Podcasts about Cloud computing

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.

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/

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/

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

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 »

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

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

Omilia's CTO shares their strategy on building AI that facilitates billions of calls and what it takes to win the next decade.Topics Include:Miguel Alava welcomes Marios Fakiolas, CTO of OmiliaOmilia has built production AI for over 20 yearsBanking and telco clients demand speed and accuracyOmilia builds its own agent framework and self-learning agentsInfrastructure and data matter more than any single modelModels are ships; Omilia's infrastructure is the permanent dockAI is core infrastructure at Omilia, not an external APIBuilders differ from orchestrators by owning bespoke modelsPlatform is a kitchen; models are ingredients for recipesOmilia believes AI should be accessible, not just for elitesAI vendors split into camps by economics and scalabilityGen AI and ROI don't yet align well industry-wideSmall unaddressed pain points can quietly sink AI projectsOmilia revisits its offering using deep customer knowledgeCost-efficient economics at billions of calls is Omilia's moatMaking AI work differs from making AI profitableBedrock enables fast prototyping and early customer feedbackOmilia moves to SageMaker AI to fully own its modelsMarios praises the AWS team supporting Omilia dailySpeed round covers AI advocates, cloud, and adaptability aheadParticipants:Marios Fakiolas – Chief Technical Officer, OmiliaMiguel Alava – EMEA ISV General 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/

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

Topics covered in this episode: Some more things about Django I've been enjoying Who cleans up after the vibe-coding party? Where Did All Your AI Tokens Go? AgentsView to the rescue! Careful with phishing all 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, 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: Some more things about Django I've been enjoying Julia Evans is learning "2010-style" web dev (Django + SQL + server-rendered HTML) after years of Go backends and JS-heavy frontends Query builders: likes defining custom QuerySet classes with chainable filter methods (.approved().future().with_tags()) — more readable than raw SQL Template filters: highlights urlize, linebreaksbr, json_script, and especially querystring for building/modifying query-string links in templates Migrations: still loves Django's auto-generated migrations — 19 and counting on her project Skips inheritance for class-based views; prefers function-based views for sharing code, though fine using Django's own mixins/interfaces Performance surprise: CPU profiling (via py-spy) — not slow DB queries — revealed the culprit; she'd accidentally disabled the cached template loader, and re-enabling it took throughput from ~2-3 req/s to ~12 req/s on a $10/mo VM Michael #2: Who cleans up after the vibe-coding party? FT Magazine piece by Sam Learner (July 11) on AI coding tools overwhelming open source maintainers - sent in by listener Dylan McConnell, whose main point was that this ran in the Financial Times, not a dev blog. cURL as the case study - Daniel Stenberg has been the only full-time person on it for years; libcurl has been installed an estimated 20+ billion times with 3,000+ listed contributors. Bug bounty killed - cURL ended its paid security bounty program in January, citing an "explosion of AI slop reports" that take real time to debunk and drain morale. Extractive contributions - authoring a PR is now nearly free, reviewing one still costs a human; tldraw's Steve Ruiz closed outside contributions entirely, asking why he'd want someone else writing the easy part. Guido weighs in - van Rossum says projects are holding emergency meetings over the slop flow, and notes LLM patches tend to touch unrelated parts of a file, making review more tedious. "Vibe Coding Kills Open Source" - paper from Miklós Koren's group: packages frequently recommended by coding models saw big download jumps with no matching engagement, breaking the reputation loop that sustains maintainers. Stack Overflow flatlined - over 100,000 questions a month before ChatGPT, under 1,500 last month, with the response rate cut roughly in half; the public archive is now stale training data. The course-creator angle - Josh Comeau's newest web dev course launched at about a third of prior enrollment, and he worries about devs who never learn which questions to ask. But the most interesting portion is what was omitted. Focused on: The end of the curl bug-bounty Omitted: High-Quality Chaos Why the omission is interesting It fits a narrative. The FT piece is a maintenance-and-decline story, and January-Stenberg is a perfect witness for it. April-Stenberg complicates it - same person, same project, better data, opposite direction on the specific claim being used. The tell is already in the article. Learner quotes Stenberg saying AI tools are much better at finding problems than fixing them. That's the April thesis in one line, and it goes undeveloped. Reason for the shift is process, not vibes. Killing the bounty removed the cash incentive and the venue change filtered the rest. Worth saying out loud, because "AI reports got better" isn't quite it - "no bounty plus a real triage platform" is closer. Joke too: Sarah O'Connor wrote a related piece (is this just before skynet launches?) Calvin #3: Where Did All Your AI Tokens Go? AgentsView to the rescue! Local-first desktop/web app for browsing, searching, and analyzing your past AI coding agent sessions (Claude Code, Codex, Copilot, Cursor, Gemini, Aider, and dozens more) Auto-discovers session files on your machine — no config needed; everything stored locally in SQLite, no cloud/accounts agentsview usage is a drop-in ccusage alternative — reads from pre-indexed SQLite, reports run 80–220× faster on large histories New Activity dashboard shows peak concurrency, active vs. idle time, agent-minutes, and cost — filterable by project/agent/machine, with a -json CLI report too Full-text + optional semantic search across every session; also imports Claude.ai/ChatGPT chat exports Install via pip install agentsview, uvx agentsview, brew install --cask agentsview, or download desktop binaries from GitHub Releases Michael #4: Careful with phishing all The situation I pass this along because it was a pretty sneaky bit of targeted phishing, and happened to play off an old interaction in bandit's repo. As usual with phishing scams there are a bunch of tells that this isn't legitimate, but just enough plausibility that I could see falling for it in a weak moment. Relative nobodies like me haven't historically been worth the effort to hit with scams this specific. Agents change the game though :-/. Be careful out there folks! Original message From: "Patrick (Blacktrace)" [HTML_REMOVED] To: LISTENER EMAIL Subject: Your Bandit #1350 (B105 NextToken false positive) -- just fixed that exact case Date: Wednesday, July 15, 2026 12:02 AM Hi AJ, Saw your Bandit issue #1350 -- the B105 hardcoded-password false positive on the string NextToken. I build a deterministic gate that filters that class of Bandit noise, and #1350 was literally the case I just fixed: NextToken / next_token / page_token / nextPageToken now stay quiet, while a genuine hardcoded token like api_token="sk-live-..." still fires. Verified against your exact case. 30-second paste: https://blacktrace.co/noise-eraser Where it still trips, published: https://blacktrace.co/kruc Curious whether it clears what you hit -- and if it trips on something of yours, that's the more useful reply. Patrick, Blacktrace I asked Claude for some analysis too. It was pretty good at finding them. The message name-drops enough real detail to feel legit, but the structure is pure phishing - everything in it exists to get AJ onto blacktrace.co. The strongest ones: Freemail sender, corporate signoff. Signs as "Patrick, Blacktrace" but sends from emailpjv@gmail.com. Real company outreach comes from the company domain, not a personal Gmail - and there's no last name. Over-specific targeting. It mirrors AJ's exact public activity - issue #1350, the B105 rule, the NextToken false positive, even the token variants. That's the "just enough plausibility" AJ flagged, and it's exactly what agents make cheap: scrape a GitHub issue, auto-generate tailored bait. Legit cold outreach rarely reads your history back to you this precisely. The entire payload is two links. Strip the technical flattery and the message is just "paste here" plus "see results here." When the whole point of an email is the click, that's the tell. "30-second paste." Low-friction urgency, and "paste" most likely means paste your source into their tool - handing your code to a stranger's site. Exfiltration dressed as convenience. Brand-new, no-reputation domain. blacktrace.co has no track record, and the name is doing some ominous work. The /kruc slug is random noise, not how real product pages get named. Precise-sounding jargon that's actually vague. "Deterministic gate," "noise-eraser" - impressive, empty. Bolted onto correct real details (B105 is the Bandit hardcoded-password test, sk-live- is a Stripe live-key prefix) to borrow credibility. The disarming close. "if it trips on something of yours, that's the more useful reply" - engineered humility that flatters your expertise and baits a response. Makes engaging feel like you're doing them a favor, which drops your guard. Extras Calvin: DjangoCon US 2026 is rapidly approaching, August 24-28, Chicago Ruff v0.16.0 massively expands its default rule set Ruff now enables 413 rules by default, up from 59 https://astral.sh/blog/ruff-v0.16.0 Michael: Completely redesigned the home page. Try /insights in Claude Code (terminal) Joke: We're Safe

From alert to root cause in one minute - how PagerDuty built autonomous incident response on Amazon Bedrock, and the future of triage and trust. Topics Include:PagerDuty's agents must perform during 2am outages — stakes are highSoftware shipping accelerated dramatically; production environments largely did notA 9:30pm slowdown traced to a race condition solved two years earlierThe fix was documented — but the context wasn't at handPagerDuty Advance ships four agents: SRE, Scribe, Shift, InsightsWhy four, not one? Focus and predictability in non-deterministic systemsSaurabh Shanbhag: Bedrock is far more than a model serviceZero data retention, PrivateLink, TLS — why enterprises pick BedrockFrontier models everywhere burns tokens; classify, route, distill, fine-tuneSRE agent triages alerts before you even join the callOne minute to root cause — context beat raw intelligenceHuman surfaces versus machine surfaces: MCP and CLI move fastest"The model eats the harness" — every upgrade invalidates foundational componentsFeeding agents everything failed; compartmentalised investigation threads work betterNew York Life's three stages of trust, and the seatbelt override that wasn't Participants:Tom Hogarty - Senior Director Product Management, PagerDutySaurabh Shanbhag – Sr Partner Solution Architect, 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/

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.

Stewart Alsop sits down with Matias Avalos on this episode of the Wisdom podcast to explore the intersection of technology, humanism, and creative sovereignty. The conversation moves from Matias's work with neural network-based audio plugins and effect chains to broader questions about corporate transhumanism, data ownership, and what it means to maintain human agency in an increasingly automated world. They discuss the dangers of convenience-driven technological adoption, the implications of companies like Palantir and Neuralink, and how bureaucratic incentives push toward total legibility while protecting their own opacity. Along the way, they touch on everything from IMAX audio production and the death of walkable cities to Instagram's transformation from visual diary to data extraction platform, ultimately arguing for local, open-source, and sovereign approaches to technology that keep humans in the loop rather than replacing them with "average fabrics" of algorithmic output. Find Matias Avalos on LinkedIn for more techno-poetic discussions.Timestamps00:00 Stewart welcomes Matias Avalos to discuss their friendship and upcoming conversation topics.05:00 Matias explains audio effect chains using neural networks to capture professional recording room signatures and create portable high-fidelity sound processing.10:00 Discussion of piezoelectric microphones converting sound vibrations to electrical signals and CIA experiments using lasers to capture audio from glass surfaces.15:00 Conversation shifts to digital audio recording, sampling rates, and the importance of source material quality for post-production work.20:00 Stewart shares his journey building web conferencing software to replace Riverside, encountering lip-sync problems and learning about FFMPEG processing.25:00 Matias discusses corporate transhumanism, Neuralink's implications, and how brain interfaces could enable continuous taste mining beyond medical applications.30:00 Analysis of corporate transhumanism through companies like Neuralink, discussing private decision-making, lack of transparency, and various transhumanist philosophies globally.35:00 Matias reads poetry about digital replicas and data generation, exploring how wearable devices continuously capture human activity creating targetable information streams.40:00 Discussion of Peter Thiel's shift from libertarianism to neoconservatism, Palantir's origins in Total Information Awareness program, and Buenos Aires as humanist sanctuary.45:00 Examination of American convenience culture, post-WWII suburban isolation, and Buenos Aires as walkable humanist alternative to car-dependent American cities.50:00 Matias presents Neil Harbison as positive transhumanism example, explaining color-to-vibration synesthesia implant while discussing techno-optimism from Global South perspective.55:00 Conversation explores bureaucratic incentives toward population legibility, compelled silence laws, and sovereignty through open-source local technology ownership avoiding corporate control.60:00 Matias concludes discussing digital identity ownership, social network portability, and how digital twins determine human worth across platforms and borders.Key Insights1. Modern digital audio processing technologies represent a fundamentally different approach to music and sound production compared to generative AI tools. Matias Avalos distinguishes between technologies like Neural DSP's Mantra plugin, which uses deep neural networks to capture and emulate professional recording environments, and generative platforms like Suno. The key difference is that traditional digital signal processing tools put the creator in control, allowing them to make artistic decisions using expensive effect chains that would otherwise only be available in elite studios like Abbey Road. These technologies democratize access to professional audio tools without removing human agency from the creative process, whereas generative AI tools operate as black boxes that produce outputs based on prompts rather than allowing genuine creative control.2. The capture and preservation of source material remains critically important in audio and video production, despite advances in post-production capabilities. Through his experience building a web conferencing application to replace Riverside.fm, Alsop learned that many technical problems, particularly lip-sync issues, stemmed from poor source file management and recording methodology. This principle extends across all media production, as Avalos explains using the example of missing lighting in professional photography. While modern generative AI might attempt to invent missing elements, the results cannot match properly captured source material. This highlights a fundamental tension in contemporary media production where the quality triangle of cheap, good, and fast has been disrupted by AI technologies that can deliver all three if we lower our standards for what constitutes good work.3. Corporate transhumanism represents a particular and concerning subset of transhumanist philosophy that differs significantly from earlier artistic and philosophical approaches to human enhancement. While early transhumanists like Neil Harbison, a color-blind artist who implanted a device to translate color frequencies into vibrations, pursued personal enhancement and expanded human experience, corporate transhumanism as practiced by companies like Neuralink focuses on technological integration with significant profit motives and control mechanisms. The discussion highlights how these corporate approaches position themselves as solving medical and cognitive problems while simultaneously creating dependency through terms of service, data mining, and token-based economic models. This represents a Trojan horse where the promise of enhanced capability masks the establishment of new forms of control and surveillance of human consciousness itself.4. The concept of legibility as a bureaucratic end goal rather than a means to an end explains much of the surveillance apparatus that has developed in Western societies, particularly in the United States since 9/11. Alsop describes how those in positions of power, wealth, and fame have a structural incentive to make everything around them legible and controllable while maintaining their own privacy and illegibility to external observation. This dynamic manifests in technologies like Palantir and in legal mechanisms like compelled silence through gag orders, which directly contradict constitutional principles of free speech. The drive for total legibility of populations appears to have no ultimate purpose beyond the accumulation of legibility itself, creating a recursive loop where surveillance and data collection become self-justifying activities that serve power structures rather than the populations they ostensibly protect.5. Human beings continuously generate enormous streams of metadata through their daily activities, creating what Avalos describes as evaporating against our own will into hundreds of RSS feeds for hundreds of corporations. This automatic data production occurs through basic activities like waking up, moving through space with smartphones and wearable devices, and interacting with digital platforms. The fundamental question that predates transhumanism but becomes more urgent within it is how individuals can own what they produce simply by existing and moving through the world. This data is captured through accelerometers, gyroscopes, GPS systems, and countless other sensors that create comprehensive digital profiles without explicit consent or meaningful control by the individuals being monitored. The unilateral nature of this communication, where individuals broadcast data without receiving genuine value in return, has become so deeply embedded in modern infrastructure that it forms part of the taken-for-granted landscape of contemporary life.6. Platform lock-in and the inability to migrate digital identity across services creates a new category of loss that requires genuine grieving. Avalos describes how his experience with Instagram, which began as a personal visual diary before the Facebook acquisition, evolved into a situation where he cannot extract his creative work and social connections from the platform without significant loss. This phenomenon extends beyond mere inconvenience to touch on fundamental questions of identity and citizenship, as social media profiles increasingly determine real-world opportunities like visa applications and border crossings. The implications of digital footprints have become severe enough that individuals can be denied entry to countries based on algorithmic analysis of their online interactions, likes, and expressed beliefs. This creates a situation where people are worth exactly what their digital twin indicates they are worth, with no meaningful avenue for human appeal or nuanced self-representation.7. The future relationship between humans and technology requires a return to principles of sovereignty, local control, and open source development rather than dependence on corporate platforms and proprietary systems. Both Alsop and Avalos advocate for a do-it-yourself approach to technology that emphasizes ownership and control over personal tools and data. This includes avoiding closed systems like Neuralink unless they become open source and user-controlled, and prioritizing local execution of AI models over cloud-based services that create dependencies and enable surveillance. The conversation suggests that techno-optimism remains possible, but only from what Avalos calls the trenches, acknowledging the different relationship that people in the Global South and those outside centers of power have with technology. This grounded optimism recognizes the entanglement of beneficial and harmful aspects of technological development and maintains that human agency and creative freedom require conscious resistance to the convenience-at-all-costs model that has characterized recent technological adoption.

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.

In Part 2 of our AWS Summits recap, Geries AbouAyash, AWS Managing Director, North America Solutions Architecture joins Malini and Amit to unpack what the shift to agentic AI really means for how we work. From Amazon Quick's autonomous agents ("Quick Just Does It") to Kiro on iOS, DevOps Agent, and Transform — and the infrastructure changes powering the emerging agent economy, like S3 Annotations and AWS WAF AI Traffic Monetization — the conversation goes beyond announcements to the bigger question: does AI just help us do more, or help us do more meaningful work? The throughline: AI isn't about replacing people — it's about removing undifferentiated work so builders, engineers, and leaders can spend more time where they create the greatest value.https://kiro.dev/blog/introducing-kiro-for-ios/https://aws.amazon.com/devops-agent/features/?trk=bdad73ef-9780-48b0-b82e-6d92ad86fcf6&sc_channel=pshttps://aws.amazon.com/about-aws/whats-new/2026/04/aws-transform-kiro-vscode/https://docs.aws.amazon.com/AmazonS3/latest/userguide/annotations-overview.htmlhttps://aws.amazon.com/about-aws/whats-new/2026/06/aws-waf-ai-traffic-monetization/AWS Hosts: Amit Narayanan & Malini ChatterjeeEmail Your Feedback: rethinkpodcast@amazon.com

Dave, Esmee, Rob and Marcel wrap up an incredible Season 5, reflecting on the biggest technology trends, the most memorable conversations, and the fantastic guests who joined us along the way. From AI and cybersecurity to quantum computing and digital transformation, it's been a season full of insights, innovation, and inspiration.Thank you to all our listeners, guests, and supporters for being part of the Realities Remixed journey. We wish you a fantastic summer and look forward to bringing you even more thought-provoking conversations when we return in September for Season 6!TLDR00:27 – Season 5 reflections and key trends02:38 – Summer observations and random interruptions05:01 – From Cloud Realities to Realities Remixed08:05 – Winning 3 Global Marketing Awards10:50 – Esmee's journey and what's next14:05 – Technology trends revisited15:20 – Cybersecurity and investment challenges18:34 – Scaling AI beyond pilots25:41 – The reality of business transformation 33:35 – AI governance, agents, ethics, and the future of work47:00 – Knowledge retention and collaboration49:20 – Hardware innovation for AI51:17 – Macro trends and standout guests57:45 – Digital sovereignty and resilience1:08:00 – Why systems thinking must change1:12:00 – The Octopus Organisation1:18:24 – Summer plans and what's aheadHostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Plus: Oil prices approach $100 a barrel as tensions continue to escalate between the U.S. and Iran. And Tesla shares fall after hours following earnings report. Imani Moise hosts. Sign up for WSJ's free What's News newsletter. An artificial-intelligence tool assisted in the making of this episode by creating summaries that were based on Wall Street Journal reporting and reviewed and adapted by an editor. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What if your MCP server shipped with its own manual? Angie Jones, VP of Developer Experience at the Agentic AI Foundation, joins William and Eyvonne to break down the Skills Over MCP working group effort, which delivers Agent Skills through MCP’s existing resources primitive (think voice over IP, not skills versus MCP). Angie shares her... Read more »

Guest: Dr. Mike Farrar, Booz Allen HamiltonWeather forecasting has come a long way—from hand-drawn maps and limited observations to a world driven by supercomputers, satellites, and real-time data. But as technology continues to evolve, so does the challenge of making forecasts faster, smarter, and more useful for the people who rely on them every day. Today on Weather Geeks, we're joined by Dr. Mike Farrar, whose career has spanned research, operations, and leadership across the meteorological community. His company has been tasked to help modernize the National Weather Service, and with that he's helping shape what the future of forecasting could look like for both meteorologists and the public alike. We'll talk about the biggest challenges facing weather operations today, how emerging technologies like AI and cloud computing are changing the forecasting landscape, and why communication and public trust remain just as important as the science itself.Chapters00:00 Introduction and Career Background of Dr. Mike Farrar01:30 The Evolution of Weather Forecasting Technologies04:18 Transformational Advances in Meteorology09:15 The Private Sector and Meteorology's Growth12:16 Break 112:19 The Impact of AI and Cloud Computing19:28 Modernizing the National Weather Service22:55 The Role of Human Forecasters in the Age of AI26:51 Break 228:01 The North Star of Meteorology: Science and Service30:18 Skills for Future Meteorologists33:50 Embracing Change in the Meteorological Field34:29 Closing Remarks and Resources ResourcesBooz Allen Hamilton - https://www.boozallen.comNOAA's National Centers for Environmental Prediction - https://www.weather.gov/ncep/American Meteorological Society - https://www.ametsoc.orgAWIPS (Advanced Weather Information Processing System) - https://vlab.noaa.gov/web/nws-heritage/-/introducing-awipsNCAR (National Center for Atmospheric Research) - https://ncar.ucar.eduGuest linksLinkedIn - linkedin.com/in/mikefarrar-wxSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What if your MCP server shipped with its own manual? Angie Jones, VP of Developer Experience at the Agentic AI Foundation, joins William and Eyvonne to break down the Skills Over MCP working group effort, which delivers Agent Skills through MCP’s existing resources primitive (think voice over IP, not skills versus MCP). Angie shares her... Read more »

Topics covered in this episode: django-orjson Best Django Redis configuration for speed and size Linus Torvalds puts the foot down against Anti-AI Kernel Maintainers Django Steering Council backs the Triptych Project 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. Michael #1: django-orjson Adam Johnson dropped django-orjson - drop-in replacements for the Django and DRF pieces that touch JSON, swapping stdlib json for orjson, the Rust-based library. Headline numbers: 10x faster serialization, 2x faster deserialization. The interesting question is why this needs to be a package at all. pip install orjson is the easy part. Adam's actual pitch: adopting it "isn't easy, especially when your framework uses json in many different parts." Django scatters JSON across JsonResponse, the test client and test case classes, the json_script template tag, and more. There's no single hook to grab, so you get a library that catches them all. Adam is refreshingly honest about the scale of the win. His words: "While database queries tend to dominate the typical Django application's runtime, the time spent in serialization and deserialization can still be significant." He calls it "a nearly free performance win" - not "this will 10x your app." That's a claim about cost, not magnitude, and it's worth keeping those straight. Worth flagging what the post doesn't cover: caveats. There are none in the article, but orjson has real ones. Django and Flask both render datetimes as RFC 822 HTTP-date (Wed, 15 Jul 2026 12:00:00 GMT); orjson does ISO 8601. It can't do ensure_ascii, it rejects NaN and Infinity (which stdlib happily emits), and it raises on Decimal. If you've got a JS client parsing dates, that's a wire-format change. Who should actually take this? If you're a DRF shop shoveling JSON all day, yes - it's cheap and it's real. If your app mostly renders HTML templates, you're optimizing a slice of runtime that's already near zero. The problem Adam's package solves doesn't exist in Flask or Quart. They already centralize every JSON operation - jsonify, request.get_json(), the test client, the |tojson filter - behind one provider object at app.json. So there's no library to install. It's about ten lines: import orjson from quart.json.provider import JSONProvider # or flask.json.provider class OrjsonProvider(JSONProvider): def dumps(self, obj, **kwargs) -> str: return orjson.dumps(obj).decode() # provider must return str def loads(self, s, **kwargs): return orjson.loads(s) app.json = OrjsonProvider(app) The numbers on talkpython.fm Evaluated it, measured it, and skipped it. The biggest JSON payload we serve is our MCP server returning a cached episode transcript, about 139 KB. Swapping the provider saves 0.119 milliseconds per request. That total response takes 1.1 ms We got 4.1x, not 10x - and the reason is the good lesson. Payload shape decides your speedup. The 10x is for structure-heavy data, lots of small keys where stdlib burns time in Python-level dispatch per item. Our hot payload is one giant transcript string, so the work is escaping and memcpy Calvin #2: Best Django Redis configuration for speed and size Peter Bengtsson revisits a classic: his 2017 "Fastest Redis configuration for Django" benchmark now has a 2026 update posted this week. The 2017 post pitted django-redis serializers (json, ujson, msgpack, pickle) and compressors (zlib, lzma) against each other; conclusion was msgpack + zlib as the sweet spot - avoid the json serializer, it's fat and slow. The 2026 update narrows focus to just compressors: default (no compression), zlib, lzma, and newcomer zstd. New results: lzma compresses best but is slowest; zstd is the fastest compressor on Ubuntu; differences between them are very small. Big takeaway across both: compression buys you a lot of space (2–3.5x smaller) for very little speed cost - worth it for Redis where memory is the constraint. Caveat from the author: results depend heavily on your data - his test stores short strings of numbers, so benchmark your own workload. Michael #3: Linus Torvalds puts the foot down against Anti-AI Kernel Maintainers Write up on Ars. Really good coverage by Maximillian: Time to wake up (for some) Torvalds said that “Linux is not one of those anti-AI projects, and if somebody has issues with that, they can do the open-source thing and fork it. Or just walk away.” I agree with Max, putting your head in the sand and waiting for AI to go away will likely mean you won't be working professionally in software development in the coming years. The statement came amid a lengthy thread arguing about the use of Sashiko, an “agentic Linux kernel code review system” that its creators claim can, in tests, independently find 53.6 percent of the bugs that would end up being fixed by human coders in later commits. “We're not forcing anybody to use [LLM tools], but I will very loudly ignore people who try to argue against other people from using it,” Torvalds said. “Anybody who points to the problems at AI had better be looking in the mirror and pointing at themselves at the same time,” Torvalds wrote. Calvin #4: Django Steering Council backs the Triptych Project Django Steering Council issued a Letter of Collaboration backing Carson Gross & Alex Petros's funding bid for the Triptych Project - three proposals to make HTML more expressive natively, in every browser. The three additions: PUT/PATCH/DELETE methods for forms, button actions (buttons that fire HTTP requests without a wrapping form), and partial page replacement. Distills the core ideas from HTMX/Unpoly/Turbo into the HTML standard itself - no JS, no library, nothing to ship or maintain. Current focus is button actions (WHATWG #12330): Logout instead of wrapping a button in a form. Relevant to Django directly - think the admin submit row and disguised delete links; Django 6.0's template partials were already inspired by these patterns. How to help: companies can send non-binding letters of support on letterhead; individuals can read the proposals and weigh in on the WHATWG issues. Extras Calvin: DOOMQL - A playable first-person shooter whose framebuffer is a SQL query. Michael: Granian 2.7.9 fixes WSGI threadpool scheduler starvation/underscaling Welcome Calvin post Joke: Solving all bugs

Domo and AWS reveal how AI agents freed sales reps from 20 hours of weekly busywork, turning scattered data into real-time coaching and forecasting.Topics Include:Domo and AWS teams introduce today's session on AI agents in sales.Topic: using AI agents to transform sales operations, from insight to action.IT teams increasingly asked to turn data into actionable outcomes, not just access.Domo's CRO wanted AI agents to boost sales rep efficiency significantly.Reps act like "archaeologists," digging through scattered systems for basic context.This digging eats roughly 20 hours weekly, half of reps' time.Goal: personal AI agent per rep, understanding their book of business.Live demo begins: agent app surfaces urgent items needing attention.Agent tracks deal milestones, timelines, and forecasts from call and email data."Deal coach" feature grades rep performance and suggests next actions.Agent tone can be tuned from gentle to direct, aiding tough feedback.Architecture overview begins: building an AI-ready data foundation first.Data from CRM, calls, and emails flows into a cloud warehouse.Two agents built: automated deal analysis and personalized deal coach.Agents write insights back to CRM, preserving human edit control.Recipe: build foundation, activate with agents, distribute to people.Governance must be embedded throughout, not bolted on afterward.Second example: Fogo do Chão uses AI to analyze restaurant reviews.AWS architecture explained: Domo runs on Bedrock, defaulting to Anthropic models.Q&A: sales team adoption was immediate and enthusiastic post-rollout.Participants:Jason Longhurst – Head of Product Marketing, DomoAman Tiwari - Sr Solutions 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/

Prediction market Kalshi moves into biotech, new study findings show no clear electromagnetic wave cancer risk in mobile phone use, Microsoft's 13-inch Surface Laptop struggles with 8GB of RAM. MP3 Please SUBSCRIBE HERE for free or get DTNS shows ad-free. A special thanks to all our supporters–without you, none of this would be possible. IfContinue reading "SpaceX In Talks To Provide Cloud Computing Power For DoD AI Projects – DTH"

Three AWS Summits across the US — LA on June 10, NYC on June 17, and Washington DC on June 30–July 1 — brought a wave of announcements that all orbited a single thesis: the age of agentic AI is here, and the winners will be organizations whose agents get smarter with every decision they make. In this episode, AWS Managing Director, North America Solutions Architecture, Geries AbouAyash joins hosts Malini and Amit to break down four major Summit announcements — Graviton5, AWS Context, AgentCore Harness, and AWS Continuum — spanning next-gen CPUs for agentic workloads, a governed knowledge graph that gives agents organizational memory, production-grade agent deployment, and security at machine speed. The throughline: in the age of Agentic AI, the challenge is no longer building intelligence but operationalizing it — and as foundation models become universally accessible, competitive advantage shifts from who has the model to who can run AI securely, efficiently, and at enterprise scale.https://aws.amazon.com/blogs/aws/top-announcements-of-the-aws-summit-in-new-york-2026/https://www.aboutamazon.com/news/aws/aws-graviton-5-cpu-amazon-ec2https://aws.amazon.com/blogs/machine-learning/context-intelligence-for-your-data-and-ai-agents-at-scale/AWS Hosts: Amit Narayanan & Malini ChatterjeeEmail Your Feedback: rethinkpodcast@amazon.com

Quantum materials discovery shows how quantum computing can create real value in industry by working alongside AI, advanced computing, and experiments to better understand materials, improve decision-making, and accelerate innovation at scale, ultimately helping deliver practical, measurable progress for the energy transition.This week, Dave, Esmee, and Rob are joined by co-host and quantum expert Phalgun Lolur, together with Jonathan Owens, Senior Scientist in Computational Materials Physics at GE Vernova to explore how quantum computing could reshape materials discovery and why that matters for the future of energy.  TLDR00:00 – Introduction01:50 – Hang out: The wet-bulb thermometer03:20 – Dig in: Technology Convergence and the Link to Quantum11:30 – Conversation with Jonathan Owens44:26 – Exciting to see how the quantum landscape matures and the magic wand for magnetismGuestJonathan Owens: https://www.linkedin.com/in/jonathan-r-owens-phd/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/Co-host Phalgun Lolur:  https://www.linkedin.com/in/phalgun-lolur/ 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

Topics covered in this episode: The trusted-publishing debate: how to do it right vs. why you shouldn't trust it JupyterLab 4.6 and Notebook 7.6 are out! Tau – new small, readable terminal coding agent Django Tasks and Django 6.1 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, 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: The trusted-publishing debate: how to do it right vs. why you shouldn't trust it https://snarky.ca/how-to-publish-to-pypi-using-github-actions-securely/ (Brett Cannon) and https://blog.yossarian.net/2026/07/07/You-shouldnt-trust-trusted-publishing (William Woodruff) Trusted Publishing (PyPI's OIDC-based auth scheme, also now used by npm, RubyGems, crates.io, NuGet) replaces long-lived API tokens with short-lived, auto-scoped credentials tied to CI/CD machine identity. Yossarian's post: it's purely an authentication mechanism between a machine identity and a package — it says nothing about package safety or quality. PyPI deliberately avoids any "verified/trusted" badge for it, unlike its verified-URL checkmarks. Same logic applies to PyPI attestations: anyone can sign with any machine identity they control, so an attestation's presence isn't itself a trust signal. Bottom line from that post: don't confuse "trusted" (machine-to-machine) with "trustworthy" (human judgment about the package). Snarky.ca's companion piece is more practical: given GitHub Actions compromises in the news, the real fix is 3 concrete steps — run zizmor to lock down workflow permissions/checkout credentials and pin actions to commit hashes, adopt Trusted Publishing to eliminate stored PyPI tokens, and require manual approval via a GitHub environment before any publish job runs. Takeaway for listeners: Trusted Publishing is good hygiene for how you authenticate to PyPI, but it's not a substitute for securing your CI pipeline itself — or for actually vetting the packages you install. Michael #2: JupyterLab 4.6 and Notebook 7.6 are out! Michał Krassowski's rundown - a chunky minor release: 68 features, 97 bug fixes, 95 contributors, one of the biggest ever. Scratchpad console (Notebook 7.6 headliner) - a console next to your notebook sharing its kernel, for throwaway experiments. Ctrl+B. Jump to last-edited cell - new commands hop through recently edited cells. File browser glow-up - Date Created column, editable breadcrumbs with Tab-completion, and Open in Terminal. Debugger - sources open in the main area, floating step/continue overlay, live kernel-sources filter. Custom layouts (Lab) - activity bar top/bottom, draggable panels, four-way tab splits, per-panel Ctrl+scroll zoom. ~5x faster extension builds - webpack → Rspack, and jupyter-builder means no full Lab install needed to build extensions. Keyboard/a11y - add shortcuts from the UI (no JSON), Find & Replace in Edit menu (Ctrl+H). Calvin #3: Tau – new small, readable terminal coding agent Tau – new small, readable terminal coding agent (Python 3.12+), built as both a working tool and a teaching project for how coding agents work under the hood Install via uv tool install tau-ai, pipx, or pip; ships a tau CLI Three-layer architecture: tau_ai (provider-neutral model layer) → tau_agent (reusable "brain": messages, tools, events, loop) → tau_coding (CLI/TUI, file & shell tools, sessions) Supports OpenAI, Anthropic, OpenAI Codex, OpenRouter, Hugging Face, and custom/local OpenAI-compatible endpoints Built-in tools (read/write/edit/bash), durable JSONL sessions with resume/branching, project instructions via AGENTS.md, and context compaction Core harness is UI-agnostic — same brain can power the TUI, print mode, or a custom frontend — usable as a standalone library too Michael #4: Django Tasks and Django 6.1 Django 6.0 finally ships first-party background tasks (django.tasks) - out of Jake Howard's DEP 14, accepted May 2024, after two decades of everyone bolting on Celery/RQ/Huey. It's an API, not a worker. Django handles task definition, validation, queuing, and result storage - it does not execute them. You bring the backend. The default backend traps people. ImmediateBackend runs tasks inline on the request thread and blocks until done - so out of the box .enqueue() backgrounds nothing (a 5-second task means a 5-second response). The other built-in, DummyBackend, runs nothing at all. Both are dev/test only. Nice API otherwise: slap @task on a function, call .enqueue(), get back a TaskResult you look up later by id - with async twins like aenqueue(). Gotcha: args and return values must survive a JSON round-trip, so a tuple sneakily comes back as a list. The community local backend to know: django-tasks-local by Chris Beaven (SmileyChris). A ThreadPoolExecutor backend that gives real background threads with zero infrastructure - no Redis, no Celery, no database - plus a ProcessPoolBackend for CPU-bound work → github.com/lincolnloop/django-tasks-local Its catch: results live in memory, so pending tasks vanish on restart or deploy. Great for dev and low-traffic production; for persistence, drop to Jake Howard's django-tasks (DatabaseBackend + worker command). Extras Calvin: Fixing the dictionary with Python 3.14 — Hugo van Kemenade stumbled on - and got fixed - a markup bug in the OED's own citation of a 1706 use of the pi symbol. Michael: Bunny DNS is now free Jokes: What's the object-oriented way to become wealthy? Inheritance To understand what recursion is... You must first understand what recursion is 3 SQL statements walk into a NoSQL bar. Soon, they walk out They couldn't find a table.

Curious how AI can query your enterprise data without moving it or making things up? AWS and Teradata break down a trustworthy analyst agent built for real production use.Topics Include:Neha Wadhera (AWS) introduces Trinath Yarlagadda and the Teradata Analyst AgentEnterprise AI data prep is costly, stalling most orgs at experimentationAgent answers plain-English questions via traceable SQL, zero data movementBarrier removal drives 3.7x ROI and 40% productivity gainsHealthcare demo setup: hospital COPD readmissions, ~$10K cost per incidentFour design principles: traceability, no data movement, deterministic-first, governance as codeMain orchestrator agent plans, writes SQL, calls Teradata MCP serverComplex questions escalate to a context-isolated data scientist agentBuilt on Claude Agent SDK, running Bedrock Claude Sonnet/Haiku/OpusLive demo: COPD readmission rates explored through iterative agent reasoningDelegation demo: data scientist agent runs in-database analysis, surfaces factorsPre/post tool hooks log every step and cost to CloudWatchAgent hosted on Amazon Bedrock AgentCore, fully serverless and scalableAgentCore delivers runtime, memory, identity, and observability out of the boxLessons learned: guardrails first, deterministic ops, multi-agent registry, ongoing evaluationParticipants:Trinath Yarlagadda – Principal Solution Architect – Agentic AI, TeradataNeha Wadhera – Sr Solutions Architect, 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/

Coding agents have gotten really good at one kind of work. You scope a feature, edit some files, run the tests, ship it. It all happens on disk. But that is not how data work feels. You load something, you look at it, you run a cell, you watch how it responds, and you decide the next move from whatever is sitting in memory. And until now, your agent couldn't see any of that. It only saw the files. Never the live state. This episode, that wall comes down. marimo pair drops a coding agent right inside a running notebook, with full access to every variable Python is holding in memory. The notebook becomes a shared canvas. You point, it runs the code. You tell it to zoom in on the Picasso paintings, and the chart just updates. No MCP tools to wire up, no schema to describe. Just Python, and an agent that can finally see what you see. Trevor Manz is back to walk us through it. Episode sponsors Sentry Error Monitoring, Code talkpython26 Talk Python Courses Links from the show marimo pair: marimo.io/pair Course transcripts announcement: talkpython.fm/blog anywidget: Jupyter Widgets made easy: talkpython.fm marimo: marimo.io blog: marimo.io GitHub: github.com given this: martinalderson.com llms.txt: talkpython.fm mcp: talkpython.fm cli: talkpython.fm open issues: github.com Discord: marimo.io Marimo Pair: marimo.io OpenCode: opencode.ai AI Tooling for Software Engineers in 2026: newsletter.pragmaticengineer.com Watch this episode on YouTube: youtube.com Episode #555 deep-dive: talkpython.fm/555 Episode transcripts: talkpython.fm Theme Song: Developer Rap

You ask an AI a question and it answers with total confidence. Most of the time, a confidently wrong answer is just an annoyance. But what if the question is medical, and there's a real patient on the other end? In that world, a hallucination isn't a bug, it's a patient-safety event. Sumit Gundawar is a London-based software engineer who builds the clinical platform for a UK longevity and aesthetic-medicine clinic, and his whole argument is that in high-stakes AI, the model is the easy part. Earning trust is the real engineering. We dig into grounding, refusal logic, human-in-the-loop design, and the messy frontier of longevity and biohacking, plus a live demo of an assistant that refuses to answer when it can't back up the claim. Let's get into it. Episode sponsors Six Feet Up Talk Python Courses Links from the show Guest Sumit Gundawar: linkedin.com Course transcripts announcement: talkpython.fm/blog Sumit Gundawar - JAX London Speaker: jaxlondon.com Anthropic: anthropic.com OpenAI Platform: platform.openai.com Anthropic: anthropic.com LangChain: langchain.com OWASP: owasp.org Pydantic: pydantic.dev EU AI Act - Regulatory Framework: digital-strategy.ec.europa.eu HIPAA - HHS: www.hhs.gov NHS: www.nhs.uk Llama: llama.com Qwen - QwenLM on GitHub: github.com OpenAI Platform: platform.openai.com Hugging Face: huggingface.co Llama: llama.com Granola: www.granola.ai HIPAA - HHS: www.hhs.gov CodeRabbit: www.coderabbit.ai Cursor Origin: cursor.com GitHub Status: www.githubstatus.com Midjourney Medical: www.midjourney.com Neko Health: www.nekohealth.com CERN: home.cern ATLAS Experiment: atlas.cern Watch this episode on YouTube: youtube.com Episode #554 deep-dive: talkpython.fm/554 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Topics covered in this episode: dust - a better du Hermes Agent: The AI agent that grows with you llm-coding-agent 0.1a0 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, 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: dust - a better du du + Rust = dust - a fast, visual, intuitive disk-usage CLI Run dust and immediately see the biggest directories and files without piping through sort, head, or awk Smart recursive output focuses on what matters instead of dumping every folder Colored bars show relative size and parent/child hierarchy, making “where did the space go?” obvious Perfect for Python projects bloated by .venv, caches, Docker volumes, downloaded datasets, and local AI models Install via brew, cargo install du-dust, conda-forge, Scoop, Snap, deb-get, or GitHub releases Calvin #2: A Way better ARchive format for Python packaging war - new archive format spec from Astral (same team as uv/ruff), v0.0.2, still no binary encoding defined yet Header-Index-Store layout: header IDs the file, index maps names to store offsets, store holds compressed data Index uses a finite-state transducer (FST) to dedupe common path prefixes across entry names Supports three entry types (file, directory, link) and three compression modes (store/DEFLATE/zstd), plus an "executable" metadata flag Unpacking is atomic - writes to a temp dir, then renames into place, so a failed extract never leaves a half-unpacked directory Strict name-segment rules (no NUL/control chars, no leading/trailing whitespace, blocks Windows-reserved names like CON/PRN) to avoid path traversal and cross-platform footguns Michael #3: Hermes Agent: The AI agent that grows with you Hermes Agent is an open-source, Python-built AI agent framework from Nous Research - think ChatGPT-style assistant, but connected to your tools, files, shell, browser, calendar, memory, and messaging apps I'm using it in Discord as a long-running agent conversation, not just a one-off chatbot session Hermes can connect through a gateway to platforms like Discord, Telegram, Slack, WhatsApp, email, webhooks, and more - so the same assistant can follow you across surfaces In my setup, I can send Hermes voice/text from Discord, keep project context across turns as threads, and ask it to actually do things: read GitHub repos, run commands, edit files, schedule calendar events, generate drafts, and verify results A fun workflow: I can trigger one-shot actions from an Apple Watch shortcut - dictate a request, send it to Hermes, and have the agent execute it asynchronously Hermes has persistent memory, so it can remember durable preferences and facts - for example, how I like my research formatted It also has “skills,” which are reusable procedures the agent can load later, so Hermes can self-improve over time instead of rediscovering the same workflow repeatedly It supports scheduled jobs / cron-style automations, so it can proactively watch for releases, send summaries, run checks, or remind you about things It's provider-agnostic: OpenRouter, Anthropic, Google, xAI, local models, Nous Portal, and others The big idea: Hermes turns an LLM from “a chat box I visit” into “an agent I can reach from anywhere that knows my workflows and can take real actions and learns over time.” Calvin #4: llm-coding-agent 0.1a0 Simon Willison built a Claude/Codex-style coding agent on top of his llm library, using an alpha of the llm package plus his python-lib-template-repo Built almost entirely via prompted TDD - asked an agent to write a spec.md, then commit + implement with red/green tests, occasionally hitting a real OpenAI key to sanity-check Shipped to PyPI as an alpha: uvx --prerelease=allow --with llm-coding-agent llm code Tool set mirrors familiar coding-agent primitives: read_file, edit_file (exact string replace + diff), write_file, list_files, search_files, execute_command Also exposes a Python API - CodingAgent(model="gpt-5.5", root=..., approve=True).run(...) - which Simon didn't ask for but got anyway Demo: llm code --yolo told GPT-5.5 to build a SwiftUI CLI clock; model correctly noted SwiftUI isn't really CLI-friendly and still produced an ASCII-art time display Extras Calvin: Slides, but for developers https://sli.dev/ Wanna reduce your token usage…. only issue is that its lossy https://github.com/teamchong/pxpipe PEP 772 - Python Packaging Council inaugural election dates set, nominations open July 28, voting September 1-15 Michael: What the pls? revisited! Joke: Min requirements for Linux

Malcolm Matalka joins William and Eyvonne to challenge the narrative that Infrastructure as Code (IaC) is dead. Malcolm argues that the real value of IaC was never the syntax, but state and governance. Together they examine whether the state was a file problem at all, or a distributed systems problem in a JSON costume. Episode... Read more »