tech

2025-12-09 · open the original ↗

• A degree was the lower-risk route past hiring bias. One speaker, a Black woman, says she expected higher scrutiny than her peers in hiring and chose a CS degree over a bootcamp to make hiring as easy as possible. She argues that despite industry lip service about skills mattering more than background, employers overwhelmingly hire people with degrees and pedigree, though bootcamps worked for some.

2025-12-08 · open the original ↗

• Draft angry emails outside your email client, then wait. Beasley, host of the Modern CTO podcast, credits Mark Porter, CTO of dbt Labs, with the advice to write emotionally charged emails in Evernote, not as a draft you might accidentally send, and review them once back to neutral. He says his not-send rate for such emails is "basically 100%", because they read like "a crazy person" wrote them.

2025-12-07 · open the original ↗

• Audit quarterly whether your time matches what matters. Beasley credits Kyle, whom he interviewed as Verizon's incoming CTO after a cold email to the outgoing CTO, with a recurring quarterly calendar event to list everything he actually does daily against everything that needs to get done, then reconcile the two. The point is to catch time spent on work that doesn't serve current goals, and Beasley says he has done this for several years.
• The host tracks daily leading and lagging habit metrics. The host describes a daily habit spreadsheet with a quarterly review, pairing inputs such as hours in bed and drinks with outcomes such as waking refreshed, and says drinks have a big negative effect on sleep quality.

2025-12-06 · open the original ↗

• In chaos, keep your world very small. Beasley ranks this as the best leadership advice from his roughly thousand Modern CTO episodes. It came from astronaut, pilot and surgeon Tom Marshburn, who Beasley says flew on Elon Musk's first crewed flight: at an emergency crash site or on a spacewalk, Marshburn ignores the surrounding chaos and focuses only on the next stitch, latch or knob. Beasley says he has applied it for three or four years in stressful situations with family, kids and work, and it has held every time.

2025-12-05 · open the original ↗

• Check the airport's official site for its real Wi-Fi SSID. Asked about honeypot networks, one speaker says fake Wi-Fi appears in many public spaces and advises confirming the SSID on the airport's website rather than trusting a plausible name such as an "airport guest" network, a habit the speaker recommends generally.

2025-12-05 · open the original ↗

• The host revived his idle Dream Wall to test unannounced software. He says the office-mounted UniFi Dream Wall had not been on since about March or April 2023. He needed several gateways for the testing, which he promises to detail soon.

2025-12-05 · open the original ↗

• Knowing scrolling is harmful does not stop anyone doing it. One speaker, a neuroscientist, admits to still scrolling Instagram when stressed, tired or anxious, and so never tells people simply to stop. The advice instead is to replace some scrolling with something generative, including creating useful content on the other side of the algorithm.

2025-12-05 · open the original ↗

• Many good startup ideas live in legal gray areas. He cites OpenAI's crawling of the entire web without permission as arguably fair use or "massive copyright theft," and recalls Lyft's founders fearing jail the week before launch, since what became Lyft and Uber was then effectively illegal.
• Laws often get rewritten once consumers clearly benefit. He argues that finding laws written before a big tech shift, laws that no longer reflect reality, can be valuable for founders, since the legal environment tends to bend once it's clear the end user wins.

2025-12-05 · open the original ↗

• Removing the driver transforms the cost per mile. The host argues that robotaxis still have to be bought, charged, cleaned, insured and maintained, but carry no hourly driver cost and can run far more hours than an idle private car, spreading capital cost over many more trips. He says Waymo rides can currently cost more than Uber or Lyft in San Francisco, but predicts per-mile prices will fall sharply at scale, which will tempt city households that spend roughly 15% of their budget on vehicle ownership.
• Robotaxis appear far safer than human drivers. The host cites Waymo safety reports showing serious-injury crashes per million miles roughly 10 times lower than human benchmarks, and a Swiss Re study finding about a 90% reduction in bodily-injury and property-damage claims. His inference is that insuring a human-driven car could become extremely expensive within our lifetime.
• Cheap rides will cause congestion without road pricing. He calls congestion a textbook externality and points to Manhattan's congestion charge cutting incoming traffic by about 10% in its first months while funding transit. He argues dynamic road pricing, perhaps framed as a robotaxi fee, will be essential to keep downtowns from gridlocking.
• Driving jobs will shrink over one to two decades. The host counts roughly half a million US taxi, chauffeur and shuttle jobs, another half million bus drivers and about 3 million truck drivers, several percent of the workforce. He says reskilling and regional transition plans are needed, and expects, from historical automation, that new and more stimulating jobs will appear.
• Fewer private cars could free a large urban land dividend. He says US downtowns devote 20 to 30% of land to parking, some central districts nearly a third, which could become housing, parks, offices, wider sidewalks and bike lanes, though cheap autonomous commutes could also fuel sprawl. He notes Baidu's Apollo Go, Pony.ai and AutoX run large services in Chinese megacities, with Apollo Go delivering millions of rides a quarter, and urges listeners to look for the "robotaxi equivalents" in their own industries.

2025-12-05 · open the original ↗

• Modern software bloat dwarfs lean native executables. One speaker contrasts the other's executables of 2 to 12 MB with websites whose PNGs are bigger, citing a 25 MB page at The Verge, and a 500 MB download needed just to control the lights on the podcast microphone.

2025-12-04 · open the original ↗

• Esolangs are an art form, not just puzzles or jokes. Temkin's book 44 Esolangs (MIT Press) is pitched at both programmers and the art world, using words like "monograph" to signal an art book; Temkin argues listicle-style coverage hides languages such as Piet, which lets programmers develop their own visual style in code.
• Each language explores an edge of what code can be. Temkin traces lineages: False's single-character commands led to Brainfuck and to Befunge, which reads in any direction and was meant to be hard to compile, and Piet carries Befunge's flow into colour. Some of the book's 44 are deliberately unrealisable; the book gives all the prompts first and the realisations second, after Sol LeWitt's split between a work's concept and its idea.
• AI gives the most mediocre answer to a creative prompt. Fed one of the book's prompts, for code written as feeling, Claude produced something close to the existing Shakespeare language; Temkin tells students to use AI to generate code but leave it no creative decisions.
• Several languages undermine the programmer's sense of control. Folders, which is Turing complete, encodes programs in empty folders read alphabetically, inspired by Whitespace; Past Tense converts a program's verbs to past tense so it must never run again; Stroll needs three walkers whose site-specific routes, such as tree species, make results change with place and time.
• Non-English languages challenge English's dominance in code. Temkin cites Ramsey Nasser's Arabic Lisp, whose tooling exposed right-to-left biases; Yorlang, in Yoruba, which Temkin says could serve mainstream use; and a single-glyph-per-line language being designed with Jon Corbett. Intercal (1972), whose PLEASE count decides whether a program runs, is the first recognised esolang; Don Woods recently found its original compiler code.

2025-12-04 · open the original ↗

• Wireless is never magic; there is always a cable behind it. One speaker, who works in airport IT, tells visiting students that Wi-Fi and cellular run back to towers and data centres over cable. The flight information displays are on the same interconnected system, cabled from one terminal to another.

2025-12-04 · open the original ↗

• A memory palace fixes the order of a comedy set. Beasley says remembering individual three-minute bits was easy but their sequence was not, so he adopted the memory-expert technique of attaching each joke to a vivid image along a walk through his house, such as a front door that is a giant fuzzy beard for his beard joke. He says the brain remembers familiar spatial paths well, the crazier the image the better, and that on stage before 500 people he can recover a lost place by "looking around" the room he is in mentally.
• Slides should be pictures, not text. The host, applying the idea to an upcoming 10-minute keynote, urges listeners never to put just text on slides and to use an image instead.

2025-12-04 · open the original ↗

• An open-source Zig project led directly to a job. One speaker says the CTO of Tuple starred their Zig version manager, zigup, on GitHub, which led them to the company's performance-focused pitch and a job as its Linux engineer. The CTO knew they were a Zig person, and the speaker says they try to "sneak Zig in" where they can.

2025-12-03 · open the original ↗

• Passive PoE sends power without negotiation, so it can fry devices. Standard PoE (802.3af, 802.3at PoE+, 802.3bt PoE++) has the device and switch agree on power and supplies none to non-PoE devices. Passive PoE keeps voltage on the line constantly, so plugging in something like an Ethernet tester could destroy it.
• Passive PoE survives mainly in older wireless-ISP gear. The host says it predates the standard and mostly powered point-to-point and point-to-multipoint antennas. Ubiquiti's discontinued 8-port 150 W UniFi switch let each port be set to standard PoE or 24 V passive, which he says he loved.

2025-12-03 · open the original ↗

• The cultural obsession with finding one purpose is harmful. One speaker, researching a book, found mentions of "finding your purpose" in books up 700% over two decades. The first problem named is that it pushes people to tie their identity and self-worth to one thing, so they lose that self-worth when it fails.

2025-12-03 · open the original ↗

• Mark filters tech news through aggregators, skipping Hacker News's noise. Mark has read Techmeme since about 2007, adds consumer sites such as The Verge, and only scans Hacker News, opening around 20 tabs to read over lunch; The Information comes through Microsoft's employee library subscriptions.
• Curated daily newsletters are Mark's way of keeping up with AI. Mark names The Rundown AI (a five-person team), Superhuman (one person, Zain Kahn), The Neuron (Grant and Corey), the less frequent The Batch from Andrew Ng's deeplearning.ai, and Turing Post, mostly free and ad-supported.
• Mailing lists have become the new RSS, Hanselman argues. He says distributed, pull-based RSS has given way to email newsletters that are easy to monetise but must be dug out of an inbox, and worries that blogging alone now goes unread; his Feedly holds 57,000 unread posts from the feeds he imported when Google Reader closed.
• Their own old newsletters and blogs are a valuable archive. Mark shows a 2001 Sysinternals newsletter at 33,000 subscribers, peaking at 80,000–90,000, and Hanselman his 2003 blog posts, including links to Mark's tools now broken after redirects; Hanselman says he blogged to learn and keep track of things.
• Mark fixed ZoomIt's LCD rendering in three days with AI help. Hanselman says the AI Tour's producer wanted ZoomIt but its default zoom looked poor on LCD screens; after Hanselman messaged Mark, the smoothing fix arrived within three days, written with help from an AI assistant.

2025-12-03 · open the original ↗

• Laughs per minute is the metric that transcends comedic taste. Beasley, who started stand-up about 10 or 11 months before recording, says professional full-time comedians hit four to five laughs per minute, so he set out to write material at that rate and says he has largely done so. He records every set, has Gemini count laughs per minute, the only browser chatbot he found that would accept video (he says GPT and Grok wouldn't as of recording), and logs each performance in a spreadsheet with what worked, audience size and money made.
• AI as a writing coach modelled on a comedians' workshop. Beasley attended about 10 comedy writers' groups, modelled how the professionals gave each other feedback, and turned that into a saved prompt that suggests other perspectives on a joke, directions it could go and nearby double-meaning words. He adds that all laughs are not equal: duration and relative intensity matter, though he keeps his own measurement basic.

2025-12-03 · open the original ↗

• These agents answer natural-language questions about a site's content, within the asker's permissions. Giard says a SharePoint agent works over a site's documents, libraries and lists, and won't answer from documents the person asking can't access. Creating one requires site editing permissions and an M365 Copilot license; he notes a pay-as-you-go pricing model is also available.
• Every site already has a built-in agent that needs no setup. It opens from an icon at the top right of the site and offers suggested prompts. In the demo, "Summarize Recent Files" listed the most recently uploaded or edited files with a short description of each. Giard calls it "pretty useful right out of the box."
• A custom agent's purpose prompt sets its scope, structure and tone. The agent is created from "Create an Agent" in the same pane, with a name, an icon (the default can be replaced) and a purpose. Giard swaps the default purpose text for one that describes what each folder holds (books, concerts and theater reviews, as PDF drafts), tells the agent to answer only from those files, and asks for a formal tone that calls everyone "sir or ma'am". In the demo it used that form of address, tolerated a typo, kept context for follow-up questions, and linked each answer to its source PDF. Asked for three novels, it found only two reviews that were clearly novels.
• The agent is saved as a file you can edit later. It is stored in the site's Documents folder, and opening it always launches the chat in M365 Copilot. From the file's ellipsis menu you can edit the name, picture and prompt. When Giard changed the tone to casual ("call everyone buddy or pal"), the next answer called him "buddy". The agent also has an option to delete all Copilot history so it forgets earlier conversations.
• Share the agent by link; deleting it removes it permanently. Giard says the simplest way to share is to copy a link from the Share option, which gives the recipient access to the same chatbot. You can set the link's access settings or email it from there. The same menu deletes the agent, and he says it is then "gone forever".

2025-12-03 · open the original ↗

• Telling a programmer something is impossible guarantees they'll try. The speakers define nerd sniping as telling a programmer something cannot be done, so they drop everything to prove otherwise; one is told they were sniped into building AppVeyor. The clip also mentions a Windows port contributed to Mitchell Hashimoto's terminal, Ghostty.

2025-12-02 · open the original ↗

• An airport's IT scope is that of a city plus aviation. One speaker lists the airport's own fire and police departments, airlines, stores, water and restaurants, on top of FAA safety regulations. Anything with a chip needs a cable, so the speaker says they were probably consulted on it.

2025-12-02 · open the original ↗

• Laughs per minute, measured by AI, is Beasley's comedy benchmark. He says professional comedians hit four to five laughs per minute, records every set, has Gemini count laughs from the video, and logs each show's laughs, audience and pay in a spreadsheet. He turned his notes from about 10 comedy writers' groups into a saved writing-coach prompt, and credits this approach with an invitation onto Dry Bar comedian Jeff Allen's tour, about 20 dates through February, roughly 10 months after his first set.
• Amazon's AI-attributed layoffs are honest, and trimming is healthy. On the news that Amazon was targeting 30,000 corporate job cuts, which the host estimates at about 10% of its roughly 300,000 corporate staff, Beasley praises Amazon for saying outright that AI was a cause, when executives he interviews avoid it. He likens cuts to trimming a garden and says a firm Amazon's size likely has 10% or even 30% bloat, though he notes conflicting reports of 14,000 versus 30,000.
• People accept human error but not machine error. Beasley relays a point from former OpenAI go-to-market head Zack Kass: car crashes kill about 1.2 million people a year without outrage, yet one serious Waymo crash would bring "pitchforks in the streets." The host links this to a 2015 paper titled "Algorithm Aversion."
• Bias is inherent to intelligence, so mandate model transparency instead. Beasley argues that complaints about LLM bias are really arguments over whose group preferences get enacted. He favours legislating a "nutrition label" disclosing what a model was told after training, so buyers can choose among differently biased models. The host reports, unverified on air, that Grok's prompt was changed to align it with Elon Musk's views on certain topics; Beasley says it's too early for him to judge.
• In chaos, keep your world small; then audit your time. Beasley ranks astronaut and surgeon Tom Marshburn's advice first: focus only on the next stitch or latch amid chaos. Second is Verizon executive Kyle Malady's quarterly comparison of what he does daily against what matters, to which Beasley adds checking what you dislike doing so you can hand it off. Third is dbt Labs CTO Mark Porter's rule of drafting angry emails in Evernote and waiting, which Beasley says leaves almost all of them unsent.

2025-12-02 · open the original ↗

• Social media works like an artificial career leaderboard. One speaker argues it is not normal to see manicured versions of hundreds of lives, including classmates from 15 to 30 years ago. Since people are incentivised to share only successes, viewers inevitably ask why a peer is "up there", as if there were a ladder everyone was climbing.

2025-12-01 · open the original ↗

• Generative AI's next step is becoming social, not just smarter. Ackerman argues that investment has focused on replacing whole careers with AI, but the industry is slowly learning that results are usually better with a human involved. She cites image inpainting, which regenerates only a highlighted section, and Suno making its tool more interactive after learning that its best users want to make music themselves. Today's AI, she says, is like brilliant people who can't interact with others, and she hopes it becomes better at collaborating with humans.

2025-11-30 · open the original ↗

• GenAI products that leave users with nothing to do don't retain them. Ackerman calls this the "one hit wonder" problem: an app that transforms your photos may be enjoyed once or twice, but without control over the output people rarely come back, because they want to express their own ideas. She says investors and industry have been "very very slow" to see this.
• The leading chatbot wins through power users, not replacement. Ackerman argues ChatGPT's success comes from users who go deep and get better by using it; she reports hearing of people whose vocabulary expanded and writing style diversified. Her advice for convincing product managers is to explain why successful products succeed, and to show where the replacement paradigm fails.
• Optimizing AI to replace workers fails collectively. Ackerman argues that if everyone optimizes for themselves and there are no more human workers, "the entire economy collapses", so the "greedy principles" guiding the economy should not be assumed to keep working.
• Mainstream chatbots are convergent by design, not inherently uncreative. Ackerman frames creativity as a search over billions of possibilities that machines explore well, but says science fiction pushed labs toward an all-knowing oracle that returns the most expected answer. Creativity has to be built in from the start; her original three-person team at Wave AI managed it, so in her view OpenAI, Microsoft and Google could too, but their goal is to replace search rather than open minds.

2025-11-29 · open the original ↗

• Machine-generated variations unlocked her songwriting. Ackerman says that, trained like many musicians to play other people's music, her songwriting "blew up" once an early research prototype, built by her collaborator David, offered many ways to sing a short lyric. Wave AI followed in late 2017, and its third product, Lyric Studio, became the successful one; the host describes Wave AI's tools as used by millions.
• The lyrics tool suggests rather than writes, to build skill. Ackerman describes Lyric Studio as a writing box with suggestions on the side from Wave AI's own lyrics LLM, built from scratch and tuned to the user's topics and style. She says the aim is never the "correct" lyrics but widening options, and claims it makes users better pen-and-paper songwriters, an effect that lasts beyond using the software.

2025-11-28 · open the original ↗

• AI gave a usable starting point, not a finished answer. One speaker says AI helped them write a custom GPU shader, outside their expertise, that keeps screen capture on the GPU and does the YUV conversion there. The first output "kind of worked" but not well; they credit it with getting them to the finish line in reasonable time, and say all their users now spend less CPU capturing and sending the screen.

2025-11-28 · open the original ↗

• The airport is a landlord, so IT stops at the handoff. Tomlin, VP of IT systems and infrastructure at Philadelphia International, says her team maintains base infrastructure while tenants run their own; American Airlines, for which PHL is a hub, manages its own terminals. When Aeromexico was onboarded in June (a direct PHL–Mexico City route, her first new airline), her team extended the carrier's circuit from a central utility hub building to its nearest closet and handed off, with no visibility into the airline's networks.
• An airport is a mini city where everything runs on cable. She describes fire, police, water, retail and federal agencies on top of FAA-regulated aviation, and says anything "with a chip in it" that needs a cable involves her team, from runway lights to flight information displays wired from terminal A west to terminal F. The FAA tower is separate from the ground towers that take over once planes land.
• Closed networks and enterprise displays keep public systems locked down. Answering Hanselman's story of a friend hijacking a Chromecast menu board in Portugal, she says PHL uses closed, on-prem networks that do not touch the internet and enterprise displays without smart-TV connectivity, with a dedicated infosec team and repeated pen tests. Her advice to travellers is to check the airport's website for the official Wi-Fi SSID rather than trust a look-alike.
• Her proudest win is uptime passengers never notice. Because airports run 24/7, she counts redundancy that hides failures as the team's real success, alongside getting Aeromexico operational in time for its inspections. New capital projects keep adding sensors to the building, and she wants to pull that data and apply AI to it, weighed against whether the opex can be sustained on a government budget.
• Public-sector IT rewards curiosity and breadth over a lane. She moved from web developer to IT director at the Free Library of Philadelphia, then to the city-owned airport, which has an IT department of a little under 80, mixing city staff and contractors. She argues that government work exposed her to servers, cabling and cloud in a way a private job would not, that city airport jobs are publicly posted, and that the people running civic infrastructure need policymakers' support to maintain it.

2025-11-28 · open the original ↗

• Early-career developers face anxieties that compound on each other. One speaker, drawing on mentoring early-career engineers, lists AI, the reputed intensity of LeetCode-style interviews, and the shift from being graded against a standard at school to a career with no rubric. They say coaching through this means helping mentees accept that some of it is outside their control and make peace with it.

2025-11-28 · open the original ↗

• Google's new model has retaken the frontier, at least for now. The host reports Gemini 3 Pro debuted first on LMArena across text, vision, coding and web development, ahead of xAI's Grok 4.1 and OpenAI's GPT-5-class models, and that the LMArena team called it the first model to break an Elo of 1500. He ties this to the time of recording, after Google trailed OpenAI and then Anthropic for about three years.
• The biggest gains are on the hardest reasoning benchmarks. As the host relays them: Humanity's Last Exam 38% with no tools against 27% for GPT-5.1; MathArena Apex about 23% against about 1% for GPT-5.1 and Claude 4.5; ARC-AGI-2 31% against 18% (GPT-5.1) and 14% (Claude 4.5). He adds new highs on AIME, GPQA Diamond and MMMU-Pro.
• Its agentic edge is in long-horizon planning and screen understanding. The host reports parity with Claude and GPT on SWE-bench Verified but a clear lead on LiveCodeBench Pro, a simulated profit of over $5,500 on Vending-Bench 2.0 (more than Claude Sonnet 4.5 and GPT-5.1 combined), and 73% on ScreenSpot Pro against 36% for Sonnet 4.5. On that last figure he says it may be the first LLM you would trust to act autonomously from what is on screen.
• Google is deploying it broadly and early users report gains. Google has revealed little architecture beyond a million-token context window, which the host says is about eight novels. It is rolling out across Search, the Gemini app and Vertex AI. He relays that Wayfair's CTO is piloting it to turn support documents into infographics, and that GitHub reported a 35% boost in code accuracy over Gemini 2.5 in an early test.
• The host's lesson is that frontier competition benefits builders. He argues that whichever lab leads in a given month is hard to predict, but practitioners deploying rapidly improving models all benefit. He also points to Google's Nano Banana Pro image model, which he says runs on Gemini 3 Pro.

2025-11-27 · open the original ↗

• Native Windows development feels painful but rewards long familiarity. Asked whether native Windows apps are a dying art, the speaker says people offer sympathy when told the team builds natively, and admits to "a bit of Stockholm syndrome" after years on the platform. They credit reading Raymond Chen for their grasp of Windows internals, and say a feature like "app fail" they could not have built at first is now a fun puzzle thanks to accumulated niche tools and knowledge.

2025-11-27 · open the original ↗

• Hallucination is the mechanism of creativity, in humans and machines alike. Ackerman argues that people hallucinate constantly, perceiving reality differently from one another, and that on certain psychedelics humans generate images and video faster and better than text-to-image models do. Recognizing that shared root, she says, means letting go of demands for control and precision all the time and leaning into how much brains rely on imagination.

2025-11-27 · open the original ↗

• Zig is obscure to most developers but has proved itself. One speaker describes Zig as a zero-dependency drop-in C/C++ compiler with cross-compilation out of the box, unknown to "dark matter" developers outside the Hacker News crowd. They admit they would have written it off as a hobby project, but say it has built a big community and is simple and fast.
• Native executables are tiny next to today's bloated websites. The same speaker contrasts the other's 2 MB and 12 MB executables with sites like The Verge, which they put at 25 MB in the browser's dev tools, while shipping executables that do 10 times more in half the size. Their other example is a 500 MB download just to control a podcast microphone's lights.

2025-11-26 · open the original ↗

• Promotion to principal brought burden more than status. One speaker, who reached principal engineer about a decade after graduating, says the milestone felt satisfying to a goal-oriented person, but they were not watching for markers like faster email replies, beyond perhaps a little from more junior people. What they noticed instead was the new burden of being the one in the meeting expected to know things and figure them out.

2025-11-26 · open the original ↗

• WSL installs a full Linux environment with one PowerShell command. Running wsl --install and following the prompts for a username and password installs Ubuntu by default; wsl --list --online shows the alternatives, such as Debian, Kali and Alpine, and typing wsl or launching Ubuntu from Start gets back in.
• Files cross both ways and the distro updates like normal Ubuntu. Linux files appear in Windows Explorer under Linux, Windows drives are mounted at /mnt/c inside Linux, and updates are sudo apt update && sudo apt upgrade -y.
• The host calls WSL a first install for Windows IT work. He points to native Docker (Docker Desktop for Windows itself runs on WSL 2), Tailscale inside WSL for remote access, testing Linux scripts without a second machine, and command-line AI tools such as Claude Code, which is what he uses it for.

2025-11-26 · open the original ↗

• Implicit trust in AI, not AI itself, is the main danger. Ackerman says the science-fiction image of an all-knowing oracle, even comparisons of LLMs to god, leads young and older users to trust ChatGPT implicitly. She argues a healthy level of doubt is enough to undo much misinformation damage and to stop people blindly taking its advice on personal problems.
• No process, human or machine, yields an infallible oracle. Ackerman rejects the idea that prediction or dependence on data is a design flaw, since humans also learn from sensory input and predict constantly. Her point is to separate process from results: however it works, it will never be perfect, just as the smartest humans are not.

2025-11-26 · open the original ↗

• Competence, built through hard challenges, is what creates confidence. The speaker rejects "fake it till you make it" as inauthentic. Their approach to impostor syndrome is to take on big, scary technical challenges in environments where people will sponsor you and support you if you fail, and to build self-confidence through repeating that.

2025-11-25 · open the original ↗

• Tuple is native because it serves human connection, not UI. One speaker notes that Claude, ChatGPT and Copilot desktop apps all feel like web views, while Tuple immediately feels native. The other agrees, arguing that apps heavy on UI chrome suit the web, but Tuple deliberately minimises chrome, so getting the system APIs right for sending video and audio over the network matters more.

2025-11-25 · open the original ↗

• Sangoma now charges separately for FreePBX single sign-on. Its new SAML module lets FreePBX users log in with Google or Microsoft accounts, inheriting their provider's multifactor authentication and centralized user management, and costs $500 a year for up to 20 users or $1,000 a year for up to 100 users.
• The host calls paid SSO "absolutely ridiculous" for basic security. He argues SSO belongs in the core product, or at least in the existing paid Sysadmin Pro module that already covers update management and VPN connectivity, not in a separate subscription.
• Crosstalk is not recommending the module to its customers. The host makes an exception only for a very specific business requirement, says the cost does not justify the convenience, and suggests Sangoma sell FreePBX if, after more than a decade of owning it, it cannot monetize it properly.

2025-11-25 · open the original ↗

• Machine creativity is undeniable and decades old. Ackerman says David Cope's Experiments in Musical Intelligence produced Bach- and Vivaldi-style compositions in the 1980s that listeners could not tell apart from the real thing in a discrimination test, yet "knew all along" once told a machine made them. She calls the swing between "AI will replace all artists" and "AI isn't really creative" a denial that blocks working out how to live with these systems.
• The recent leap came from size and money, not new ideas. Ackerman dates convincing generated audio, as opposed to scores, to about 2022, and says Suno and Udio's direct sound generation is meaningful but smaller than the public believes. What changed was the funding to build bigger "brains", which she likens to OpenAI's Microsoft investment, plus marketing; because we build brains rather than programs, she argues control over them is inherently limited.
• Creativity should be judged by outcomes, not process. Ackerman grants that most human art carries authentic emotion, but notes commissioned professionals deliver on deadline whether they feel it or not, and a photographer friend invents stories for galleries. Her point is that critics of AI art should know when they are criticising the process rather than the product.
• Generative models expose a culture's collective beliefs and biases. Drawing on Carl Jung's collective consciousness, Ackerman says models trained on Western data reveal Western assumptions more honestly than any person would: Midjourney once returned a Christmas tree for "Hanukkah" (since fixed, she says) and bagels for sufganiyot. Her research showed image models reproduce "brilliance bias", the belief that genius is male; the host cites a version presented at GHTC in 2022.
• Industry's oracle-and-replacement goal is the wrong target for GenAI. Ackerman argues products work better with humans involved, pointing to inpainting and to Suno making its product more interactive after finding its best users want to make music. She expects AI to become "more social" and collaborative, the approach she says Wave AI's Lyric Studio and Melody Studio take by suggesting lyrics, chords and melodies rather than writing for the user.

2025-11-24 · open the original ↗

• General meeting tools add typing lag that ruins pair programming. One speaker describes pairing over Zoom or Teams as a dance of scheduling, screen sharing at mismatched resolutions and granting control, with lag between a fast typist's keystrokes and their appearance on the other screen. The other says nearly everyone at Tuple is a developer, so the team pays close attention to that kind of lag.

2025-11-24 · open the original ↗

• Open interoperability is meant to lower the bar for enterprise agent adoption. Pandey says that was AGNTCY's goal from the start: agentic workflows run into "brown field heterogeneity", with agents from Salesforce, Cisco, Microsoft and ServiceNow sitting in different clouds with different intents, even for a simple sales funnel. He names four steps enterprises struggle with daily: discovery, identity, collaboration and evaluation, with identity the big stumbling block.
• Agents need shared meaning, not just connectivity. Pandey's example: when an agent returns "the best X with 90% confidence", it is unclear whether "best" and "90%" mean the same thing across all agents or vary vendor by vendor. He agrees with the host that frameworks such as zero-trust agency and task-based access control are aimed at helping practitioners get agentic projects through security review.

2025-11-23 · open the original ↗

• Zero trust for agents means permissions scoped to one task, then revoked. Pandey defines it as trusting no agent until it is shown it should do a specific task, granting access just in time for that task, tool or transaction, and revoking the token the moment it finishes. His analogy: role-based access lets him open a safe, but task-based access lets him withdraw only $10 in the next 10 seconds and then shuts the door.
• Making task-based access control work takes three pieces of infrastructure. Pandey lists identity providers and authorization servers that support it; a semantic parser that reads agent-to-agent and agent-to-human communication to work out what task is actually being requested; and an ephemeral, sandboxed runtime that executes only that task. A short recap that follows, apparently the host's, also lists human-in-the-loop approvals.
• Agents earn trust through directories, then through evaluation. Pandey says the simplest step is a directory that lets you discover agents by capability, reputation and trust, for example the best-of-breed financial agent from a reputable vendor. Crowdsourced ratings, like an app-store score, are one option; for more rigor, ongoing evaluation of agents and multi-agent workflows feeds back into the directory's reputation score, valid until something in the system changes.

2025-11-22 · open the original ↗

• The framework embraces rival agent protocols to avoid fragmentation. Pandey says AGNTCY, which works alongside MCP and A2A, moved to the Linux Foundation with Cisco, Dell, Google, Red Hat and Oracle as formative members and about 80 other organizations contributing or deploying it. Cisco is a foundational member of Google's A2A project there, and Google of AGNTCY, because he argues multiple competing standards would confuse an enterprise market already struggling to deploy agents.
• Agent communication today resembles networking before a common standard. Pandey describes mid-1990s "islands of connectivity", DECnet, AppleTalk and IBM SNA, that did not interoperate until the industry standardized on the open-sourced BSD TCP/IP stack, a move he credits to Vint Cerf and says Cisco backed. He sees agents at a similar juncture, where some systems talk to each other and some don't.
• Many agent protocols will appear, so the scaffold around them matters more. Pandey points out that TCP/IP was not the end: QUIC later combined TCP's delivery guarantees with UDP's low latency. He expects the same proliferation beyond MCP and A2A, and argues the lasting need is a protocol-independent scaffold: discovery (a DNS for agents and their capabilities), identity, messaging and evaluation.

2025-11-21 · open the original ↗

• The host rates the discounted Wi-Fi 5 access points the best value. The UAP HD is down from $349 MSRP to $89, almost 75% off; the Nano HD and Flex HD are $69 each, about 61.5% off; the AC Pro is 40% off. He calls them rock-solid devices Crosstalk sold to many customers.
• The U6+ is his pick for home Wi-Fi 6. At $99 it is about 23% off MSRP, and he suggests buying a couple for a home network.
• The UXG Lite is the gateway bargain, with a management caveat. At $49 it is 62% off MSRP, but it has no UniFi Network application on board, so it needs a separate UniFi OS console or Cloud Key.
• Buy the UCG Max with storage rather than without. The 512 GB Protect-storage version is $179, almost 36% off, and only $20 more than the storage-less one, which he says is about what the SSD tray accessory costs anyway; the UDR7 is the weakest deal, about 18% ($50) off, at $229.
• Switches and Protect cameras carry solid but smaller discounts. Three USW Enterprise switches are 25–37% off, the outdoor-rated EdgePoint S16 with PoE is almost 50% off at $299, the G5 Pro camera is $199 (almost half off) and the G5 PTZ is $229 (about 23% off).

2025-11-21 · open the original ↗

• Expert forecasters expect AI-assisted work to jump within five years. The host relays the Longitudinal Expert AI Panel (LEAP), a monthly survey of over 300 experts and superforecasters: its median forecast is that AI will assist roughly 18% of US work hours by 2030, up from about 2% today. The same panel expects AI training and deployment to use about 7% of US electricity by then, more than all US data centers combined today.
• The panel rates AI as at least a technology of the century by 2040. On Nate Silver's 10-point "technological Richter scale", LEAP's modal forecast is level 8, the tier of electricity or the automobile. The experts give about a 1 in 3 chance of level 9, the tier of the printing press or the industrial revolution, within 15 years.
• Capability jumps keep outrunning expectations, which policy must match. The host argues LEAP's strength is short-horizon questions that let it weight the most accurate forecasters, because progress is lumpy. His examples: Gemini 2.5 Deep Think's record 29% on tiers 1–3 of FrontierMath in October, and a virology test in which top models, with OpenAI's o3 highlighted, beat PhD virologists at troubleshooting wet-lab tasks, prompting calls for guardrails. His lesson is that governance must keep pace, not panic.
• The host expects gradual job pressure, not sudden collapse. He cites the IMF estimate that about 60% of jobs in advanced economies are exposed to AI, roughly half likely complemented and half at risk of substitution, and reads LEAP as pointing to slower growth in some white-collar categories. His advice is to treat 18% AI-assisted work by 2030 as a planning baseline, invest in skills and process change now, and assume pressure on power and infrastructure.

2025-11-20 · open the original ↗

• Rogue Support is hiring networking technicians to clear a ticket backlog. The host says customer tickets on Wi-Fi, security and remote access are arriving faster than the service can answer; techs get a base rate that rises with volume and reputation, plus direct tips and rehires, and at least five more are to be brought on by the end of the year.

2025-11-20 · open the original ↗

• C++'s crusty reputation comes from its backward compatibility. Dos Reis, a principal SDE at Microsoft on the MSVC toolset and on the ISO C++ committee since 1997, says 1990s "C with classes" code still compiles, so nothing forced people to modernize and the old image fossilized. He also faults advocates like himself for not showcasing a killer app in modern C++, the way the STL once changed minds.
• Compatibility is a feature; renovate in place rather than rewrite. He argues customers would quit a language that made them throw away working code every two years, and that memory safety is now the forcing function to re-examine code. His answer is incremental renovation instead of a rewrite in Go, Rust or Java; he says MSVC itself contains comments from the 1980s alongside the newest features.
• Engineering means dull, robust code the next person can maintain. He separates programming from engineering and teaches around contemporary problems rather than the language's history, starting with constexpr by default so the compiler catches accidental dynamic initialization. He contrasts this with 1980s-style template metaprogramming showing "how cute I am," which he says does not scale.
• C++ neglected tooling, but modules forced the committee to act. He agrees with Hanselman that package management and build systems were neglected, allowing diverse tools but fracturing the community. Designing modules for C++20 made the problem unavoidable, and he asked Herb Sutter, then running the committee, for a tooling study group.
• Memory safety by default needs profiles, still not standardized. He says memory-safe C++ is possible today; the problem is how easy it is by default. Profiles, developed with Bjarne Stroustrup, did not get into C++26, and they are pursuing them and parts of contracts on a parallel track released alongside it. He recommends Stroustrup's updated A Tour of C++ as a modern starting point, and learning two or three different paradigms, such as C++ and Haskell.

2025-11-20 · open the original ↗

• Real workflows chain very different agents across vendors, clouds and the physical world. Pandey's example, from a pharma company, runs from an LLM that plans the drug-discovery goal, to a scientific foundation model such as a protein-folding model that explores candidates, to robotic wet labs that test them physically, then to animal and human trials. Underneath run agents checking efficacy, cost and compliance.
• The internet of agents spans software, social and embodied agents. Pandey says it covers social interaction, scientific discovery, B2B services and physical AI robotics, and that no platform let such heterogeneous agents collaborate, which is the problem he says Cisco's open-source AGNTCY targets. Beyond communication, it must handle discovering capabilities, identity, composing agents into self-forming teams, and evaluating whether they serve a common goal.

2025-11-19 · open the original ↗

• An agent-human collaboration platform should be open, like the original internet. Pandey says the work began about two years before recording with the view that no platform let agents and humans collaborate on business, social, physical or service outcomes. Since Cisco was behind the original open internet, the team framed the thesis as the "internet of agents" and open-sourced it as AGNTCY, arguing "open source are the new standards".
• Today's business and coding agents are a myopic view of what's coming. Pandey forecasts multi-agent human societies tackling the biggest problems: drugs, materials, how the universe formed. He also expects agents for social interaction and embodied agents for physical work, arguing humans alone will not suffice; he wants agents to do his dishes, not to paint or play guitar for him.

2025-11-18 · open the original ↗

• Unshielded Cat 6 is fine for almost every home and office. The host puts it at 99% of cases, saying even runs past electrical panels or access points at home will probably see no interference; shielding, a foil or braid around the four twisted pairs against EMI, matters in factories with heavy motors, server rooms and data centers, and near radio transmitters or medical equipment such as an MRI lab.
• Shielded cable is wasted without shielded connectors and proper grounding. It needs shielded RJ45 connectors and grounded equipment at both ends, and the host's bottom line is to use it only in those environments or where interference has actually been measured.
• Shielding costs more and is harder to work with. He puts the premium at 30–40%: at TrueCable, his preferred supplier, 1,000 ft of unshielded Cat 6 is $145 against just over $200 shielded, and the thicker, stiffer cable gave TechnoTim trouble on their ghost town install.

2025-11-18 · open the original ↗

• Agents need an open, protocol-agnostic scaffold, like the early internet's. Pandey says Outshift, Cisco's internal incubator, open-sourced its "internet of agents" thesis as AGNTCY, now in the Linux Foundation with Cisco, Dell, Google, Red Hat and Oracle as formative members and about 80 other organizations involved. He likens today's agents to pre-TCP/IP networking islands and expects many protocols beyond MCP and A2A, so the lasting layer is discovery, identity, messaging and evaluation.
• Probabilistic AI works best blended with deterministic tools. Pandey argues the LLM craze is making people ignore deterministic tools that work well, and points to a resurgence of neuro-symbolic AI. His example is Outshift's network configuration and validation pipeline, which pairs a digital twin of the network with generative agents to get speed and accuracy together.
• Identity and access management breaks for agents. Pandey says IAM was built for humans or deterministic software, while agents talk like humans, give different answers to the same question and act at machine speed and scale, sometimes for one person and then another a minute later. Role-, attribute- and relationship-based access control assume stable roles that agents lack.
• Task-scoped, just-in-time permissions are the proposed fix. Pandey's task, tool and transaction-based access control (TBAC) grants a token for one task in a sandbox, then revokes it; it needs identity-provider support, semantic parsing of agent communication and ephemeral runtimes. Role-based control stays for humans, and the two must be bridged because humans will stay in the loop for approvals "for a long time". Agents earn trust through a reputation directory fed by evaluation.
• The next problem is shared meaning, not shared syntax. Pandey says current frameworks and protocols such as LangGraph, CrewAI and Google's Agent SDK solve only syntactic interoperability. Agents must also agree on what "best" or "90%" means, which takes the work into knowledge and cognition and, he says, will spawn many more protocols.

2025-11-17 · open the original ↗

• Enterprise AI projects fail when goals are vague and humans are absent. Responding to the MIT claim the host covered in episode 924, that 95% of enterprise AI projects fail to deliver a return in production, Gupta says success starts with clear goals, down to the desired type and accuracy of responses. He argues humans must stay in the loop in training and also in production, as built-in feedback to catch drift.
• Don't apply GenAI where traditional machine learning already works. Gupta says he has seen "plenty of misuse" of GenAI on problems well solved by solid, deterministic machine learning. His sequence is problem, goal, then the right tool, followed by use-case-specific best practices.
• Model choice can dead-end when scaling across devices. Cox says that with two million models on Hugging Face, Dell's tooling offers a curated set of enterprise-ready models checked for performance across silicon types. His reason is that teams often start with one model and hit a dead end when scaling up or across device categories.

2025-11-16 · open the original ↗

• Starlink warned old-dish owners to update or be bricked. The host reports an email from Starlink saying his Gen 1 dish had to be plugged in and allowed to update by November 17th or it would essentially stop working; the app showed "update required" and said the download would happen within 24 hours, with an automatic reboot if finished before 3:00 a.m.
• The update itself was quick and needed no active service. The host's unused dish finished within about an hour, after which the app showed service inactive, offering reactivation or standby mode for $5 a month; he boxed it back up and asked what Gen 1 dishes fetch secondhand.

2025-11-16 · open the original ↗

• State space models are an old control technique retooled for language. Cox explains they map an input signal onto a hidden state with one set of equations and turn that state into an observable output with another, and were used in 1960s spaceflight control, population studies and economics. Researchers at Carnegie Mellon and Princeton adapted them to sequence modeling in papers from 2021 to 2025, running from S4 to S6 and then to Mamba and Mamba 2.
• The hybrid design trades attention for far lower long-context memory. Cox says IBM's Granite 4.0 H models use a 9:1 ratio of Mamba to attention layers with no positional embedding. Training data reaches 512k context and the models are validated to 128k. He cites IBM's release notes: eight sessions at 128k context on the 3-billion-parameter Micro model use about 15 gigabytes of memory versus about 80 for a pure transformer, freeing usable context for RAG and multi-turn work on constrained edge devices.
• The small models score with frontier-scale ones on tool use. Cox says Granite ranks in the top five of the Berkeley Function Calling Leaderboard (BFCL v3) at the time of recording, alongside frontier models with hundreds of billions of parameters, at a 32-billion-parameter footprint. Gupta had earlier pointed to IFEval for instruction following.

2025-11-16 · open the original ↗

• Vibe coding suits small utilities, not production code. Hanselman builds on Edge Light, a WPF app on .NET 10 that he vibe-coded the day before to copy a macOS Tahoe feature putting a ring light around the screen, and he says it has only a handful of users. He works entirely in GitHub Copilot CLI with Claude Sonnet, dictating through Windows' built-in voice typing (Win+H) because of mobility problems in his hands, and says an IDE such as VS Code or Visual Studio would give a better experience, including debugging.
• Treat the agent's answers as claims to check, not verdicts. Reviewing a contributor's PR that swapped emoji for Segoe Fluent icons and a blur for a drop shadow, he asks the agent for risks and warns that "any one of these things could be wrong or a lie." The agent flags that the icon font is missing on Windows 10 and offers to check his users' systems, which he notes it cannot know; they add a fallback, merge, bump to 1.8 and watch the GitHub Actions build and auto-update work.
• Plan before coding, and keep permission prompts on. For the new feature, cycling the light between monitors from a toolbar button, he has the agent plan on a new branch before writing code, greys the button out for single-monitor users, and refuses "YOLO mode" so he sees every commit and push. His four mismatched monitors exposed a bug: the app started on monitor 2 because the screen array does not guarantee the primary display is index zero.
• Juniors can use these tools but miss the edge cases. He argues the risk for early-career engineers is not the tool but missing DPI, API choice, backward compatibility and hot-plugging; former testers, he says, are good at this work. He pushes the agent past a button-only bounds check to handle resize events when a monitor is unplugged, and admits he has not tested that path.
• An LLM mirrors you back; it is a sycophant. He notes Claude says "You're absolutely right" without knowing that he is, and echoed his own "good corporate citizen" phrasing. He also caught a hard-coded 0.4 default version in his build script and had it read the version from the project. He leaves open whether a cut-out or "bubble" around the mouse is something to vibe or write by hand, and concedes the 45-minute session might not beat doing it manually.

2025-11-15 · open the original ↗

• Open, enterprise-grade small models now ship across the hardware range. Gupta says the partnership announced at IBM TechXchange brings IBM's Granite 4.0 models into Dell's AI Factory for deployment from servers to edge devices to PCs. He calls them enterprise-grade because they are Apache 2.0 licensed with open weights and open training data, and says they sit near the top of HELM leaderboards, bookended by models of 100 billion parameters and more; he recommends them as a starting point for fine-tuning.
• Hybrid state-space layers cut transformers' quadratic memory cost. Cox explains that attention's memory scales quadratically, so doubling context quadruples memory such as the KV cache, while state space models scale linearly; Granite 4's hybrids get sub-quadratic scaling. He credits IBM with steady gains across Granite 3.0 to 3.3, the base for a pure-transformer Granite 4 Micro.
• The four variants trade size, sparsity and architecture. As Cox lays them out: Granite 4 Micro, a 3-billion-parameter dense transformer; 4H Micro, the same size but hybrid; 4H Tiny, a hybrid mixture-of-experts model with 7 billion total and 1 billion active parameters; and 4H Small, 32 billion total and 9 billion active. He explains that sparse models have knowledge and accuracy closer to their total parameter count but throughput closer to their active count.

2025-11-14 · open the original ↗

• The speed of change, not lost skills, is the real challenge. McGovern, founder of ODSC, cites a study he read finding skills in AI-exposed jobs turn over by "30 something%", roughly every three years, though he says he doesn't quite believe it. He argues skills never go away but multiply, and that practitioners should shift from building models from scratch to designing workflows, supervision and evaluation, as orchestrators rather than builders.
• Optimization behind an LLM interface puts planners in charge of what-if analysis. A Gurobi optimization specialist describes a Toyota talk on vehicle manufacturing planning, where planners test scenarios such as tariffs swinging from 0% to 10% to 80% through natural language, without writing models. He also describes Total Wine, whose data-science team had no operations-research background, learning mathematical optimization when machine learning "was not cutting it", and saving what he calls "a lot of money".
• Technologists should hold an unenforced professional ethos, not more regulation. Hare says she favors a Hippocratic-style oath precisely because it is not enforceable: an ethos of "first do no harm" and of maximizing benefits while minimizing harms, as lawyers, accountants and UK civil servants have. She notes the medical oath was rebooted after the Nuremberg doctors' trial, and disputes the host's suggestion that profit is technology's first incentive, saying the best work comes from solving problems.
• The new architecture's networks concatenate into one multilingual model. The BDH ("baby dragon hatchling") paper's author says its models scale along a single dimension, the number of neurons, so two networks trained on different languages can be placed side by side and work out of the box, optionally with post-training. He says its 1-billion-parameter models match or beat others at that scale, and that the team is aiming at reasoning models over contexts as large as 1 billion tokens rather than releasing a 70–80-billion-parameter chatbot.
• Customers pay only once a custom AI build shows business value. Schneider says Unframe, founded around March of the previous year and having raised $50 million in total, broke the startup playbook by serving many personas and industries from day one. Its "managed AI delivery platform" assembles hundreds of building blocks into tailored solutions, with no cost until agreed KPIs are hit. Services are included in a T-shirt-sized subscription per solution per year, and some customers run 5 to 15 solutions on it.

2025-11-13 · open the original ↗

• Postgres's popularity is a "happy accident" of several factors. Giordano, who works on the open-source Postgres project at Microsoft and joined via Citus in 2017, points to extensibility as the second objective in Stonebraker and Rowe's 1986 design document, which let Citus scale Postgres horizontally as an extension rather than a fork. She adds the permissive MIT/BSD-like license, which got it into universities, and watershed moments such as JSON support around 2012, followed by JSONB.
• No single company owns Postgres, which she sees as decisive. Microsoft, EDB, Amazon, Google and smaller firms all pay upstream contributors, and some call it "the people's database." She credits managed services as trendsetters, dating Heroku's to 2007, Amazon RDS Postgres to 2013 and Azure's to 2017. Hanselman's own theory is that standards compliance and enterprise focus made it "an overnight success in 40 years."
• Features win by persuasion, not a top-down roadmap. Work is bottom-up and decided largely on public mailing lists; an author must convince enough people and find one of the 31 committers willing to commit and then maintain the change. She says this makes Postgres conservative about features, and that even a hyperscaler's engineers must lobby across company lines. Asynchronous I/O for reads, new in Postgres 18, took about five years of groundwork across earlier releases.
• Open source does not mean open trademark season. As a board member of the Postgres Community Association, which holds the Postgres and PostgreSQL names and the Slonik logo, she urges anyone naming a product with "Postgres" to read the trademark policy first. Hanselman cites a past attempt to trademark the name that the core team pushed back on.
• The project deliberately avoids depending on commercial vendors. Its source lives on project-run git servers, with GitHub only a mirror, maintained by a volunteer sysadmin team of about seven or eight, with sponsored hardware. Its build farm has over 200 "animals," and she reports over 229 million seconds of build time across Postgres 18's roughly 15-month development cycle. Azure shipped Postgres 18 in preview, in one region, on GA day, which she says it had not managed a couple of releases earlier.

2025-11-13 · open the original ↗

• Orbital data centers could remove Earth's energy and water constraints on AI compute. Philip Johnston, co-founder of StarCloud, argues data centers in space draw constant solar power, radiate heat via infrared into deep space instead of evaporating fresh water, and can scale without land or grid limits, ultimately competing on cost with the largest terrestrial data centers.

• A large, low-cost deployable radiator is StarCloud's core technical bet and IP. Johnston says the main public criticism, from a viral post by Andrew McCallip, is that dissipating heat needs impractically large surface area; he counters that co-founder Ezra, a satellite-structures PhD, is leading half the engineering team to just build that large radiator.

• StarCloud pivoted from beaming solar power to Earth to sending data centers into orbit instead. Johnston says the team's original space-based-solar concept loses 95% of energy in transmission and only breaks even near $50/kg launch cost; recalculating for orbital data centers instead put breakeven near $500/kg, much closer to today's falling launch prices.

• StarCloud built and launched its first satellite in 15 months, versus roughly 4 years for prior space startups. The company, backed by YC after a third application attempt (under its earlier name Lumen Orbit), launched its StarCloud 1 satellite with an Nvidia H100 GPU on November 2nd and plans a second, Blackwell-equipped launch in October 2026.

2025-11-13 · open the original ↗

• The on-device AI stack is mostly glue over partners' runtimes. Cox says Dell's tooling, formerly Dell Pro AI Studio, presents one consistent API across systems such as Dell Pro Max and Pro Plus, so apps need not handle each platform's quantization parameters, toolchains and runtimes. He says it integrates eight back-end runtimes "and counting", which Dell did not build, so an app doesn't have to carry the difference between, say, an AMD NPU and an Nvidia RTX Pro GPU.
• Multi-chip routing and model management hide hardware complexity. Cox says some systems carry four or five kinds of accelerator, and the software lets an app run a model on the NPU in one session and the GPU in the next. Its model management sends the right model versions and dependencies to each platform, so an IT admin deploying to 5,000 users doesn't pick versions per machine. The command-line tools follow existing local-AI conventions rather than reinventing them.

2025-11-12 · open the original ↗

• A wireless bridge beat fiber for a friend's Airbnb back house. At the property, in Los Angeles, fiber to the back house would have meant a run of over 200 ft and boring under a concrete walkway: an 811 utility-marking call, digging, renting a horizontal borer or auger, conduit, pulling and cleanup, taking days, with gas-line risk and lost Airbnb revenue while the network was down.
• Equipment cost is similar; labor and rentals decide it. The host says the bridge installed in hours, was cheaper overall and delivered a solid 300 Mbps across the property, arguing a properly dialed-in wireless bridge can be as reliable as a hardwired link.

2025-11-12 · open the original ↗

• A single informal paper list carries Mark's to-dos. Mark keeps one office-supply notebook, work in the left column and home in the right, carries unfinished items forward under a new horizontal line, and throws old notebooks away. He says many studies show offloading to a list removes a load from the brain, and argues a more organized system costs effort whose return he doubts; he puts links, AI hallucination screenshots and papers on jailbreaks in OneNote instead.
• Procrastination can be background processing, not avoidance. Mark calls himself an "incredible procrastinator" but says he is subconsciously working on a task and sizing its effort before he starts. Hanselman likens it to a background agent and says his own last-minute talk preparation feels like rumination rather than avoidance, adding that once you find a system that works, keep it, while people early in their careers should try several.
• Hanselman relies on paper, a reMarkable and the calendar. He has kept notebooks for about 20 years, back to at least 2007, and says writing things down is why he sleeps well; his reMarkable e-ink tablet syncs everything, which shows him how much he has offloaded. He argues the shared calendar removes the most "psychic weight" in a household, and recommends iPhone geofenced reminders ("remind me next time I'm at Fred Meyer to buy milk") as underused.
• Neither host has a true second brain. Hanselman says he keeps wishing for an organized Obsidian or OneNote knowledge base but falls back on paper; asked whether AI should do retrieval over their notes, they joke about handing it to AI "interns" and conclude there is only "a hierarchy of brains." Both call the episode rambling and "not our finest hour."

2025-11-12 · open the original ↗

• Authorization belongs in the application, not the identity system. Leroux Bustamante says putting roles or permissions in the token bloats it until it gets blocked, and multiplies roles: she has seen systems with 200 roles that permission-based design could cut to about 20. She advises letting the app own the rules, or centralizing when there are many apps and governance, audit and role history matter, using a product such as her own Policy Server ("shameless plug") or the open-source Open Policy Agent (OPA).
• Missing MFA is the number one cause of breaches. She ranks the options: email is "a terrible idea", SMS is extremely common, banks included, but no longer preferred, authenticator apps and FIDO keys such as YubiKey suit technical users, and passkeys are now the most accessible form for consumers.
• A web application firewall in front is the first platform control. For an Azure deployment she recommends turning on a WAF via Front Door or App Gateway to catch the OWASP top-10 failures, putting data on a separate network from app services, using Private Link, and using managed identities everywhere so no secrets are stored. She says she has heard of many sites that went down because a key rotation was not known in advance and simply expired.
• Measure posture against NIST CSF, and staff the monitoring. She maps tools such as Defender and Sentinel to the framework's six categories and gives a CISO a dashboard scoring each from one to four, but says turning those tools on without someone acting on the output is useless. When Giard asks about AI for digesting reports, she says it saves time but can hallucinate, so a human must stay in the loop "for a while".
• Dev should match prod's security posture from the start. She sees customers whose dev environments differ from production and who lock developers out of logs and audit trails in upper environments; the pain then lands in QA, and developers get blamed for delays such as an API gateway that exists in QA but not in dev. Her case is to shift left: plan security in the SDLC up front, because product owners "don't sell security features" and budgets often rise only after something goes wrong.

2025-11-12 · open the original ↗

• Unequal inferences mean AI will run hybrid, cloud to PC. Gupta says customers who start in the cloud and scale to production find that costs skyrocket or on-prem compute runs out. Citing a prediction that 90% of AI workloads will be inference by the turn of the decade, he forecasts workloads running seamlessly across cloud, edge and PC fleets.
• The model should match the "quality of tokens" a task needs. Gupta's example is coding: autocomplete can run on a small local model rather than burdening a GB300 superchip, while a full-scale refactor may need a frontier model. He expects much intelligence to go into routing workloads, and AI PCs to play an important role in enterprise AI strategy.
• Local inference cuts latency, keeps queries private and stays available. Gupta says running on the PC removes about 200 milliseconds of cloud latency, which matters for voice and video. He argues that even when the data sits in the cloud, a local model keeps the query and its inputs and outputs private, whereas he says public cloud model queries are "completely indexable by search engines". A recent AWS outage, he adds, showed that on-device AI is always available.

2025-11-12 · open the original ↗

• The local test repo must first get a GitHub remote. Building on the Playwright test and Azure Playwright workspace from the series' first two videos, Giard creates an empty GitHub repository with the same name as the local one, links it with git remote add origin plus the repository URL ending in .git, and pushes with git push -u origin main.
• Repository secrets keep workspace and identity details out of the YAML. Under Settings > Secrets and variables, Giard creates four Actions secrets: the Playwright service URL (copied from the workspace's Get Started page), the Azure client ID, the Azure tenant ID and the Azure subscription ID. He first fills them with an "X" as placeholders, because each value comes from a different place.
• An Entra app registration supplies the identity the tests run under. Giard registers an app limited to accounts in his own organization's directory, with a Web redirect left blank. Its application (client) ID and directory (tenant) ID become two of the secrets; the subscription ID comes from Subscriptions in portal.azure.com. He then assigns the app the Contributor role on that subscription through Access control (IAM), noting that Contributor is listed among the privileged administrator roles.
• A federated credential ties that identity to one repository branch. In the app registration, under Certificates & secrets > Federated credentials, Giard adds a credential using the "GitHub Actions deploying Azure resources" scenario, giving his GitHub account as the organization, the repository name (he notes it is case-sensitive), entity type branch, and the main branch.
• The workflow YAML runs the tests in Azure and keeps the report. Giard's replacement YAML triggers on a push or pull request to main, requests ID-token write and contents read permissions for Entra, and runs one test job on the latest Ubuntu with a 60-minute timeout. Its steps are checkout, Azure login using the three ID secrets, installing dependencies with npm, npx playwright test against the service config file from the previous video with a set maximum of workers and a report format, and an always-run upload of the Playwright report folder as an artifact, its retention changed from 5 to 10 days. A commit and push started the run, which took about a minute and a half, and the report downloads from the run page as a zip file.

2025-11-12 · open the original ↗

• An Azure Playwright workspace runs existing Playwright tests in the cloud. It is created in the Azure portal by searching resources for "Playwright workspaces" and giving a resource group, subscription, name, region (only a few regions offer it) and optional tags; creation takes about 30 seconds, and the workspace's Get Started tab lists the steps for wiring up a test project. The project is the one from the previous episode.
• npm init @azure/playwright@latest adds the cloud config to the project. Run from bash, it created a playwright.service.config file (running on Linux with default Azure credentials) and added authentication settings to existing files; the recommended identity is Entra ID, so Giard signs in with az login and picks the tenant holding the workspace.
• Tests reach the workspace through an environment variable and the service config. PLAYWRIGHT_SERVICE_URL is set to the workspace endpoint, then npx playwright test runs all tests or a named file such as example.spec.js, with --config pointing at the service config — renamed from .ts to .js because the project uses JavaScript. A maximum worker count is optional and lets many tests run simultaneously; his three tests passed in the cloud on one worker.
• Persist the endpoint in a .env file instead of in memory. Installing dotenv with npm i --save-dev and adding require('dotenv').config() to the config file makes it read the PLAYWRIGHT_SERVICE_URL= name-value pair (without export) from .env; Giard notes a store such as Key Vault might be more secure. Rerun this way, the three tests passed again.

2025-11-11 · open the original ↗

• On-device AI needed to be as easy to deploy as the cloud. Gupta says Dell's toolkit, formerly Dell Pro AI Studio and being renamed within the Dell AI Factory, answered three problems: silicon and runtime diversity slowing adoption, no enterprise-grade fleet lifecycle management, and the gap with cloud ease. Its parts are a PC model catalog in the Dell Enterprise Hub on Hugging Face, an on-device framework that lets cloud workloads point at the PC as localhost via existing API standards, and lifecycle management through the Dell Management Portal in Intune.
• Inference should be routed by the token quality each task needs. Gupta cites a prediction that 90% of AI workloads will be inference by the end of the decade and forecasts hybrid AI across cloud, edge and PC. In his example, code autocomplete belongs on a small local model and a full refactor on a frontier model. Local inference also removes about 200 milliseconds of cloud latency and keeps queries private; he says a recent AWS outage showed its availability value.
• Hybrid Mamba-attention models keep long context cheap. Cox says Granite 4.0 H models interleave Mamba and attention layers at a 9:1 ratio because Mamba handles global context well but loses attention's local sensitivity. He cites IBM's figure of about 15 gigabytes for eight 128k-context sessions on the 3-billion-parameter Micro, against about 80 for a pure transformer. He relays a Meta FAIR paper recommending more hybrids for training and inference efficiency, and expects more of them.
• Sparse Granite variants pair large-model knowledge with small-model throughput. Cox describes Granite 4H Tiny (7 billion total, 1 billion active parameters) and 4H Small (32 billion total, 9 billion active) as mixture-of-experts hybrids, alongside 3-billion-parameter dense Micro models. He says Dell tunes inference parameters such as context length per device, from a 16-gigabyte AI PC to an RTX Pro 6000 Blackwell with 96 gigs of VRAM, and had day-zero support.
• AI PCs should be judged on CPU, GPU and NPU together. Gupta compares a Dell Pro Plus with Intel Core Ultra 200V (Lunar Lake) against an older non-AI-PC chipset: 88% more battery runtime in Teams meetings, 4.8x graphics, almost 10x on-device AI CPU and 4.2x AI GPU performance, over 6x on Mistral 7B and Llama 3.1 text generation, and up to 5.6x on Stable Diffusion 1.5 image generation.

2025-11-10 · open the original ↗

• Image processing could catch brain shrinkage too subtle for doctors. Dupuis says his master's research at Imperial College London, about 10 years before recording, used image processing on brain scans to detect early Alzheimer's. Back then brain shrinkage was one of the early physiological signs, but too subtle for a doctor to see until months later, when it was too late; Alzheimer's is hard to reverse, but early detection might slow it. He notes other markers have advanced a lot since.
• Brain-signal decoding is mostly a hard signal-versus-noise problem. Dupuis says much of his broader biotech master's covered signal processing of brain waves, for example from implants in monkeys controlling robotic arms. The difficulty is separating intent from everything else in billions of connections, such as whether the brain is reacting to what the eyes see or to the attempt to move the arm.

2025-11-09 · open the original ↗

• AI analytics risks redefining a metric every time someone asks. Dupuis calls it a "justified fear" that AI given to everyone will reinvent metrics with each question, even when humans agree on definitions. He points to semantic layers and guardrails, with data teams supervising and working with business stakeholders, as the answer, and says the data team's job of keeping metrics consistent does not change.
• Dashboards will be fewer but matter more. Dupuis argues the dashboards that survive will be curated by data teams and track the core metrics such as churn, ARR and retention, with the team spending more time making sure they are correct. AI's role is the questions that have not yet reached the north-star metrics or OKRs.
• Explore a metric with AI before formalizing it. Dupuis's process is for a data scientist and a product manager or CSM to explore a hypothesis metric with AI on raw or curated data, often finding the question was wrong, rather than modeling it into the warehouse first. If the metric holds steady for a month or a quarter, it then goes through the "proper channels" into the warehouse, data models and a dashboard.

2025-11-08 · open the original ↗

• AI plays two distinct roles in data work: coder and embedded collaborator. Dupuis says the first is code generation, writing, debugging or optimizing SQL and Python; in Fabi, he says, 90 to 95% of the code run is AI-generated, with manual correction possible. The second goes beyond automating a dashboard or a chart being sent: an agent embedded in the workflow interprets the table or chart and suggests the next best action. Fabi's AI summarization cells, for instance, turn any number of data frames into an executive summary using the user's choice of LLM.

2025-11-07 · open the original ↗

• Coding agents fail at data science because they never interpret the data. Kodialam, co-founder and CEO of Sphinx, which the host says has raised $9.5 million, argues data work differs from software engineering the way a poem differs from a technical paper. His example: a frontier coding agent handles a clean linear regression, but with outliers, invalid rows or non-linear shape its answers become "very variable". It treats the task as code that runs and outputs an R-squared, "mission accomplished", without looking at the data.
• Sphinx treats data as its own modality, built for AI to read. Kodialam says Sphinx builds only a representation-learning layer that turns data into context, and leaves text and code to frontier models. His illustration is five years of Walmart's stock price printed as about 80 pages of numbers, which is how an LLM sees data today, against a candlestick chart a human grasps at a glance. He adds that models are also poor at reading charts, giving vague answers on the correlation in a scatter plot.
• The agent works from the Python kernel and executes on the user's side. Kodialam says most coding agents treat the bash terminal as home base, while Sphinx uses the IPython kernel so it can transform in-memory objects, which makes Jupyter a natural interface. It works as a side chat operating at the level of actions, writes ordinary SQL, Python and markdown cells for auditability, and runs on the user's compute so Sphinx never takes their data. Users typically start with small tasks such as joining two tables before moving to fully agentic flows.
• Better tools mean more data scientists, not fewer. Kodialam says existing data-heavy clients mainly get "five times faster", while the more transformative case is a consumer packaged goods customer now hiring more data scientists because each produces more. He says some early customers' data teams have doubled, and cites a Harvard Business School figure that 80% of CEOs call data a top priority but 20% actually invest in it.

2025-11-07 · open the original ↗

• Playwright is installed by an interactive npm initializer. With Node.js and an IDE (his is Visual Studio Code) as prerequisites, npm init playwright@latest asks for TypeScript or JavaScript (he picks JavaScript), a folder for end-to-end tests (default tests), whether to add a GitHub Actions workflow (yes), and whether to install the Playwright browsers now.
• By default every test runs once in each of three browser engines. The config installs Chromium (the engine under Chrome and Edge), Firefox and WebKit (the engine under desktop Safari), and engines can be added or removed later; so the two generated sample tests ran as six under npx playwright test, and npx playwright show-report serves the per-browser results from a local web server.
• A test is an awaited sequence of page actions followed by assertions. The samples await page.goto the playwright.dev URL and expect the title "Playwright", or click the link with role and name "Get started" and expect a heading named "Installation" to be visible; the test passes only if the assertion holds.
• Codegen records clicks and keystrokes in a browser as test code. npx playwright codegen <URL> opens an emulated browser beside a code window that writes a line per action; toolbar buttons add assertions (assert visibility, assert text), and the output can be switched from Node to Python, .NET with MSTest or NUnit, or Java with JUnit. Giard pasted a recorded run of a simple form into the spec file as a third test.
• The recorded test failed only in WebKit, which he left unresolved. Three tests across three browsers made nine runs; the new one passed in Chromium and Firefox but in WebKit hit the 30-second timeout because it could not find and check a radio button. Giard guesses it may relate to Safari not being supported on Windows and calls it something to explore.

2025-11-06 · open the original ↗

• Computers belong running, not behind glass. Jones, formerly senior engineering manager at Living Computers: Museum + Labs and now at the Interim Computer Museum, argues a machine behind glass only celebrates industrial design, while a running one conveys what it did. He says Living Computers had seven full-time engineers, "unheard of" for a technical museum, since most outsource exhibit building and interpretation.
• The new museum survives on community, not a benefactor. ICM, a nonprofit that got charitable status in April and joined Benevity for matched donations in May, focuses on covering lease and utilities; Jones reports 356 members and sponsors and its first surplus quarter. He draws the model from SDF.org, a 1987 BBS turned nonprofit Unix ISP that he says survived the dot-com bust on membership; a $36-a-year membership gives access to 26 remote vintage systems, real, hybrid and simulated.
• Living Computers' collection was not gutted, contrary to coverage. Jones calls GeekWire's June 2024 articles cruel and a missed opportunity, saying only about 30 LCM items went to the Christie's auction alongside space art and other memorabilia. He says most of the rest is at the Mims museum in Roswell, Georgia, which took the Living Computers name and is preparing an Apple 50th exhibit, or at ICM's roughly 3,000 sq ft space in Tukwila, near SeaTac, open to members by appointment.
• Legacy media is degrading, which is why the museum is "interim." ICM's preservation lab holds about 3,000 magnetic media artifacts, from disk packs to DECtapes, and uses techniques such as baking tapes to restore binders. Jones says the name expresses urgency: data remains trapped on esoteric carriers while the media slowly degrades.
• Retro tools bridge old machines and the present. Hanselman argues "we're forgetting how to drive stick shift" and says running multitasking Unix on a simulator taught him how the cloud descends from the Altair. Both cite adapters that put old machines online and read old disks; Hanselman says he recovered a never-released DOS 4 beta that Ray Ozzie sent him on floppies. Jones adds that history's sidelined ideas, such as Lisp machines and the Connection Machine, show the best concepts do not always win.

2025-11-06 · open the original ↗

• Self-serve AI analytics changes data scientists' work rather than replacing them. Dupuis says that when business users explore data themselves, even imperfectly, they bring data scientists much better initial questions instead of filing a Jira or Linear ticket. He says this is the change he sees most with customers: a more collaborative, data-literate working relationship.
• Business understanding and statistics will outvalue memorized coding. Dupuis argues that as AI gets good at coding, recalling syntax such as a Plotly chart matters less. He says data scientists should learn how the business makes money and its P&L, and lean on fundamentals in statistics and ML to design experiments and supervise the AI. He calls it the most exciting time for data scientists in five or ten years.