildbot, but failures on tier 3 platforms explicitly do not block a release. Saying "ongoing CI/testing expectations" oversells it. The honest bit is "someone is now on the hook for it, and breakage gets noticed," not "it's guaranteed working." Worth the caveat that this is Linux SBCs, not microcontrollers. A VisionFive 2 counts, an ESP32-C6 or Pico 2 does not. Those are 32-bit non-Linux parts where MicroPython is still the answer. Michael #4: Django's annual releases make every version an LTS Starting with Django 2028, Django will move to one January feature release per year, adopt calendar-based version numbers, and support every release for three years. The old distinction between standard and LTS releases disappears, giving teams a predictable annual upgrade path that aligns more closely with Python's own release and support cadence. Every Django release becomes the safe, long-supported choice, so teams no longer need to wait for a specially designated LTS version or absorb two years of changes at once. Each release gets one year of mainstream bug fixes followed by two years of security and data-loss fixes. New releases support the three latest Python versions and add the next Python release during their first year. Calendar versioning begins with Django 2028, followed by Django 2029 and so on. Three Django versions will be supported at any time, giving third-party packages a clearer rolling target. Nothing changes before 2028, and existing commitments for Django 5.2 LTS and 6.2 LTS remain in place. Extras Calvin: The Python docs now document the time complexity of built-in types https://docs.python.org/3.16/library/time-complexity.html Thinking in Python - Bruce Eckel's free book https://thinkinginpython.com/ Michael: prune_uv_pythons.py - Prune uv-managed Python installs, keeping only the newest patch per minor version Runs automatically in my system “upgrade” script: upgrade-output-2026.png Started using Ollama cloud models for my Hermes assistant. Thanks to Jeff Triplett I learned they are not just local models. Joke: The Tao of Programming - Book Seven: Corporate Wisdom

Demandbase's Vice President of Product explains why they deleted a fully-approved AI architecture two months before launch — and how the rebuild surpassed some of their customer's highest expectations.Topics Include:AWS's Achint Naveen introduces Demandbase's VP of Product, Chad HoldorfDemandbase unifies sales, marketing, and revenue data into one viewNovember's architecture used many specialized agents, all committee-approvedThat design failed constantly — only a 30% conversation pass rateOn May 11th, the team deleted the entire architectureRebuilt in May with AWS Strands: one simpler, flexible agentPass rate leapt from 30% to 94% almost overnightWeek two retention rose from the low 20s to upper 80sWeekly active users grew 45% week-over-week after launchReal customer interviews play, calling the new AI a "dream"One user cut an hour-long report down to fifteen minutesCustomers now trace ad impressions directly to closed dealsHoldorf's advice: delete and rebuild when architecture gets too complexAWS's Naveen walks through Bedrock, AgentCore, and StrandsAgentCore Memory highlighted as Demandbase's next area of explorationParticipants:Chad Holdorf – Vice President of Product Management, DemandbaseAchint Naveen – Sr Account Manager, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Supply chains don't break at the nodes — they break at the seams. Hosts Malini Chatterjee and Diana Conner sit down with Sriram Nagaswamy, EVP of Technology at FourKites, to unpack why a decade of supply chain investment still hasn't solved the handoff problem — and how agentic AI built on Amazon Bedrock is changing the game.From competing on resilience in an era of tariffs and nearshoring, to autonomous agents that act on disruptions (not just report them), this episode covers what it takes to move from visibility to execution at scale.AI agents that autonomously execute supply chain operations — built on the world's first Intelligent Control Tower, powered by 1.1M carriers and suppliers across 200+ countries. For details on how to get started, visit FourKites.aiGuest: Sriram Nagaswamy, EVP of Technology, FourKitesHosts: Malini Chatterjee & Diana Conner

Your site is down. It's 3am. Is it a bug, a bill, or a breach? You can't tell yet, and everyone is watching you find out. Matt Lea has spent fifteen years being the person companies call when an outage is costing them real money per hour, and his whole argument is that everything you'd want in that moment gets decided months earlier, on ordinary afternoons, when someone chose the convenient thing. We walk his top twelve dos and don'ts in AWS - infrastructure as code, IAM roles instead of access keys, private subnets, no wildcards, no public buckets - and I push on which of them actually matter if you're one person on a small VPS. Then we get to Cloud War Games, where Matt breaks things on purpose so your team's first real incident isn't their first incident. Let's get into it. Episode sponsors Sentry Error Monitoring, Code talkpython26 Talk Python Courses Talk Python Courses Links from the show Guest Matt Lea: linkedin.com Talk Python Certificates: training.talkpython.fm/certificates Schematical: schematical.com CloudWarGames.com: cloudwargames.com Zero to Hero on AWS Security: www.oreilly.com Repo: github.com Custom Wheel Offset: customwheeloffset.com 2012 TechCrunch Disrupt Hackathon: techcrunch.com tech comics: schematical.com shhgit: github.com Zero Trust in 200ms: Implementing Identity-Per-Transaction: us.pycon.org Coolify: coolify.io returned to full GA Nov 2025: aws.amazon.com Signed URLs/cookies: docs.aws.amazon.com Cloudflare: www.cloudflare.com Bunny Shield: bunny.net Cloud War Games One: www.youtube.com Cloud War Games Two: www.youtube.com LinkedIn: linkedin.com YouTube: youtube.com KnocKnoc: knocknoc.io Watch this episode on YouTube: youtube.com Episode #559 deep-dive: talkpython.fm/559 Episode transcripts: talkpython.fm Theme Song: Developer Rap

William Collins and Eyvonne Sharp dig into the latest AI headlines, from the largest copyright settlement in American history to stolen AI models and invisible watermarks on Claude output. Plus, they discuss why so many companies have rallied around NVIDIA’s support for open weight AI models. Our hosts also examine the biggest questions arising from... Read more »

William Collins and Eyvonne Sharp dig into the latest AI headlines, from the largest copyright settlement in American history to stolen AI models and invisible watermarks on Claude output. Plus, they discuss why so many companies have rallied around NVIDIA’s support for open weight AI models. Our hosts also examine the biggest questions arising from... Read more »

Topics covered in this episode: Python 3.12.14, 3.11.16, 3.10.21 - security releases Codeberg's AI-code ban tests its role as a GitHub alternative Brett Cannon: what's missing for reproducible builds on PyPI nothing records the source code a distribution came from. direct_url.json captures it when you install from a repo or archive, so the fix is putting the same info in sdist/wheel metadata. recording the build tools. Wheels can already do this via PEP 770 SBOMs in .dist-info/sboms/ - sdists can't, since they're a tarball plus a precalculated PKG-INFO with nowhere to hang extra metadata. Either "don't use sdists" or an sdist v2. Extra extra extra, hear all about it Extras Joke Watch on YouTube Sponsored by Logfire from Pydantic pythonbytes.fm/logfire This episode is brought to you by Pydantic Logfire. It's observability for AI apps from the team behind Pydantic - agents, LLMs, APIs, database, and infrastructure in a single trace, queried with Postgres-compatible SQL. Your coding agent can query it too, through their MCP server. I'll tell you more later. Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am 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. Calvin #1: Python 3.12.14, 3.11.16, 3.10.21 - security releases https://blog.python.org/2026/08/python-31214-31116-31021/ Source-only security releases for the three branches now in security-fix-only mode; release team blamed the European solar eclipse for the timing. tarfile hardening. Multiple path-traversal bypasses of the data filter closed, including a symlink escape that bypassed the CVE-2025-4330 fix; extract() now applies the filter to link targets too. Four fresh CVEs: CVE-2026-2297 (SourcelessFileLoader not using io.open_code() for .pyc), CVE-2026-4224 (expat crash on deeply nested content models), CVE-2026-3644 (control chars in http.cookies.Morsel), plus the completed CVE-2021-4189 fix in ftplib.ftpcp. Quadratic-complexity DoS cleanup across the stdlib: HTMLParser, configparser regexes, unicodedata.normalize(), csv.Sniffer.sniff(), and ElementTree XPath index predicates. Header/injection fixes: CR/LF rejected in HTTPConnection.set_tunnel(), control chars blocked in wsgiref.handlers status, and webbrowser now rejects leading dashes (plus a %action prefix bypass). http.client now caps chunked trailer lines and 1xx interim responses at 100 each - a hostile server could previously hang the client forever despite a socket timeout. Memory-safety odds and ends: stale pointers in lzma/bz2/zlib decompressors after MemoryError, a bz2 stack overflow on reuse-after-error, and bundled libexpat bumped to 2.8.3. If you're still on 3.10, 3.11, or 3.12 - and you extract tarballs from anywhere you don't fully control - this one's not optional. Michael #2: Codeberg's AI-code ban tests its role as a GitHub alternative Armin's article “Codeberg Divides” Armin Ronacher argues that Codeberg's new terms, which prohibit projects mostly written with generative AI, create a vague and difficult-to-enforce boundary. His larger concern is that a democratically governed host can still be unpredictable or ideologically narrow, weakening Codeberg's potential as a broad European alternative to GitHub. The strongest question for Python developers is whether repository hosting should judge legal open source by how code was produced, or focus on behavior and resource abuse. “Mostly generated” is hard to measure in modern codebases where developers mix handwritten code, completions, agents, and generated refactors. Ronacher suggests clearer alternatives: ban all LLM involvement, or target autonomous repository spam, abusive resource use, and low-quality generated contributions directly. Codeberg is free to choose a values-driven community, but that may conflict with being predictable, neutral infrastructure and a serious GitHub competitor. Worth discussing: can open-source communities set meaningful AI boundaries without driving maintainers and projects into opposing camps? Very first search for these terms lands on this page. Codeberg looked like a viable alternative. … Unfortunately, the latest update to its terms of service seems to mark a first step in changing one part I moved there for, namely the “freedom” part. Sponsor: Logfire from Pydantic Your AI agent failed at 2am. Was it the model? A tool call? The database? Most observability tools can't tell you, because they only see part of your stack. Pydantic Logfire sees all of it. One trace across your agents, LLMs, APIs, and database. Down to the infrastructure: services, Kubernetes, and hosts. It's built on OpenTelemetry, with SDKs for Python, TypeScript, and Rust, and it works with any OTel-compatible language. Every prompt, token count, and cost, right next to your vector searches and API calls. You query everything with Postgres-compatible SQL. And so can your coding agent, through the Logfire MCP server. Stop guessing. Read the trace. Pydantic Logfire. AI, it's still just engineering. Visit pythonbytes.fm/logfire today and sign up today. Get 10M records free every month, no card required. You can even click “Onboard with your coding agent” to copy a prompt to have claude or codex integrate Logfire into your app. Thanks to Pydantic for supporting the show. Calvin #3: Brett Cannon: what's missing for reproducible builds on PyPI Framing came out of his 2026 Python Packaging Council nomination - the secure-supply-chain gap he found is that Python has no defined way to do reproducible builds at all. Design goal is zero friction: producers uploading to PyPI shouldn't have to do anything. The work lands on build backends and installers. Gap #1: nothing records the source code a distribution came from. direct_url.json captures it when you install from a repo or archive, so the fix is putting the same info in sdist/wheel metadata. Gap #2: recording the build tools. Wheels can already do this via PEP 770 SBOMs in .dist-info/sboms/ - sdists can't, since they're a tarball plus a precalculated PKG-INFO with nowhere to hang extra metadata. Either "don't use sdists" or an sdist v2. The replay mechanism already exists: [build-system] in pyproject.toml is a defined entry point, so if backends recorded their own environment, you could reinstall and re-run the build. Payoff idea: trusted third parties report successful reproductions back to PyPI, which displays "independently reproduced by X" - surfaced in the index API so installers could prefer reproduced files. Explicitly framed as a perk, not a requirement - roughly SLSA build level 1, no shaming projects that don't opt in. Verbal kicker option: "And don't think pure-Python wheels are off the hook. Something built that wheel, and if that something was compromised, so is your wheel. SolarWinds was a build-process attack." Michael #4: Extra extra extra, hear all about it Python 3.14.7 Upgraded the MCP servers to 2026-07-28 v2 protocols (talk python, python bytes) Got agentsview running synced via postgres Talk Python courses, teams trial offering Talk Python courses, government procurement offering Lean TDD audio book is out Extras Calvin: uv now prefers post-quantum key exchange - https://github.com/astral-sh/uv/releases/tag/0.12.4 Joke: Beware of dog

ServiceNow and AWS reveal how the DevOps Agent and MCP Server Console are turning incident response into a fast, autonomous, fully governed process. Topics Include:Govind Menon (ServiceNow) and Arun Jacob (AWS) discuss MCP and A2A strategy.ServiceNow understands workflows; partners with AWS to power them with AI.AI Control Tower governs and secures agent access to enterprise data.MCP is the industry standard for how AI agents read and act.Action Fabric spans A2A, REST APIs, and MCP for agentic work.AWS DevOps Agent, built on Bedrock, resolves incidents through sub-agents.Admin and operator access patterns integrate with Dynatrace, Datadog, Slack, GitHub.Demo: ServiceNow incident automatically triggers DevOps Agent investigation and resolution.DevOps Agent writes findings live back into the ServiceNow incident ticket.ServiceNow champions capping MCP servers at 30 tools for performance.MCP Server Console lets teams build scoped, use-case-specific tool servers.NowAssist skills, Knowledge Graph, and REST APIs become MCP tools.Live demo connects a 38-tool custom MCP server to DevOps Agent.Role-based access ensures users only see their permitted MCP tools.ServiceNow's autonomous ITOM agents point toward unsupervised future operations. Participants:Govind Menon – Head of MCP Product, ServiceNow Arunsingh Jeyasingh Jacob – Senior Solution Architect - ISV, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Conversations on Groong - August 16, 2026In this episode of Conversations on Groong, we speak with Richard Campbell about artificial intelligence infrastructure and Armenia's Firebird project. We discuss the global AI race, the economics and energy demands of data centers, whether current AI valuations align with physical and economic realities, and what sovereign AI capacity means for Armenia's strategic positioning.Topics:Global AI race and hypeEconomics of AI data centersEnergy limits and infrastructure demandsArmenia's Firebird AI projectJobs, innovation, and local benefitsAI sovereignty and export controlsMilitary value and security risksGuest: Richard CampbellHosts:Hovik ManucharyanAsbed BedrossianEpisode 577 | Recorded: August 11, 2026SHOW NOTES: https://podcasts.groong.org/577VIDEO: https://youtu.be/dFx8Oe48RaYINTERESTING TALKS BY RICHARD CAMPBELL:Keynote: After the AI Hype - What's Real, and What's Next - Richard Campbell - 2026Above the Cloud: Building Data Centers in Space - Richard Campbell - NDC Copenhagen 2026#ArtificialIntelligence #Armenia #FirebirdAI #AIDataCenters #SovereignAI #EnergySecurity #TechGeopolitics #NationalSecuritySubscribe and follow us everywhere you are: linktr.ee/groong

Topics covered in this episode: Claude Code /insights Post-quantum crypto lands in Python MCP goes stateless — and FastMCP gets renamed inshellisense - IDE style command line auto complete Extras Joke Watch on YouTube About the show Sponsored by Xweather Xweather combines enterprise-grade weather intelligence with agent-ready APIs, natural language capabilities, and an MCP server so your agents can adapt workflows, automate responses, and make better decisions based on real-world conditions. Michael will tell you more about them later in the show. Get started for free at pythonbytes.fm/xweather Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too. Finally, if you want an artisanal 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: Claude Code /insights Michael's Insights: michael-kennedy-claude-code-insights-2026-08-09.html Be careful sharing these outputs, they include details references to your projects, errors, security findings, etc. ;) /insights reads your last 30 days of local session transcripts and hands back an interactive HTML report on how you actually work. One command, zero setup: type /insights in a session, or run claude -p "/insights" from the shell for a non-interactive version that just prints the path Reads what's already on disk: pulls session logs from ~/.claude/projects/, skipping agent sub-sessions and anything under 2 messages or 1 minute Project areas: clusters your sessions into themes like "CLI Tooling" or "Documentation" with session counts Friction analysis: categorizes where things went wrong by root cause - and quotes your own prompts back at you Interaction style: tells you whether you're a delegator or a micromanager, plus which workflows are worth doubling down on Actually actionable: suggests concrete CLAUDE.md additions and Claude Code features you're not using The catch: Haiku does the per-session classification, so the first run takes several minutes; results cache to ~/.claude/usage-data/facets/ and the report lands at ~/.claude/usage-data/report.html Calvin #2: Post-quantum crypto lands in Python pyca/cryptography 48 ships ML-KEM (key establishment) and ML-DSA (signatures) — NIST's post-quantum standards, now one pip install away. Big deal because it's the 11th most-downloaded package on PyPI (~1.2B downloads/month) and sits under Ansible, Certbot, Airflow, and paramiko. No PQ there, no PQ anywhere in Python. Trail of Bits did the work (Rust bindings, cross-backend API, tests, AWS-LC backend support), funded by the Sovereign Tech Agency. Timing tracks a June 22 White House order setting federal deadlines: PQ key establishment by end of 2030, PQ signatures by end of 2031. Not a drop-in swap — the wire sizes explode. ML-DSA-65 signatures are 3,309 bytes vs Ed25519's 64; ML-KEM-768 public keys are 1,184 bytes vs X25519's 32. Hardcoded field sizes and length prefixes will bite. API looks like the existing asymmetric primitives, except ML-KEM is encapsulate/decapsulate rather than a Diffie-Hellman exchange. SLH-DSA (the hash-based conservative backstop) is still in progress. The primitives are here, but protocols haven't caught up — so you won't be running post-quantum Certbot this week. Sponsor: Xweather You're using agents that can write code, summarize documents, and automate workflows. But they're missing one thing: awareness of the world around them. This is where today's sponsor, Xweather comes in. Xweather combines enterprise-grade weather intelligence with agent-ready APIs, natural language capabilities, and an MCP server built for tools like Claude, Codex, Copilot, and modern IDEs – so your agents can adapt workflows, automate responses, and make better decisions based on real-world conditions. Backed by Vaisala, whose instruments fly on NASA missions to Mars, Xweather delivers trusted data and unique insights that go beyond conditions to actual impact – from real-time lightning strikes to road surface forecasts. Start with 15,000 free API calls each month and pay only for what you use as you grow. Xweather is your full weather stack, for developers by developers. Start building for free today at pythonbytes.fm/xweather. The link is in your podcast player's show notes and on the episode page. Thanks so much to Xweather for supporting Python Bytes. Calvin #3: MCP goes stateless — and FastMCP gets renamed From Philipp Acsany over at Real Python The 2026-07-28 spec landed July 28 and the Python SDK shipped 2.0.0 the same day. Biggest rewrite since MCP launched, and it's breaking on purpose. Context for scale: the Tier 1 SDKs are pulling close to half a billion downloads a month, with TypeScript and Python each past a billion total. The headline is the stateless core. The initialize/initialized handshake and the Mcp-Session-Id header are both retired — protocol version, client identity, and capabilities now ride in _meta on every request, with an optional server/discover RPC if a client wants capabilities up front. Any request can land on any instance behind plain round-robin, no shared storage. Server-initiated calls are the hard part of the migration. Sampling, elicitation, and roots/list no longer call back to the client; instead the server returns resultType: "input_required" and the client retries with inputResponses attached. Multi Round-Trip Requests, MRTR. Also: Mcp-Method and Mcp-Name are now required headers so gateways route on headers instead of cracking JSON bodies, and missing-resource errors move to standard 32602. Deprecation sweep with an actual policy behind it — Roots, Sampling, Logging, and the legacy HTTP+SSE transport all deprecated with a twelve-month minimum offramp. Tasks graduated out of the experimental core into a real extension, which is what the formalized extensions framework was for. MCP Apps is now an official extension too, so a tool call can return sandboxed interactive HTML. Auth picked up RFC 9207 issuer validation, issuer-bound credentials, and a shift from DCR toward CIMD. Python SDK 2.0 is where it gets personal: FastMCP is now MCPServer, no alias, no shim. McpError → MCPError. Wire types went snake_case (is_error, input_schema) and moved to a standalone mcp_types package, with mcp.types kept as a permanent alias. One Client object replaces the old transport + ClientSession + initialize() stack. httpx became httpx2. Sync handlers run on worker threads now, so asyncio.get_running_loop() raises inside them. The good news: one MCPServer serves both protocol eras, so 2025-era clients keep working with nothing to configure, and a Resolve(fn) parameter lets one tool body cover MRTR and the old path. 1.x is maintenance-and-security-fixes only — pin mcp>=1.28,

Chief Strategy Officer Nick Reed unpacks the "architecture of trust," AI-native enterprise transformation, and why staying laser-focused on customer value is central to Bizzdesign's bold AI strategy.Topics Include:Bizzdesign: global enterprise transformation SaaS company with Dutch roots, founded 2000, Main Capital-backedCustomers include HSBC, Shell, KPMG, and Airbus globallyBold 12-month strategy: acquired Mega International and Alfabet from Software AGAcquisitions tripled revenue, created the first true end-to-end enterprise transformation suiteBizzdesign's 18-year recognition as a Gartner Magic Quadrant Leader in Enterprise ArchitectureThe launch of Bizzdesign Unify in April 2026, an AI-native transformation collaboration platform Nick Reed's journey: enterprise software, customer value, M&A strategy, and AI-driven transformationHow Bizzdesign supports planning, design, and governance pillars across the transformation lifecycleHow Bizzdesign Unify complements existing enterprise architecture and portfolio management environmentsWhy Bizzdesign Unify is architecturally different: conversational AI-native experience, not traditional UIAI acts as a co-worker, supporting transformation work and decisions through curated skillsNew experience opens enterprise context to broader stakeholdersBizzdesign Unify bridges the gap between messy whiteboards and governed enterprise dataExample walkthrough: mapping customer service transformation dependencies and impactsGenerative AI creates transformation scenarios grounded in enterprise contextTech stack built on Amazon Bedrock, MCP clients, graph dataBalancing agentic AI and automation with human-in-the-loop accountability"Architecture of trust": permissions, oversight, and decentralized controlPricing shifts from seat-based to AI credit consumption modelClosing advice: stay laser-focused on core customer value creationParticipants:Nick Reed – Chief Strategy Officer, BizzdesignKamil Davidov – Sales Leader Israel ISV-BizApps, Amazon Web ServicesJohan Broman – EMEA ISV Head of Solutions Architecture, 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/

Every company has one. The little internal tool that Jane built back in 2021, and then Jane left. Nobody understands it, nobody will touch it. There are two unwritten rules around it: don't change it, it's working. And if you break it, you bought it. That's dark-matter enterprise software. For every app you can actually see, there are ten of these sitting in the shadows, frozen. Michael Booth thinks that just changed. He read my article on hyper-personal software and ran with it, writing about hyper-team software: small teams inside big companies finally building the tools that were never going to get built. We cover where this works, where it quietly goes wrong, and the guardrails that keep it from turning into a mess. Let's get into it. Episode sponsors Sentry Error Monitoring, Code talkpython26 Python in Production Talk Python Courses Links from the show Guest Michael Booth: github.com Talk Python AI Integrations: talkpython.fm/blog From Hyper-Personal to Hyper-Team Software: Small Team-Built, AI-Assisted Tools Inside the Enterprise: www.databooth.com.au What hyper-personal software looks like (MK's article): mkennedy.codes Databooth Site: www.databooth.com.au Wall Street just lost $285 billion because of 13 markdown files: martinalderson.com SaaSpocalypse is real but everyone is panicking about the wrong thing: www.reddit.com Warp Terminal: www.warp.dev Watch this episode on YouTube: youtube.com Episode #558 deep-dive: talkpython.fm/558 Episode transcripts: talkpython.fm Theme Song: Developer Rap

For over 125 years, Farmers Mutual Telephone Company (FMTC) has helped connect rural Iowa—first with telephones, then cable television, cellular service, broadband internet, and now preparing for what may become agriculture's next major infrastructure investment: AI computing. In this episode, Kevin shares how a small rural telephone company evolved into a modern broadband provider and why Iowa's independent telecommunications companies have been uniquely positioned to bring fiber internet to rural communities long before much of the country caught up. He explains how fiber optic networks work, why broadband is becoming just as essential as electricity, and why nearly every modern technology—from cellular service to Starlink—ultimately depends on fiber somewhere along the journey. The conversation then turns toward one of the fastest-growing topics in technology: artificial intelligence. Kevin explains why AI is creating unprecedented demand for computing power, what massive data centers mean for energy and infrastructure, and why he believes the future isn't giant facilities consuming thousands of acres—but rather distributed micro data centers that could fit on a single lot while serving customers around the world. The hosts also tackle concerns many farmers have about large data centers, including land use, energy consumption, and local economic impact. Kevin discusses how smaller AI computing facilities could create new opportunities without removing productive farmland while giving farmers more control over their own data. The discussion explores whether producers could someday "farm data" just like they market grain—owning, storing, and deciding when and how to monetize one of their operation's fastest-growing assets. Along the way, you'll also hear: How the internet actually reaches your farm Why symmetrical upload and download speeds matter The differences between fiber, cellular, and Starlink The future of precision agriculture and AI Why protecting farm data may become just as important as protecting grain in the bin Whether fiber optics will ever be replaced If you've ever wondered how technology is reshaping agriculture—or where rural America fits into the AI revolution—this episode offers a fascinating look at what's coming next. Want Farm4Profit Merch? Custom order your favorite items today!https://farmfocused.com/farm-4profit/ Don't forget to like the podcast on all platforms and leave a review where ever you listen! Website: www.Farm4Profit.comShareable episode link: https://intro-to-farm4profit.simplecast.comEmail address: Farm4profitllc@gmail.comCall/Text: 515.207.9640Subscribe to YouTube: https://www.youtube.com/channel/UCSR8c1BrCjNDDI_Acku5XqwFollow us on TikTok: https://www.tiktok.com/@farm4profitllc Connect with us on Facebook: https://www.facebook.com/Farm4ProfitLLC/Farm4Profit Media is not a financial, legal, or tax advisor. Content is provided for informational purposes only, and we serve solely as a platform for third-party opinions. Any actions taken based on this content are at your own risk. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Behind the headlines about skyrocketing revenues and AI investments, the actual costs and future risks for Microsoft, Google, and Amazon are shrouded in strategic accounting moves. Plus, Paul finished rewriting and adding new chapters to the Windows 11 Field Guide - mostly just clean-up now, and then whatever new monthly features. Lastly, The Document Foundation issues a friendly reminder about the Office 2021 EOL and how that never happens with their software Microsoft earnings Microsoft earnings up 18 percent to $90 billion Analysis: Microsoft finds a new way to not account for AI costs Windows Pavan Davuluri says he's "energized" about what's happening to Windows in 2026. OK. But what's really happened so far? When will the biggest changes land? And when, if ever, will you address the real enshittification in Windows 11? Windows Insider Program: Five new builds - New Taskbar comes to Beta channel This leads to questions of timing, and here, WIP is not all that transparent still Another antitrust win: Apple to allow Copy and Paste between Windows and iPhone AMD revenues up 50 percent to $11.5 billion, but it's all AI datacenter Amazon: up 20 percent to $200 billion Apple: up 16 percent to $109 billion AI Satya Nadella mentions AI super app again, not clear why anyone cares about this Proton Lumo can do data visualization now Xbox and gaming Asha Sharma details the priorities for XBOX in the next year and number 5 will shock you XBOX console prices going up in the EU and UK Thanks, Caption Obvious: Yes, Backward Compatibility on PC will support Xbox 360 games too XBOX plans new FanFest tour dates - there's SO much to celebrate! Gears of War: E-Day leads the charge for new Game Pass titles in August XBOX Insiders is testing new console features XBOX app comes to Hisense and VIDDA TVs EA goes private for $55 billion in cash, but also some debt Sony has sold 95.3 million PS5s Sony responds to concerns about no more discs (with "pffffftttt") Tips and picks Tip of the week: It's done! App pick of the week: LibreOffice RunAs Radio this week: Ransomware Readiness with Heather Renze Brown liquor pick of the week: Frey Ranch Straight Bourbon Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: cirasync.com/Windows threatlocker.com/twit

Behind the headlines about skyrocketing revenues and AI investments, the actual costs and future risks for Microsoft, Google, and Amazon are shrouded in strategic accounting moves. Plus, Paul finished rewriting and adding new chapters to the Windows 11 Field Guide - mostly just clean-up now, and then whatever new monthly features. Lastly, The Document Foundation issues a friendly reminder about the Office 2021 EOL and how that never happens with their software Microsoft earnings Microsoft earnings up 18 percent to $90 billion Analysis: Microsoft finds a new way to not account for AI costs Windows Pavan Davuluri says he's "energized" about what's happening to Windows in 2026. OK. But what's really happened so far? When will the biggest changes land? And when, if ever, will you address the real enshittification in Windows 11? Windows Insider Program: Five new builds - New Taskbar comes to Beta channel This leads to questions of timing, and here, WIP is not all that transparent still Another antitrust win: Apple to allow Copy and Paste between Windows and iPhone AMD revenues up 50 percent to $11.5 billion, but it's all AI datacenter Amazon: up 20 percent to $200 billion Apple: up 16 percent to $109 billion AI Satya Nadella mentions AI super app again, not clear why anyone cares about this Proton Lumo can do data visualization now Xbox and gaming Asha Sharma details the priorities for XBOX in the next year and number 5 will shock you XBOX console prices going up in the EU and UK Thanks, Caption Obvious: Yes, Backward Compatibility on PC will support Xbox 360 games too XBOX plans new FanFest tour dates - there's SO much to celebrate! Gears of War: E-Day leads the charge for new Game Pass titles in August XBOX Insiders is testing new console features XBOX app comes to Hisense and VIDDA TVs EA goes private for $55 billion in cash, but also some debt Sony has sold 95.3 million PS5s Sony responds to concerns about no more discs (with "pffffftttt") Tips and picks Tip of the week: It's done! App pick of the week: LibreOffice RunAs Radio this week: Ransomware Readiness with Heather Renze Brown liquor pick of the week: Frey Ranch Straight Bourbon Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: cirasync.com/Windows threatlocker.com/twit

William Collins is joined by guest co-host Eric Chou as well as Network Automation Forum founders Scott Robohn and Chris Grundemann to discuss how their community emerged from a simple question: Why haven’t we seen full adoption of network automation, yet? They discuss the growth of AutoCon and how its practitioner-focused, vendor-neutral approach has fostered... Read more »

Behind the headlines about skyrocketing revenues and AI investments, the actual costs and future risks for Microsoft, Google, and Amazon are shrouded in strategic accounting moves. Plus, Paul finished rewriting and adding new chapters to the Windows 11 Field Guide - mostly just clean-up now, and then whatever new monthly features. Lastly, The Document Foundation issues a friendly reminder about the Office 2021 EOL and how that never happens with their software Microsoft earnings Microsoft earnings up 18 percent to $90 billion Analysis: Microsoft finds a new way to not account for AI costs Windows Pavan Davuluri says he's "energized" about what's happening to Windows in 2026. OK. But what's really happened so far? When will the biggest changes land? And when, if ever, will you address the real enshittification in Windows 11? Windows Insider Program: Five new builds - New Taskbar comes to Beta channel This leads to questions of timing, and here, WIP is not all that transparent still Another antitrust win: Apple to allow Copy and Paste between Windows and iPhone AMD revenues up 50 percent to $11.5 billion, but it's all AI datacenter Amazon: up 20 percent to $200 billion Apple: up 16 percent to $109 billion AI Satya Nadella mentions AI super app again, not clear why anyone cares about this Proton Lumo can do data visualization now Xbox and gaming Asha Sharma details the priorities for XBOX in the next year and number 5 will shock you XBOX console prices going up in the EU and UK Thanks, Caption Obvious: Yes, Backward Compatibility on PC will support Xbox 360 games too XBOX plans new FanFest tour dates - there's SO much to celebrate! Gears of War: E-Day leads the charge for new Game Pass titles in August XBOX Insiders is testing new console features XBOX app comes to Hisense and VIDDA TVs EA goes private for $55 billion in cash, but also some debt Sony has sold 95.3 million PS5s Sony responds to concerns about no more discs (with "pffffftttt") Tips and picks Tip of the week: It's done! App pick of the week: LibreOffice RunAs Radio this week: Ransomware Readiness with Heather Renze Brown liquor pick of the week: Frey Ranch Straight Bourbon Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: cirasync.com/Windows threatlocker.com/twit

Behind the headlines about skyrocketing revenues and AI investments, the actual costs and future risks for Microsoft, Google, and Amazon are shrouded in strategic accounting moves. Plus, Paul finished rewriting and adding new chapters to the Windows 11 Field Guide - mostly just clean-up now, and then whatever new monthly features. Lastly, The Document Foundation issues a friendly reminder about the Office 2021 EOL and how that never happens with their software Microsoft earnings Microsoft earnings up 18 percent to $90 billion Analysis: Microsoft finds a new way to not account for AI costs Windows Pavan Davuluri says he's "energized" about what's happening to Windows in 2026. OK. But what's really happened so far? When will the biggest changes land? And when, if ever, will you address the real enshittification in Windows 11? Windows Insider Program: Five new builds - New Taskbar comes to Beta channel This leads to questions of timing, and here, WIP is not all that transparent still Another antitrust win: Apple to allow Copy and Paste between Windows and iPhone AMD revenues up 50 percent to $11.5 billion, but it's all AI datacenter Amazon: up 20 percent to $200 billion Apple: up 16 percent to $109 billion AI Satya Nadella mentions AI super app again, not clear why anyone cares about this Proton Lumo can do data visualization now Xbox and gaming Asha Sharma details the priorities for XBOX in the next year and number 5 will shock you XBOX console prices going up in the EU and UK Thanks, Caption Obvious: Yes, Backward Compatibility on PC will support Xbox 360 games too XBOX plans new FanFest tour dates - there's SO much to celebrate! Gears of War: E-Day leads the charge for new Game Pass titles in August XBOX Insiders is testing new console features XBOX app comes to Hisense and VIDDA TVs EA goes private for $55 billion in cash, but also some debt Sony has sold 95.3 million PS5s Sony responds to concerns about no more discs (with "pffffftttt") Tips and picks Tip of the week: It's done! App pick of the week: LibreOffice RunAs Radio this week: Ransomware Readiness with Heather Renze Brown liquor pick of the week: Frey Ranch Straight Bourbon Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: cirasync.com/Windows threatlocker.com/twit

William Collins is joined by guest co-host Eric Chou as well as Network Automation Forum founders Scott Robohn and Chris Grundemann to discuss how their community emerged from a simple question: Why haven’t we seen full adoption of network automation, yet? They discuss the growth of AutoCon and how its practitioner-focused, vendor-neutral approach has fostered... Read more »

Security has always been the vegetables of software. Everyone agrees it matters, and somehow it never quite makes it onto the plate. At PyCon US this year, that changed. For the first time ever, security got its own dedicated, day-long track, one of just two at the whole conference, sitting right next to AI. And the room was packed to the back wall. On this episode, I'm joined by the three people at the center of it. Seth Larson, Security Developer in Residence at the Python Software Foundation and, very recently, a CPython core developer. Juanita Gomez, a PhD researcher at UC Santa Cruz in open source security, who co-chaired the track. And Mike Fiedler, PyPI's Safety and Security Engineer, one of the very few people paid full-time to keep the packages you install safe. We use the arc of the track's talks to take the temperature of Python security right now: supply chain attacks, dependency cooldowns, zero trust, SBOMs, and the push to bring Rust into CPython. And why not one of us thinks security is anywhere close to solved. Turns out that's the good news. It's why the room was full. Episode sponsors Sentry Error Monitoring, Code talkpython26 Talk Python Courses Links from the show Guests Juanita Gomez: linkedin.com Mike Fiedler: miketheman.dev Seth Michael Larson: sethmlarson.dev Trailblazing Python Security: us.pycon.org Everything Security at PyCon US 2026 (PSF blog): pyfound.blogspot.com Dependency Cooldowns: cooldowns.dev Anatomy of a Phishing Campaign (Mike Fiedler) Recording: www.youtube.com FedRAMP: www.gsa.gov Zero Trust in 200ms: Implementing Identity-Per-Transaction with Python & Serverless-Tristan McKinnon: www.youtube.com Rust for CPython project: blog.python.org pre-PEP: discuss.python.org Rust for CPython: Making Python Safer and More Robust for Everyone - Emma Smith: www.youtube.com SBOMit: github.com Asleep at the Wheel: Getting your SBOMs to pay attention... - Sanchit Sahay, Abhishek Reddypalle: www.youtube.com Volatility: volatilityfoundation.org Post Incident Runtime SBOM Generation from Python Memory - Hala Ali: www.youtube.com zizmor: docs.zizmor.sh GitHub Actions security in Python packages (Andrew Nesbitt write-up): nesbitt.io andrew/pycon: data & analysis for the GitHub Actions security talk: github.com GitHub Actions Security in Python Packages - Andrew Nesbitt: www.youtube.com gh-profiler: examine a GitHub user's profile to gauge their contributions: github.com PyCon US YouTube channel: www.youtube.com SBOMit: adding verification to SBOMs (OpenSSF): openssf.org Ecosystems: ecosyste.ms Watch this episode on YouTube: youtube.com Episode #557 deep-dive: talkpython.fm/557 Episode transcripts: talkpython.fm Theme Song: Developer Rap

For years, "Django and async" came with an asterisk. The docs themselves warned you off it. Scary performance notes, a story that felt half-finished. Well, that story just got rewritten, literally, and the person who rewrote it is here to tell you why the old framing was wrong. Carlton Gibson is a former Django Fellow, sat on the security team for eight years, and he's on the steering council. On this episode we get into the async topic doc rewrite, what actually remains versus what was just fear, the new Tasks framework in 6.0, DB-level cascades and fetch modes landing in 6.1, and why free-threading is the bet that's about to pay off big for Django. If you've been told Django's async story isn't ready, this is the episode that puts that myth to bed. Episode sponsors Sentry Error Monitoring, Code talkpython26 Python in Production Talk Python Courses Links from the show DjangoCon Europe: djangocon.eu PyCon Italia: pycon.it Django on the Med: djangomed.eu Django Mantle: noumenal.es PyPI: pypi.org release notes: docs.djangoproject.com on_delete: docs.djangoproject.com Fetch modes: docs.djangoproject.com HttpRequest.multipart_parser_class: docs.djangoproject.com async topic doc: docs.djangoproject.com docs: docs.djangoproject.com DEP 14: github.com django-tasks: github.com django-tasks-local: github.com Celery: docs.celeryq.dev PEP 703: peps.python.org free-threading HOWTO: docs.python.org PEP 779: peps.python.org ASGI: docs.djangoproject.com PGBouncer: www.pgbouncer.org Channels: channels.readthedocs.io sync_to_async / async_to_sync: docs.djangoproject.com noumenal.es: noumenal.es Django Chat: djangochat.com @carlton@fosstodon.org: fosstodon.org Article: Cutting Python Web App Memory Over 31%: mkennedy.codes Watch this episode on YouTube: youtube.com Episode #556 deep-dive: talkpython.fm/556 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Plus: SAP shares rise after earnings beat. And CATL profit surges on booming battery demand. Imani Moise hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

P.M. Edition for July 23. The U.S. plans to impose new tariffs on most trade partners, replacing President Trump's temporary global 10% tariff. Plus, the threat of escalating conflict in the Middle East drove oil prices over $100, and concerns around higher inflation made bond yields surge. WSJ markets reporter Sam Goldfarb discusses how that ripples through the economy. Meanwhile, heavy AI spending from Alphabet and Tesla spooked investors, and the Nasdaq dropped more than 2%. And after IBM issued a rare profit warning last week, the company's earnings shed more light on what went wrong. We hear from reporter Anissa Gardizy about where its business goes from here, while tech columnist Christopher Mims spoke with IBM CEO Arvind Krishna. Alex Ossola hosts. Correction: New U.S. tariffs target 60 economies, or more than 80 countries. An earlier version of this podcast incorrectly said the tariffs target 60 countries. (Corrected on July 24.) Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.