Podcasts about James Brady

Megyn Kelly is joined by John Hinckley Jr., musician, artist, and author of "John Hinckley Jr.: Who I Really Am," to talk about what he thought when he saw another Trump assassination attempt at the "Hinckley Hilton," the rise of political violence in America today, people reaching out to him on X to commit further violence against Trump, what an "erotomaniac" actually is, Hinckley's delusion that led to his Jodie Foster obsession, what happened when he actually saw Foster in person at Yale, what led him to start thinking about hurting someone to impress Jodie Foster, his initial targets of Jimmy Carter and even Ted Kennedy, the circumstances that led to his assassination attempt on President Ronald Reagan, how easy it was to get close to Reagan to take the shots, his reaction to Reagan and James Brady's comments about him, what he'd say to their family members now, his communication with Ted Bundy, what life was like in the psychiatric facility, getting released and what life is like now, and more.   More from Hinckley Jr.- https://wbp.bz/johnhinckleyjr   Supersure Insurance: Upgrade your business insurance to a year-round SuperAgency at https://Supersure.com/Megyn Veracity Health: Head to https://VeracityHealth.co and use code Megyn for up to 65% off your order Herald Group: Learn more at https://GuardYourCard.com Sundays for Dogs: Upgrade your dog's food without the hassle—try Sundays for Dogs and get 50% off your first order at https://sundaysfordogs.com/MEGYN or use code MEGYN at checkout.     Follow The Megyn Kelly Show on all social platforms: YouTube: https://www.youtube.com/MegynKelly Twitter: http://Twitter.com/MegynKellyShow Instagram: http://Instagram.com/MegynKellyShow Facebook: http://Facebook.com/MegynKellyShow Find out more information at:https://www.devilmaycaremedia.com/megynkellyshow Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This week on Hashtag History, we will be discussing the attempted assassination of Ronald Reagan. On March 30, 1981, President of the United States Ronald Reagan was shot outside of the Washington Hilton in Washington, DC, as he was leaving a speaking engagement. He was shot by a man named John Hinckley, Jr., a twenty-five year old man who had fallen in love with actress Jodie Foster after seeing her in the movie, Taxi Driver (which she starred in when she was twelve-years-old), and believed that if he successfully killed the President, that she would be impressed.Reagan was actually seriously injured during this attempt. When he was thrown into his limousine by his servicemen, they originally thought he had just broken a rib or something and that's why he was experiencing chest pain. But they discovered after he reached the hospital – where he collapsed – that Hinckley had successfully hit him with a bullet that had come within an inch of his heart. He miraculously recovered and was released a few weeks later.As for his would-be assassin, he was found Not Guilty by Reason of Insanity and was sent to a psychiatric hospital…that he was actually released from in 2021…so yes, he is out and about…so that's great.I don't want to spend this whole episode talking about just Reagan and Hinckley though because, one of the major pieces of this story that so many people neglect to tell, is that several of Reagan's staffers and local policemen were also wounded during the assassination attempt including White House press secretary James Brady who was hit in the head and, as a result, suffered from brain damage for the rest of his life. It's actually because of Brady and his wife that we have the Brady Law (or, the Brady Handgun Violence Prevention Act of 1993) which established federal background checks on firearms and a five-day waiting period for handgun purchases.Follow Hashtag History on Instagram @hashtaghistory_podcast for all of the pictures mentioned in this episode.Citations for all sources can be located on our website at www.HashtagHistory-Pod.com. You can also check out our website for super cute merch!You can now sponsor a cocktail and get a shout-out on air! Just head to www.buymeacoffee.com/hashtaghistory or head to the Support tab on our website!You can locate us on www.Patreon.com/hashtaghistory where you can donate $1 a month to our Books and Booze Supply. All of your support goes a long ways and we are endlessly grateful! To show our gratitude, all Patreon Supporters receive an automatic 15% OFF all merchandise in our merchandise store, a shoutout on social media, and stickers!THANKS FOR LISTENING!- Rachel and LeahEditor: Alex PerezCopyright: The Hashtag History Podcast

In insurance we usually spend a lot more time talking about innovation than we end up doing it. So this podcast focuses on two of the do-ers putting innovation into practice. It's now ten years since Hiscox launched its market-first, tech-enabled, live quote and bind FloodPlus product and this Episode examines the story of that product's development and its growth into a market opportunity that was primed for expansion. To guide me through the story I am joined by James Brady, Property Divisional Director at Hiscox London Market & Tom King, the firm's Flood Line Underwriter. This is a story about overcoming obstacles, recovering from setbacks and constant iteration. Ten years on and Hiscox is the biggest flood market in Lloyd's and the opportunity to write flood from the private market is only growing. Indeed since we completed this recording the Trump Administration's Council to Assess the Federal Emergency Management Agency (FEMA), which runs the National Flood Insurance Program (NFIP) has just issued its final report, recommending the implementation of risk-based pricing and a take-out program to incentivise the transfer of policies to the private market. With US market penetration still at only 4% the prize for the private market is as big as any other underwriting opportunity out there today. Tom and James are sparkling guests and this podcast is an inspiring celebration of innovation in action that has applications way beyond the highly specific field of US flood. NOTES: The President's Council to Assess the Federal Emergency Management Agency (FEMA) report can be found here. The part relating to Flood is on Page 11. LINKS: We thank our naming sponsor AdvantageGo, now part of Sapiens: https://www.advantagego.com

One bullet struck Reagan's press secretary, James Brady, another wounded District of Columbia police officer Thomas Delahanty, and a third struck Secret Service agent Timothy McCarthy as he attempted to shield the president. Nevertheless a fourth bullet ricocheted off the side of the presidential limousine and entered Reagan's left side under his ...

Loneliness keeps rising even as our screens glow brighter, and we wanted to understand why—and what to do about it. We start by reordering the foundations of daily life: God first, then spouse, then family and neighbor. That simple hierarchy changes how we spend time, handle stress, and make sacrifices. Proverbs 5 calls husbands and wives to mutual faithfulness that is lived, not just promised. Matthew 17 reminds us that a mustard seed of faith can move the mountains in our homes and hearts, while a coin in a fish's mouth shows how God provides in the most practical moments. Psalm 22 gives voice to anguish without giving up on trust.From the personal we zoom out to the civic. We honor James Brady's Medal of Honor courage, then look to John Adams' stark warning about unrestrained democracy: passion without guardrails can turn into a mob. We examine how erasing uncomfortable history—whether French terrors, totalitarian purges, or our own national failures—only blinds us to the lessons that keep a republic healthy. Facing the record honestly strengthens love of country because it anchors hope in truth rather than myth.This conversation aims to equip you with grounded steps: choose people over pixels, set a clear order in your home, practice small daily acts of love, read hard history with open eyes, and cultivate a faith that acts. If this resonates, share it with someone you care about, subscribe for more faith-and-history episodes, and leave a review to help others find the show. What's one change you'll make today to value people over screens?Support the showThe American Soul Podcasthttps://www.buzzsprout.com/1791934/subscribe Countryside Book Series https://www.amazon.com/Countryside-Book-J-T-Cope-IV-ebook/dp/B00MPIXOB2

Dr. Victor Cha, Dr. James Brady, and Mr. Tobias Harris discussed the newly elected leader of Japan's ruling Liberal Democratic Party (LDP), Sanae Takaichi—who is likely to become the next prime minister following a parliamentary vote in mid-October—as well as trilateral relations among the United States, the Republic of Korea, and Japan, foreign policy views, and more.

Send us a textJim Brady was a popular member of the Reagan campaign , and briefly the Reagan Administration. He was gunned down in 1981 in the attempt to assassinate Ronald Reagan. He lived, but suffered permanent brain damage, leaving him paralyzed and slow to speak for the rest of his life. His wife, Sarah Brady, would go on to lead a lifelong crusade to bring some form of gun control to America. This is the story of the passage of the bill named in her husbands honor. Bob Dole opposed the legislation. This episode we will hear the floor debate between Dole and Senate Leader George Mitchell. We will learn how Dole treated everyone fairly, and we will get to see a real test between the President and the Minority Leader. In this early battle between the two leaders of their party, Clinton would win. The Brady Bill passed the House of Representatives 238 - 189 , and it passed in the United States Senate 63 - 36 with an amendment. The Bill introduced one of the things that Bob Dole had been pushing for years, a National instant background check.  Questions or comments at , Randalrgw1@aol.com , https://twitter.com/randal_wallace , and http://www.randalwallace.com/Please Leave us a review at wherever you get your podcastsThanks for listening!!

It's episode 217 and time for our Summer Media Update! We discuss shelf trophies, sumo wrestling, Kpop Demon Hunters, blogs in book form, and more! You can download the podcast directly, find it on Libsyn, or get it through Apple Podcasts or your favourite podcast delivery system. In this episode Anna Ferri | Meghan Whyte | Matthew Murray

Episode Guest:James Brady is the Property Divisional Director at Hiscox, where he leads underwriting and strategy across the UK property market. With over 18 years at Hiscox, James has built teams, led growth, and championed insurance as one of the world's best-kept career secrets.Episode Timestamps:0:00 Introduction0:41 James on demystifying insurance careers1:12 First job and early lessons in pensions2:33 How to stand out in a competitive job market3:28 Knowing your differentiator in interviews4:40 When a “good vibe” job isn't the right fit5:28 Why you should never leave without another role lined up6:21 The role of recruiters and how to spot a good one8:12 Why you must drive your own career9:41 The non-linear path to success10:46 What Hiscox taught James about opportunity12:22 Why insurance is the world's best-kept career secret13:36 The variety of careers inside insurance14:57 How the Lloyd's of London market works16:58 Local vs London underwriting explained18:56 Why James has stayed 18 years at Hiscox20:39 What makes a great manager22:17 The hardest and most rewarding part of managing people22:53 Moving from London to Manchester — a career-defining opportunity24:20 What to consider before saying yes to a big move26:09 Rebuilding the Manchester team and brand27:31 The power of consistency and being as good as your word28:28 Specialising in media and technology insurance29:49 Insuring content creators, designers, and media giants31:07 Why join Hiscox and the insurance industry today32:46 James's duvet flip – what gets him out of bed in the morningEpisode PartnerHiscox, a leading international insurer with more than 3,000 employees worldwide. The company is known for specialist insurance solutions and a strong commitment to customer service.Disclaimer:The content provided on Duvet Flip is for informational and entertainment purposes only and should not be considered professional advice. The views expressed by hosts, guests, brands or contributors are their own and do not necessarily reflect those of the show's producers, sponsors, or affiliates. The information shared is not a substitute for professional advice, including but not limited to career counseling, financial guidance, legal consultation, or mental health support.Listeners and viewers are responsible for their own decisions and actions based on the content provided, and Duvet Flip assumes no liability for any outcomes resulting from reliance on the information shared. By engaging with the show, you acknowledge and agree to this disclaimer.If you're struggling with debt, trusted advice and free support can be found here: https://www.gov.uk/debt-adviceIf you're struggling with mental health of any kind, you can find free support here: https://www.nhs.uk/mental-health/

In this podcast we share a few selected highlights from the Alzheimer's Association International Conference (AAIC) first and second day of the main event in Toronto and Online, 27the - 31st July. -- Dr James Brady, Postdoctoral Research Fellow at University of Tasmania hosts the show with special guests: Dr Lucy Stirland, Academic Old Age Psychiatrist at The University of Edinburgh Dr Isabel Castanho, Instructor at the Beth Israel Deaconess Medical Center (BIDMC), Harvard Medical School Felix Wittmann, Research Fellow & PhD candidate at Leipzig University -- The AAIC brings together distinguished basic scientists, clinical researchers, early career investigators, clinicians and the care research community at the largest and most influential international conference on dementia science. They share theories and breakthroughs while exploring opportunities to accelerate work and elevate careers. Main plenary talks from the day came from Professor Katerina Akassoglou, University of California, San Francisco, United States exploring Neurovascular Interactions in Alzheimer's Disease: From Mechanisms to Treatments + Professor Maria Grazia Spillantini, from University of Cambridge United Kingdom for her plenary titled 'The Multiple Facets of Tau Pathology'. -- #AAIC25 @alzassociation -- Find more information on our guests, and a full transcript of this podcast on our website at: https://www.dementiaresearcher.nihr.ac.uk/podcast -- The views and opinions expressed by guests in this podcast represent those of the guests and do not necessarily reflect those of NIHR Dementia Researchers, PIA membership, ISTAART or the Alzheimer's Association.

Leadership, Legacy, and Work-Life Fit: A Journey from NASA to Space Center Houston and Beyond What if the secret to developing great leaders isn’t found in training programs, but in the experiences, mentoring, and coaching you provide along the way? In this episode of Engineer Your Success, Dr. James Bryant talks with Brady Pyle, Chief HR and Inclusion Officer at Space Center Houston, about intentional leadership development and creating sustainable work-life fit. From transitioning between vastly different organizational scales to building leadership capacity in growth mode, Brady shares his 70-20-10 approach to developing leaders. You’ll discover how to distinguish between mentors, coaches, and sponsors in your career growth, why setting boundaries early prevents workplace burnout, and how personal mission statements guide career decisions. Whether you’re an engineer stepping into leadership roles or a seasoned professional navigating career transitions, this episode will help you develop others while maintaining what matters most.

IPS DEPROGRAM 6/1/25 News Bending PsyopsThe episode began with the host announcing the launch of a new AI agent called the IPS stenographer in the Discord server. This bot is designed to automatically summarize the latest comments and create infographics every four hours, posting them in a dedicated summary room. Users can also get a synopsis on demand using a specific command. The host mentioned previously doing this manually and used ChatGPT and Grok to help automate the process. They noted that Grok can elaborate on prompts and assisted in activating the bot on Discord.A core theme of the discussion is the analysis of current events and media through the lens of predictive programming and a concept called the "meta script," which is described as the big story that becomes history. The host views media, including movie trailers and news, as different forms of propaganda – entertainment propaganda parallel to information propaganda – that are interconnected and reveal a larger narrative. By looking at these things holistically, they aim to arrive at subtexts and bigger pictures.The conversation delved into numerous examples and recurring symbols observed in media and events:Movie trailers discussed included Sinners, Mickey 17, Captain America: Brave New World, Fantastic Four, Final Destination: Bloodlines, The Home, and Welcome to Derry.Recurring symbols and themes highlighted were the Space Needle (linked to EMP, the Electronic Music Project, movie plots, and the sinking of the West), EMP events, the eye/iris and needle into the eye (appearing in movie posters and montages), three pillars/masts (seen in the International Hotel, Space Needle, and a Mexican Navy ship), space interpreted as inner space or mind control, the sinking of America or the West (symbolized by the Titanic, the boat hitting the bridge, the Space Needle, and One World Trade Tower), and various numbers and dates (such as 6-11, 11-6, 84, 216, and 33).Specific events analyzed through this lens included the Trump shooting in Butler (linked to the Riddler, Ave Maria, and specific numbers), a Mexican Navy ship hitting the Brooklyn Bridge (noting the three masts and the death of a cadet named America), the East Palestine train derailment (compared to the Netflix movie White Noise and recent lawsuits against BlackRock and Vanguard), the JFK assassination (connected to Trump symbolism, dates, Macbeth, and a home movie allegedly showing his "death"), and the Reagan shooting (noting the 33-year delay in James Brady's death being ruled a homicide).The host discussed the concept of the "auto-hoaxer" and observed media attempts to frame it negatively. They also touched on "Psychic Driving", the "political horseshoe theory" as a deliberately implemented model, and interpreting world events through the lens of WWE kayfabe.The host mentioned the upcoming release of PSYOP trading cards.

The episode began with the host announcing the launch of a new AI agent called the IPS stenographer in the Discord server. This bot is designed to automatically summarize the latest comments and create infographics every four hours, posting them in a dedicated summary room. Users can also get a synopsis on demand using a specific command. The host mentioned previously doing this manually and used ChatGPT and Grok to help automate the process. They noted that Grok can elaborate on prompts and assisted in activating the bot on Discord.A core theme of the discussion is the analysis of current events and media through the lens of predictive programming and a concept called the "meta script," which is described as the big story that becomes history. The host views media, including movie trailers and news, as different forms of propaganda – entertainment propaganda parallel to information propaganda – that are interconnected and reveal a larger narrative. By looking at these things holistically, they aim to arrive at subtexts and bigger pictures.The conversation delved into numerous examples and recurring symbols observed in media and events:Movie trailers discussed included Sinners, Mickey 17, Captain America: Brave New World, Fantastic Four, Final Destination: Bloodlines, The Home, and Welcome to Derry.Recurring symbols and themes highlighted were the Space Needle (linked to EMP, the Electronic Music Project, movie plots, and the sinking of the West), EMP events, the eye/iris and needle into the eye (appearing in movie posters and montages), three pillars/masts (seen in the International Hotel, Space Needle, and a Mexican Navy ship), space interpreted as inner space or mind control, the sinking of America or the West (symbolized by the Titanic, the boat hitting the bridge, the Space Needle, and One World Trade Tower), and various numbers and dates (such as 6-11, 11-6, 84, 216, and 33).Specific events analyzed through this lens included the Trump shooting in Butler (linked to the Riddler, Ave Maria, and specific numbers), a Mexican Navy ship hitting the Brooklyn Bridge (noting the three masts and the death of a cadet named America), the East Palestine train derailment (compared to the Netflix movie White Noise and recent lawsuits against BlackRock and Vanguard), the JFK assassination (connected to Trump symbolism, dates, Macbeth, and a home movie allegedly showing his "death"), and the Reagan shooting (noting the 33-year delay in James Brady's death being ruled a homicide).The host discussed the concept of the "auto-hoaxer" and observed media attempts to frame it negatively. They also touched on "Psychic Driving", the "political horseshoe theory" as a deliberately implemented model, and interpreting world events through the lens of WWE kayfabe.The host mentioned the upcoming release of PSYOP trading cards.

In this episode, our host Max Louis of MLC, and freelance artist James Brady sit down to explore his journey into the world of game art. James shares how he first got into freelance work, detailing the challenges and rewards of building a career in this competitive field. We dive deep into his experiences, discussing the highs and lows of freelancing, from the creative freedom it offers to the unpredictability of the work. James also gives us an insider's look at his impressive career in AAA game development, revealing what it's like to contribute to some of the industry's most well-known titles.

Editor's note: One of the top reasons we have hundreds of companies and thousands of AI Engineers joining the World's Fair next week is, apart from discussing technology and being present for the big launches planned, to hire and be hired! Listeners loved our previous Elicit episode and were so glad to welcome 2 more members of Elicit back for a guest post (and bonus podcast) on how they think through hiring. Don't miss their AI engineer job description, and template which you can use to create your own hiring plan! How to Hire AI EngineersJames Brady, Head of Engineering @ Elicit (ex Spring, Square, Trigger.io, IBM)Adam Wiggins, Internal Journalist @ Elicit (Cofounder Ink & Switch and Heroku)If you're leading a team that uses AI in your product in some way, you probably need to hire AI engineers. As defined in this article, that's someone with conventional engineering skills in addition to knowledge of language models and prompt engineering, without being a full-fledged Machine Learning expert.But how do you hire someone with this skillset? At Elicit we've been applying machine learning to reasoning tools since 2018, and our technical team is a mix of ML experts and what we can now call AI engineers. This article will cover our process from job description through interviewing. (You can also flip the perspectives here and use it just as easily for how to get hired as an AI engineer!)My own journeyBefore getting into the brass tacks, I want to share my journey to becoming an AI engineer.Up until a few years ago, I was happily working my job as an engineering manager of a big team at a late-stage startup. Like many, I was tracking the rapid increase in AI capabilities stemming from the deep learning revolution, but it was the release of GPT-3 in 2020 which was the watershed moment. At the time, we were all blown away by how the model could string together coherent sentences on demand. (Oh how far we've come since then!)I'd been a professional software engineer for nearly 15 years—enough to have experienced one or two technology cycles—but I could see this was something categorically new. I found this simultaneously exciting and somewhat disconcerting. I knew I wanted to dive into this world, but it seemed like the only path was going back to school for a master's degree in Machine Learning. I started talking with my boss about options for taking a sabbatical or doing a part-time distance learning degree.In 2021, I instead decided to launch a startup focused on productizing new research ideas on ML interpretability. It was through that process that I reached out to Andreas—a leading ML researcher and founder of Elicit—to see if he would be an advisor. Over the next few months, I learned more about Elicit: that they were trying to apply these fascinating technologies to the real-world problems of science, and with a business model that aligned it with safety goals. I realized that I was way more excited about Elicit than I was about my own startup ideas, and wrote about my motivations at the time.Three years later, it's clear this was a seismic shift in my career on the scale of when I chose to leave my comfy engineering job at IBM to go through the Y Combinator program back in 2008. Working with this new breed of technology has been more intellectually stimulating, challenging, and rewarding than I could have imagined.Deep ML expertise not requiredIt's important to note that AI engineers are not ML experts, nor is that their best contribution to a tech team.In our article Living documents as an AI UX pattern, we wrote:It's easy to think that AI advancements are all about training and applying new models, and certainly this is a huge part of our work in the ML team at Elicit. But those of us working in the UX part of the team believe that we have a big contribution to make in how AI is applied to end-user problems.We think of LLMs as a new medium to work with, one that we've barely begun to grasp the contours of. New computing mediums like GUIs in the 1980s, web/cloud in the 90s and 2000s, and multitouch smartphones in the 2000s/2010s opened a whole new era of engineering and design practices. So too will LLMs open new frontiers for our work in the coming decade.To compare to the early era of mobile development: great iOS developers didn't require a detailed understanding of the physics of capacitive touchscreens. But they did need to know the capabilities and limitations of a multi-touch screen, the constrained CPU and storage available, the context in which the user is using it (very different from a webpage or desktop computer), etc.In the same way, an AI engineer needs to work with LLMs as a medium that is fundamentally different from other compute mediums. That means an interest in the ML side of things, whether through their own self-study, tinkering with prompts and model fine-tuning, or following along in #llm-paper-club. But this understanding is so that they can work with the medium effectively versus, say, spending their days training new models.Language models as a chaotic mediumSo if we're not expecting deep ML expertise from AI engineers, what are we expecting? This brings us to what makes LLMs different.We'll assume already that our ideal candidate is already inspired by, and full of ideas about, all the new capabilities AI can bring to software products. But the flip side is all the things that make this new medium difficult to work with. LLM calls are annoying due to high latency (measured in tens of seconds sometimes, rather than milliseconds), extreme variance on latency, high error rates even under normal operation. Not to mention getting extremely different answers to the same prompt provided to the same model on two subsequent calls!The net effect is that an AI engineer, even working at the application development level, needs to have a skillset comparable to distributed systems engineering. Handling errors, retries, asynchronous calls, streaming responses, parallelizing and recombining model calls, the halting problem, and fallbacks are just some of the day-in-the-life of an AI engineer. Chaos engineering gets new life in the era of AI.Skills and qualities in candidatesLet's put together what we don't need (deep ML expertise) with what we do (work with capabilities and limitations of the medium). Thus we start to see what Elicit looks for in AI engineers:* Conventional software engineering skills. Especially back-end engineering on complex, data-intensive applications.* Professional, real-world experience with applications at scale.* Deep, hands-on experience across a few back-end web frameworks.* Light devops and an understanding of infrastructure best practices.* Queues, message buses, event-driven and serverless architectures, … there's no single “correct” approach, but having a deep toolbox to draw from is very important.* A genuine curiosity and enthusiasm for the capabilities of language models.* One or more serious projects (side projects are fine) of using them in interesting ways on a unique domain.* …ideally with some level of factored cognition, e.g. breaking the problem down into chunks, making thoughtful decisions about which things to push to the language model and which stay within the realm of conventional heuristics and compute capabilities.* Personal studying with resources like Elicit's ML reading list. Part of the role is collaborating with the ML engineers and researchers on our team. To do so, the candidate needs to “speak their language” somewhat, just as a mobile engineer needs some familiarity with backends in order to collaborate effectively on API creation with backend engineers.* An understanding of the challenges that come along with working with large models (high latency, variance, etc.) leading to a defensive, fault-first mindset.* Careful and principled handling of error cases, asynchronous code (and ability to reason about and debug it), streaming data, caching, logging and analytics for understanding behavior in production.* This is a similar mindset that one can develop working on conventional apps which are complex, data-intensive, or large-scale apps. The difference is that an AI engineer will need this mindset even when working on relatively small scales!On net, a great AI engineer will combine two seemingly contrasting perspectives: knowledge of, and a sense of wonder for, the capabilities of modern ML models; but also the understanding that this is a difficult and imperfect foundation, and the willingness to build resilient and performant systems on top of it.Here's the resulting AI engineer job description for Elicit. And here's a template that you can borrow from for writing your own JD.Hiring processOnce you know what you're looking for in an AI engineer, the process is not too different from other technical roles. Here's how we do it, broken down into two stages: sourcing and interviewing.SourcingWe're primarily looking for people with (1) a familiarity with and interest in ML, and (2) proven experience building complex systems using web technologies. The former is important for culture fit and as an indication that the candidate will be able to do some light prompt engineering as part of their role. The latter is important because language model APIs are built on top of web standards and—as noted above—aren't always the easiest tools to work with.Only a handful of people have built complex ML-first apps, but fortunately the two qualities listed above are relatively independent. Perhaps they've proven (2) through their professional experience and have some side projects which demonstrate (1).Talking of side projects, evidence of creative and original prototypes is a huge plus as we're evaluating candidates. We've barely scratched the surface of what's possible to build with LLMs—even the current generation of models—so candidates who have been willing to dive into crazy “I wonder if it's possible to…” ideas have a huge advantage.InterviewingThe hard skills we spend most of our time evaluating during our interview process are in the “building complex systems using web technologies” side of things. We will be checking that the candidate is familiar with asynchronous programming, defensive coding, distributed systems concepts and tools, and display an ability to think about scaling and performance. They needn't have 10+ years of experience doing this stuff: even junior candidates can display an aptitude and thirst for learning which gives us confidence they'll be successful tackling the difficult technical challenges we'll put in front of them.One anti-pattern—something which makes my heart sink when I hear it from candidates—is that they have no familiarity with ML, but claim that they're excited to learn about it. The amount of free and easily-accessible resources available is incredible, so a motivated candidate should have already dived into self-study.Putting all that together, here's the interview process that we follow for AI engineer candidates:* 30-minute introductory conversation. Non-technical, explaining the interview process, answering questions, understanding the candidate's career path and goals.* 60-minute technical interview. This is a coding exercise, where we play product manager and the candidate is making changes to a little web app. Here are some examples of topics we might hit upon through that exercise:* Update API endpoints to include extra metadata. Think about appropriate data types. Stub out frontend code to accept the new data.* Convert a synchronous REST API to an asynchronous streaming endpoint.* Cancellation of asynchronous work when a user closes their tab.* Choose an appropriate data structure to represent the pending, active, and completed ML work which is required to service a user request.* 60–90 minute non-technical interview. Walk through the candidate's professional experience, identifying high and low points, getting a grasp of what kinds of challenges and environments they thrive in.* On-site interviews. Half a day in our office in Oakland, meeting as much of the team as possible: more technical and non-technical conversations.The frontier is wide openAlthough Elicit is perhaps further along than other companies on AI engineering, we also acknowledge that this is a brand-new field whose shape and qualities are only just now starting to form. We're looking forward to hearing how other companies do this and being part of the conversation as the role evolves.We're excited for the AI Engineer World's Fair as another next step for this emerging subfield. And of course, check out the Elicit careers page if you're interested in joining our team.Podcast versionTimestamps* [00:00:24] Intros* [00:05:25] Defining the Hiring Process* [00:08:42] Defensive AI Engineering as a chaotic medium* [00:10:26] Tech Choices for Defensive AI Engineering* [00:14:04] How do you Interview for Defensive AI Engineering* [00:19:25] Does Model Shadowing Work?* [00:22:29] Is it too early to standardize Tech stacks?* [00:32:02] Capabilities: Offensive AI Engineering* [00:37:24] AI Engineering Required Knowledge* [00:40:13] ML First Mindset* [00:45:13] AI Engineers and Creativity* [00:47:51] Inside of Me There Are Two Wolves* [00:49:58] Sourcing AI Engineers* [00:58:45] Parting ThoughtsTranscript[00:00:00] swyx: Okay, so welcome to the Latent Space Podcast. This is another remote episode that we're recording. This is the first one that we're doing around a guest post. And I'm very honored to have two of the authors of the post with me, James and Adam from Elicit. Welcome, James. Welcome, Adam.[00:00:22] James Brady: Thank you. Great to be here.[00:00:23] Hey there.[00:00:24] Intros[00:00:24] swyx: Okay, so I think I will do this kind of in order. I think James, you're, you're sort of the primary author. So James, you are head of engineering at Elicit. You also, We're VP Eng at Teespring and Spring as well. And you also , you have a long history in sort of engineering. How did you, , find your way into something like Elicit where, , it's, you, you are basically traditional sort of VP Eng, VP technology type person moving into a more of an AI role.[00:00:53] James Brady: Yeah, that's right. It definitely was something of a Sideways move if not a left turn. So the story there was I'd been doing, as you said, VP technology, CTO type stuff for around about 15 years or so, and Notice that there was this crazy explosion of capability and interesting stuff happening within AI and ML and language models, that kind of thing.[00:01:16] I guess this was in 2019 or so, and decided that I needed to get involved. , this is a kind of generational shift. And Spent maybe a year or so trying to get up to speed on the state of the art, reading papers, reading books, practicing things, that kind of stuff. Was going to found a startup actually in in the space of interpretability and transparency, and through that met Andreas, who has obviously been on the, on the podcast before asked him to be an advisor for my startup, and he countered with, maybe you'd like to come and run the engineering team at Elicit, which it turns out was a much better idea.[00:01:48] And yeah, I kind of quickly changed in that direction. So I think some of the stuff that we're going to be talking about today is how actually a lot of the work when you're building applications with AI and ML looks and smells and feels much more like conventional software engineering with a few key differences rather than really deep ML stuff.[00:02:07] And I think that's one of the reasons why I was able to transfer skills over from one place to the other.[00:02:12] swyx: Yeah, I[00:02:12] James Brady: definitely[00:02:12] swyx: agree with that. I, I do often say that I think AI engineering is about 90 percent software engineering with like the, the 10 percent of like really strong really differentiated AI engineering.[00:02:22] And that might, that obviously that number might change over time. I want to also welcome Adam onto my podcast because you welcomed me onto your podcast two years ago.[00:02:31] Adam Wiggins: Yeah, that was a wonderful episode.[00:02:32] swyx: That was, that was a fun episode. You famously founded Heroku. You just wrapped up a few years working on Muse.[00:02:38] And now you've described yourself as a journalist, internal journalist working on Elicit.[00:02:43] Adam Wiggins: Yeah, well I'm kind of a little bit in a wandering phase here and trying to take this time in between ventures to see what's out there in the world and some of my wandering took me to the Elicit team. And found that they were some of the folks who were doing the most interesting, really deep work in terms of taking the capabilities of language models and applying them to what I feel like are really important problems.[00:03:08] So in this case, science and literature search and, and, and that sort of thing. It fits into my general interest in tools and productivity software. I, I think of it as a tool for thought in many ways, but a tool for science, obviously, if we can accelerate that discovery of new medicines and things like that, that's, that's just so powerful.[00:03:24] But to me, it's a. It's kind of also an opportunity to learn at the feet of some real masters in this space, people who have been working on it since it was, before it was cool, if you want to put it that way. So for me, the last couple of months have been this crash course, and why I sometimes describe myself as an internal journalist is I'm helping to write some, some posts, including Supporting James in this article here we're doing for latent space where I'm just bringing my writing skill and that sort of thing to bear on their very deep domain expertise around language models and applying them to the real world and kind of surface that in a way that's I don't know, accessible, legible, that, that sort of thing.[00:04:03] And so, and the great benefit to me is I get to learn this stuff in a way that I don't think I would, or I haven't, just kind of tinkering with my own side projects.[00:04:12] swyx: I forgot to mention that you also run Ink and Switch, which is one of the leading research labs, in my mind, of the tools for thought productivity space, , whatever people mentioned there, or maybe future of programming even, a little bit of that.[00:04:24] As well. I think you guys definitely started the local first wave. I think there was just the first conference that you guys held. I don't know if you were personally involved.[00:04:31] Adam Wiggins: Yeah, I was one of the co organizers along with a few other folks for, yeah, called Local First Conf here in Berlin.[00:04:36] Huge success from my, my point of view. Local first, obviously, a whole other topic we can talk about on another day. I think there actually is a lot more what would you call it , handshake emoji between kind of language models and the local first data model. And that was part of the topic of the conference here, but yeah, topic for another day.[00:04:55] swyx: Not necessarily. I mean , I, I selected as one of my keynotes, Justine Tunney, working at LlamaFall in Mozilla, because I think there's a lot of people interested in that stuff. But we can, we can focus on the headline topic. And just to not bury the lead, which is we're talking about hire, how to hire AI engineers, this is something that I've been looking for a credible source on for months.[00:05:14] People keep asking me for my opinions. I don't feel qualified to give an opinion and it's not like I have. So that's kind of defined hiring process that I'm super happy with, even though I've worked with a number of AI engineers.[00:05:25] Defining the Hiring Process[00:05:25] swyx: I'll just leave it open to you, James. How was your process of defining your hiring, hiring roles?[00:05:31] James Brady: Yeah. So I think the first thing to say is that we've effectively been hiring for this kind of a role since before you, before you coined the term and tried to kind of build this understanding of what it was.[00:05:42] So, which is not a bad thing. Like it's, it was a, it was a good thing. A concept, a concept that was coming to the fore and effectively needed a name, which is which is what you did. So the reason I mentioned that is I think it was something that we kind of backed into, if you will. We didn't sit down and come up with a brand new role from, from scratch of this is a completely novel set of responsibilities and skills that this person would need.[00:06:06] However, it is a A kind of particular blend of different skills and attitudes and and curiosities interests, which I think makes sense to kind of bundle together. So in the, in the post, the three things that we say are most important for a highly effective AI engineer are first of all, conventional software engineering skills, which is Kind of a given, but definitely worth mentioning.[00:06:30] The second thing is a curiosity and enthusiasm for machine learning and maybe in particular language models. That's certainly true in our case. And then the third thing is to do with basically a fault first mindset, being able to build systems that can handle things going wrong in, in, in some sense.[00:06:49] And yeah, the I think the kind of middle point, the curiosity about ML and language models is probably fairly self evident. They're going to be working with, and prompting, and dealing with the responses from these models, so that's clearly relevant. The last point, though, maybe takes the most explaining.[00:07:07] To do with this fault first mindset and the ability to, to build resilient systems. The reason that is, is so important is because compared to normal APIs, where normal, think of something like a Stripe API or a search API or something like this. The latency when you're working with language models is, is wild, like you can get 10x variation.[00:07:32] I mean, I was looking at the stats before, actually, before, before the podcast. We do often, normally, in fact, see a 10x variation in the P90 latency over the course of, Half an hour, an hour when we're prompting these models, which is way higher than if you're working with a, more kind of conventional conventionally backed API.[00:07:49] And the responses that you get, the actual content and the responses are naturally unpredictable as well. They come back with different formats. Maybe you're expecting JSON. It's not quite JSON. You have to handle this stuff. And also the, the semantics of the messages are unpredictable too, which is, which is a good thing.[00:08:08] Like this is one of the things that you're looking for from these language models, but it all adds up to needing to. Build a resilient, reliable, solid feeling system on top of this fundamentally, well, certainly currently fundamentally shaky foundation. The models do not behave in the way that you would like them to.[00:08:28] And yeah, the ability to structure the code around them such that it does give the user this warm, reassuring, Snappy, solid feeling is is really what we're driving for there.[00:08:42] Defensive AI Engineering as a chaotic medium[00:08:42] Adam Wiggins: What really struck me as we, we dug in on the content for this article was that third point there. The, the language models is this kind of chaotic medium, this, this dragon, this wild horse you're, you're, you're riding and trying to guide in the direction that is going to be useful and reliable to users, because I think.[00:08:58] So much of software engineering is about making things not only high performance and snappy, but really just making it stable, reliable, predictable, which is literally the opposite of what you get from from the language models. And yet, yeah, the output is so useful, and indeed, some of their Creativity, if you want to call it that, which is, is precisely their value.[00:09:19] And so you need to work with this medium. And I guess the nuanced or the thing that came out of Elissa's experience that I thought was so interesting is quite a lot of working with that is things that come from distributed systems engineering. But you have really the AI engineers as we're defining them or, or labeling them on the illicit team is people who are really application developers.[00:09:39] You're building things for end users. You're thinking about, okay, I need to populate this interface with some response to user input. That's useful to the tasks they're trying to do, but you have this. This is the thing, this medium that you're working with that in some ways you need to apply some of this chaos engineering, distributed systems engineering, which typically those people with those engineering skills are not kind of the application level developers with the product mindset or whatever, they're more deep in the guts of a, of a system.[00:10:07] And so it's, those, those skills and, and knowledge do exist throughout the engineering discipline, but sort of putting them together into one person that is That feels like sort of a unique thing and working with the folks on the Elicit team who have that skills I'm quite struck by that unique that unique blend.[00:10:23] I haven't really seen that before in my 30 year career in technology.[00:10:26] Tech Choices for Defensive AI Engineering[00:10:26] swyx: Yeah, that's a Fascinating I like the reference to chaos engineering. I have some appreciation, I think when you had me on your podcast, I was still working at Temporal and that was like a nice Framework, if you live within Temporal's boundaries, you can pretend that all those faults don't exist, and you can, you can code in a sort of very fault tolerant way.[00:10:47] What is, what is you guys solutions around this, actually? Like, I think you're, you're emphasizing having the mindset, but maybe naming some technologies would help? Not saying that you have to adopt these technologies, but they're just, they're just quick vectors into what you're talking about when you're, when you're talking about distributed systems.[00:11:03] Like, that's such a big, chunky word, , like are we talking, are Kubernetes or, and I suspect we're not, , like we're, we're talking something else now.[00:11:10] James Brady: Yeah, that's right. It's more at the application level rather than at the infrastructure level, at least, at least the way that it works for us.[00:11:17] So there's nothing kind of radically novel here. It is more a careful application of existing concepts. So the kinds of tools that we reach for to handle these kind of slightly chaotic objects that Adam was just talking about, are retries and fallbacks and timeouts and careful error handling. And, yeah, the standard stuff, really.[00:11:39] There's also a great degree of dependence. We rely heavily on parallelization because, , these language models are not innately very snappy, and , there's just a lot of I. O. going back and forth. So All these things I'm talking about when I was in my earlier stages of a career, these are kind of the things that are the difficult parts that most senior software engineers will be better at.[00:12:01] It is careful error handling, and concurrency, and fallbacks, and distributed systems, and, , eventual consistency, and all this kind of stuff and As Adam was saying, the kind of person that is deep in the guts of some kind of distributed systems, a really high, high scale backend kind of a problem would probably naturally have these kinds of skills.[00:12:21] But you'll find them on, on day one, if you're building a, , an ML powered app, even if it's not got massive scale. I think one one thing that I would mention that we do do yeah, maybe, maybe two related things, actually. The first is we're big fans of strong typing. We share the types all the way from the Backend Python code all the way to the to the front end in TypeScript and find that is I mean We'd probably do this anyway But it really helps one reason around the shapes of the data which can going to be going back and forth and that's really important When you can't rely upon You you're going to have to coerce the data that you get back from the ML if you want if you want for it to be structured basically speaking and The second thing which is related is we use checked exceptions inside our Python code base, which means that we can use the type system to make sure we are handling, properly handling, all of the, the various things that could be going wrong, all the different exceptions that could be getting raised.[00:13:16] So, checked exceptions are not, not really particularly popular. Actually there's not many people that are big fans of them. For our particular use case, to really make sure that we've not just forgotten to handle, , This particular type of error we have found them useful to to, to force us to think about all the different edge cases that can come up.[00:13:32] swyx: Fascinating. How just a quick note of technology. How do you share types from Python to TypeScript? Do you, do you use GraphQL? Do you use something[00:13:39] James Brady: else? We don't, we don't use GraphQL. Yeah. So we've got the We've got the types defined in Python, that's the source of truth. And we go from the OpenAPI spec, and there's a, there's a tool that you work and use to generate types dynamically, like TypeScript types from those OpenAPI definitions.[00:13:57] swyx: Okay, excellent. Okay, cool. Sorry, sorry for diving into that rabbit hole a little bit. I always like to spell out technologies for people to dig their teeth into.[00:14:04] How do you Interview for Defensive AI Engineering[00:14:04] swyx: One thing I'll, one thing I'll mention quickly is that a lot of the stuff that you mentioned is typically not part of the normal interview loop.[00:14:10] It's actually really hard to interview for because this is the stuff that you polish out in, as you go into production, the coding interviews are typically about the happy path. How do we do that? How do we, how do we design, how do you look for a defensive fault first mindset?[00:14:24] Because you can defensive code all day long and not add functionality. to your to your application.[00:14:29] James Brady: Yeah, it's a great question and I think that's exactly true. Normally the interview is about the happy path and then there's maybe a box checking exercise at the end of the candidate says of course in reality I would handle the edge cases or something like this and that unfortunately isn't isn't quite good enough when when the happy path is is very very narrow and yeah there's lots of weirdness on either side so basically speaking, it's just a case of, of foregrounding those kind of concerns through the interview process.[00:14:58] It's, there's, there's no magic to it. We, we talk about this in the, in the po in the post that we're gonna be putting up on, on Laton space. The, there's two main technical exercises that we do through our interview process for this role. The first is more coding focus, and the second is more system designy.[00:15:16] Yeah. White whiteboarding a potential solution. And in, without giving too much away in the coding exercise. You do need to think about edge cases. You do need to think about errors. The exercise consists of adding features and fixing bugs inside the code base. And in both of those two cases, it does demand, because of the way that we set the application up and the interview up, it does demand that you think about something other than the happy path.[00:15:41] But your thinking is the right prompt of how do we get the candidate thinking outside of the, the kind of normal Sweet spot, smooth smooth, smoothly paved path. In terms of the system design interview, that's a little easier to prompt this kind of fault first mindset because it's very easy in that situation just to say, let's imagine that, , this node dies, how does the app still work?[00:16:03] Let's imagine that this network is, is going super slow. Let's imagine that, I don't know, like you, you run out of, you run out of capacity in, in, in this database that you've sketched out here, how do you handle that, that, that sort of stuff. So. It's, in both cases, they're not firmly anchored to and built specifically around language models and ways language models can go wrong, but we do exercise the same muscles of thinking defensively and yeah, foregrounding the edge cases, basically.[00:16:32] Adam Wiggins: James, earlier there you mentioned retries. And this is something that I think I've seen some interesting debates internally about things regarding, first of all, retries are, can be costly, right? In general, this medium, in addition to having this incredibly high variance and response rate, and, , being non deterministic, is actually quite expensive.[00:16:50] And so, in many cases, doing a retry when you get a fail does make sense, but actually that has an impact on cost. And so there is Some sense to which, at least I've seen the AI engineers on our team, worry about that. They worry about, okay, how do we give the best user experience, but balance that against what the infrastructure is going to, , is going to cost our company, which I think is again, an interesting mix of, yeah, again, it's a little bit the distributed system mindset, but it's also a product perspective and you're thinking about the end user experience, but also the.[00:17:22] The bottom line for the business, you're bringing together a lot of a lot of qualities there. And there's also the fallback case, which is kind of, kind of a related or adjacent one. I think there was also a discussion on that internally where, I think it maybe was search, there was something recently where there was one of the frontline search providers was having some, yeah, slowness and outages, and essentially then we had a fallback, but essentially that gave people for a while, especially new users that come in that don't the difference, they're getting a They're getting worse results for their search.[00:17:52] And so then you have this debate about, okay, there's sort of what is correct to do from an engineering perspective, but then there's also what actually is the best result for the user. Is giving them a kind of a worse answer to their search result better, or is it better to kind of give them an error and be like, yeah, sorry, it's not working right at the moment, try again.[00:18:12] Later, both are obviously non optimal, but but this is the kind of thing I think that that you run into or, or the kind of thing we need to grapple with a lot more than you would other kinds of, of mediums.[00:18:24] James Brady: Yeah, that's a really good example. I think it brings to the fore the two different things that you could be optimizing for of uptime and response at all costs on one end of the spectrum and then effectively fragility, but kind of, if you get a response, it's the best response we can come up with at the other end of the spectrum.[00:18:43] And where you want to land there kind of depends on, well, it certainly depends on the app, obviously depends on the user. I think it depends on the, feature within the app as well. So in the search case that you, that you mentioned there, in retrospect, we probably didn't want to have the fallback. And we've actually just recently on Monday, changed that to Show an error message rather than giving people a kind of degraded experience in other situations We could use for example a large language model from a large language model from provider B rather than provider A and Get something which is within the A few percentage points performance, and that's just a really different situation.[00:19:21] So yeah, like any interesting question, the answer is, it depends.[00:19:25] Does Model Shadowing Work?[00:19:25] swyx: I do hear a lot of people suggesting I, let's call this model shadowing as a defensive technique, which is, if OpenAI happens to be down, which, , happens more often than people think then you fall back to anthropic or something.[00:19:38] How realistic is that, right? Like you, don't you have to develop completely different prompts for different models and won't the, won't the performance of your application suffer from whatever reason, right? Like it may be caused differently or it's not maintained in the same way. I, I think that people raise this idea of fallbacks to models, but I don't think it's, I don't, I don't see it practiced very much.[00:20:02] James Brady: Yeah, it is, you, you definitely need to have a different prompt if you want to stay within a few percentage points degradation Like I, like I said before, and that certainly comes at a cost, like fallbacks and backups and things like this It's really easy for them to go stale and kind of flake out on you because they're off the beaten track And In our particular case inside of Elicit, we do have fallbacks for a number of kind of crucial functions where it's going to be very obvious if something has gone wrong, but we don't have fallbacks in all cases.[00:20:40] It really depends on a task to task basis throughout the app. So I can't give you a kind of a, a single kind of simple rule of thumb for, in this case, do this. And in the other, do that. But yeah, we've it's a little bit easier now that the APIs between the anthropic models and opening are more similar than they used to be.[00:20:59] So we don't have two totally separate code paths with different protocols, like wire protocols to, to speak, which makes things easier, but you're right. You do need to have different prompts if you want to, have similar performance across the providers.[00:21:12] Adam Wiggins: I'll also note, just observing again as a relative newcomer here, I was surprised, impressed, not sure what the word is for it, at the blend of different backends that the team is using.[00:21:24] And so there's many The product presents as kind of one single interface, but there's actually several dozen kind of main paths. There's like, for example, the search versus a data extraction of a certain type, versus chat with papers, versus And each one of these, , the team has worked very hard to pick the right Model for the job and craft the prompt there, but also is constantly testing new ones.[00:21:48] So a new one comes out from either, from the big providers or in some cases, Our own models that are , running on, on essentially our own infrastructure. And sometimes that's more about cost or performance, but the point is kind of switching very fluidly between them and, and very quickly because this field is moving so fast and there's new ones to choose from all the time is like part of the day to day, I would say.[00:22:11] So it isn't more of a like, there's a main one, it's been kind of the same for a year, there's a fallback, but it's got cobwebs on it. It's more like which model and which prompt is changing weekly. And so I think it's quite, quite reasonable to to, to, to have a fallback that you can expect might work.[00:22:29] Is it too early to standardize Tech stacks?[00:22:29] swyx: I'm curious because you guys have had experience working at both, , Elicit, which is a smaller operation and, and larger companies. A lot of companies are looking at this with a certain amount of trepidation as, as, , it's very chaotic. When you have, when you have , one engineering team that, that, knows everyone else's names and like, , they, they, they, they meet constantly in Slack and knows what's going on.[00:22:50] It's easier to, to sync on technology choices. When you have a hundred teams, all shipping AI products and all making their own independent tech choices. It can be, it can be very hard to control. One solution I'm hearing from like the sales forces of the worlds and Walmarts of the world is that they are creating their own AI gateway, right?[00:23:05] Internal AI gateway. This is the one model hub that controls all the things and has our standards. Is that a feasible thing? Is that something that you would want? Is that something you have and you're working towards? What are your thoughts on this stuff? Like, Centralization of control or like an AI platform internally.[00:23:22] James Brady: Certainly for larger organizations and organizations that are doing things which maybe are running into HIPAA compliance or other, um, legislative tools like that. It could make a lot of sense. Yeah. I think for the TLDR for something like Elicit is we are small enough, as you indicated, and need to have full control over all the levers available and switch between different models and different prompts and whatnot, as Adam was just saying, that that kind of thing wouldn't work for us.[00:23:52] But yeah, I've spoken with and, um, advised a couple of companies that are trying to sell into that kind of a space or at a larger stage, and it does seem to make a lot of sense for them. So, for example, if you're trying to sell If you're looking to sell to a large enterprise and they cannot have any data leaving the EU, then you need to be really careful about someone just accidentally putting in, , the sort of US East 1 GPT 4 endpoints or something like this.[00:24:22] I'd be interested in understanding better what the specific problem is that they're looking to solve with that, whether it is to do with data security or centralization of billing, or if they have a kind of Suite of prompts or something like this that people can choose from so they don't need to reinvent the wheel again and again I wouldn't be able to say without understanding the problems and their proposed solutions , which kind of situations that be better or worse fit for but yeah for illicit where really the The secret sauce, if there is a secret sauce, is which models we're using, how we're using them, how we're combining them, how we're thinking about the user problem, how we're thinking about all these pieces coming together.[00:25:02] You really need to have all of the affordances available to you to be able to experiment with things and iterate rapidly. And generally speaking, whenever you put these kind of layers of abstraction and control and generalization in there, that, that gets in the way. So, so for us, it would not work.[00:25:19] Adam Wiggins: Do you feel like there's always a tendency to want to reach for standardization and abstractions pretty early in a new technology cycle?[00:25:26] There's something comforting there, or you feel like you can see them, or whatever. I feel like there's some of that discussion around lang chain right now. But yeah, this is not only so early, but also moving so fast. , I think it's . I think it's tough to, to ask for that. That's, that's not the, that's not the space we're in, but the, yeah, the larger an organization, the more that's your, your default is to, to, to want to reach for that.[00:25:48] It, it, it's a sort of comfort.[00:25:51] swyx: Yeah, I find it interesting that you would say that , being a founder of Heroku where , you were one of the first platforms as a service that more or less standardized what, , that sort of early developer experience should have looked like.[00:26:04] And I think basically people are feeling the differences between calling various model lab APIs and having an actual AI platform where. , all, all their development needs are thought of for them. , it's, it's very much, and, and I, I defined this in my AI engineer post as well.[00:26:19] Like the model labs just see their job ending at serving models and that's about it. But actually the responsibility of the AI engineer has to fill in a lot of the gaps beyond that. So.[00:26:31] Adam Wiggins: Yeah, that's true. I think, , a huge part of the exercise with Heroku, which It was largely inspired by Rails, which itself was one of the first frameworks to standardize the SQL database.[00:26:42] And people had been building apps like that for many, many years. I had built many apps. I had made my own templates based on that. I think others had done it. And Rails came along at the right moment. We had been doing it long enough that you see the patterns and then you can say look let's let's extract those into a framework that's going to make it not only easier to build for the experts but for people who are relatively new the best practices are encoded into you.[00:27:07] That framework, , Model View Controller, to take one example. But then, yeah, once you see that, and once you experience the power of a framework, and again, it's so comforting, and you can develop faster, and it's easier to onboard new people to it because you have these standards. And this consistency, then folks want that for something new that's evolving.[00:27:29] Now here I'm thinking maybe if you fast forward a little to, for example, when React came on the on the scene, , a decade ago or whatever. And then, okay, we need to do state management. What's that? And then there's, , there's a new library every six months. Okay, this is the one, this is the gold standard.[00:27:42] And then, , six months later, that's deprecated. Because of course, it's evolving, you need to figure it out, like the tacit knowledge and the experience of putting it in practice and seeing what those real What those real needs are are, are critical, and so it's, it is really about finding the right time to say yes, we can generalize, we can make standards and abstractions, whether it's for a company, whether it's for, , a library, an open source library, for a whole class of apps and it, it's very much a, much more of a A judgment call slash just a sense of taste or , experience to be able to say, Yeah, we're at the right point.[00:28:16] We can standardize this. But it's at least my, my very, again, and I'm so new to that, this world compared to you both, but my, my sense is, yeah, still the wild west. That's what makes it so exciting and feels kind of too early for too much. too much in the way of standardized abstractions. Not that it's not interesting to try, but , you can't necessarily get there in the same way Rails did until you've got that decade of experience of whatever building different classes of apps in that, with that technology.[00:28:45] James Brady: Yeah, it's, it's interesting to think about what is going to stay more static and what is expected to change over the coming five years, let's say. Which seems like when I think about it through an ML lens, it's an incredibly long time. And if you just said five years, it doesn't seem, doesn't seem that long.[00:29:01] I think that, that kind of talks to part of the problem here is that things that are moving are moving incredibly quickly. I would expect, this is my, my hot take rather than some kind of official carefully thought out position, but my hot take would be something like the You can, you'll be able to get to good quality apps without doing really careful prompt engineering.[00:29:21] I don't think that prompt engineering is going to be a kind of durable differential skill that people will, will hold. I do think that, The way that you set up the ML problem to kind of ask the right questions, if you see what I mean, rather than the specific phrasing of exactly how you're doing chain of thought or few shot or something in the prompt I think the way that you set it up is, is probably going to be remain to be trickier for longer.[00:29:47] And I think some of the operational challenges that we've been talking about of wild variations in, in, in latency, And handling the, I mean, one way to think about these models is the first lesson that you learn when, when you're an engineer, software engineer, is that you need to sanitize user input, right?[00:30:05] It was, I think it was the top OWASP security threat for a while. Like you, you have to sanitize and validate user input. And we got used to that. And it kind of feels like this is the, The shell around the app and then everything else inside you're kind of in control of and you can grasp and you can debug, etc.[00:30:22] And what we've effectively done is, through some kind of weird rearguard action, we've now got these slightly chaotic things. I think of them more as complex adaptive systems, which , related but a bit different. Definitely have some of the same dynamics. We've, we've injected these into the foundations of the, of the app and you kind of now need to think with this defined defensive mindset downwards as well as upwards if you, if you see what I mean.[00:30:46] So I think it would gonna, it's, I think it will take a while for us to truly wrap our heads around that. And also these kinds of problems where you have to handle things being unreliable and slow sometimes and whatever else, even if it doesn't happen very often, there isn't some kind of industry wide accepted way of handling that at massive scale.[00:31:10] There are definitely patterns and anti patterns and tools and whatnot, but it's not like this is a solved problem. So I would expect that it's not going to go down easily as a, as a solvable problem at the ML scale either.[00:31:23] swyx: Yeah, excellent. I would describe in, in the terminology of the stuff that I've written in the past, I describe this inversion of architecture as sort of LLM at the core versus LLM or code at the core.[00:31:34] We're very used to code at the core. Actually, we can scale that very well. When we build LLM core apps, we have to realize that the, the central part of our app that's orchestrating things is actually prompt, prone to, , prompt injections and non determinism and all that, all that good stuff.[00:31:48] I, I did want to move the conversation a little bit from the sort of defensive side of things to the more offensive or, , the fun side of things, capabilities side of things, because that is the other part. of the job description that we kind of skimmed over. So I'll, I'll repeat what you said earlier.[00:32:02] Capabilities: Offensive AI Engineering[00:32:02] swyx: It's, you want people to have a genuine curiosity and enthusiasm for the capabilities of language models. We just, we're recording this the day after Anthropic just dropped Cloud 3. 5. And I was wondering, , maybe this is a good, good exercise is how do people have Curiosity and enthusiasm for capabilities language models when for example the research paper for cloud 3.[00:32:22] 5 is four pages[00:32:23] James Brady: Maybe that's not a bad thing actually in this particular case So yeah If you really want to know exactly how the sausage was made That hasn't been possible for a few years now in fact for for these new models but from our perspective as when we're building illicit What we primarily care about is what can these models do?[00:32:41] How do they perform on the tasks that we already have set up and the evaluations we have in mind? And then on a slightly more expansive note, what kinds of new capabilities do they seem to have? Can we elicit, no pun intended, from the models? For example, well, there's, there's very obvious ones like multimodality , there wasn't that and then there was that, or it could be something a bit more subtle, like it seems to be getting better at reasoning, or it seems to be getting better at metacognition, or Or it seems to be getting better at marking its own work and giving calibrated confidence estimates, things like this.[00:33:19] So yeah, there's, there's plenty to be excited about there. It's just that yeah, there's rightly or wrongly been this, this, this shift over the last few years to not give all the details. So no, but from application development perspective we, every time there's a new model release, there's a flow of activity in our Slack, and we try to figure out what's going on.[00:33:38] What it can do, what it can't do, run our evaluation frameworks, and yeah, it's always an exciting, happy day.[00:33:44] Adam Wiggins: Yeah, from my perspective, what I'm seeing from the folks on the team is, first of all, just awareness of the new stuff that's coming out, so that's, , an enthusiasm for the space and following along, and then being able to very quickly, partially that's having Slack to do this, but be able to quickly map that to, okay, What does this do for our specific case?[00:34:07] And that, the simple version of that is, let's run the evaluation framework, which Lissa has quite a comprehensive one. I'm actually working on an article on that right now, which I'm very excited about, because it's a very interesting world of things. But basically, you can just try, not just, but try the new model in the evaluations framework.[00:34:27] Run it. It has a whole slew of benchmarks, which includes not just Accuracy and confidence, but also things like performance, cost, and so on. And all of these things may trade off against each other. Maybe it's actually, it's very slightly worse, but it's way faster and way cheaper, so actually this might be a net win, for example.[00:34:46] Or, it's way more accurate. But that comes at its slower and higher cost, and so now you need to think about those trade offs. And so to me, coming back to the qualities of an AI engineer, especially when you're trying to hire for them, It's this, it's, it is very much an application developer in the sense of a product mindset of What are our users or our customers trying to do?[00:35:08] What problem do they need solved? Or what what does our product solve for them? And how does the capabilities of a particular model potentially solve that better for them than what exists today? And by the way, what exists today is becoming an increasingly gigantic cornucopia of things, right? And so, You say, okay, this new model has these capabilities, therefore, , the simple version of that is plug it into our existing evaluations and just look at that and see if it, it seems like it's better for a straight out swap out, but when you talk about, for example, you have multimodal capabilities, and then you say, okay, wait a minute, actually, maybe there's a new feature or a whole new There's a whole bunch of ways we could be using it, not just a simple model swap out, but actually a different thing we could do that we couldn't do before that would have been too slow, or too inaccurate, or something like that, that now we do have the capability to do.[00:35:58] I think of that as being a great thing. I don't even know if I want to call it a skill, maybe it's even like an attitude or a perspective, which is a desire to both be excited about the new technology, , the new models and things as they come along, but also holding in the mind, what does our product do?[00:36:16] Who is our user? And how can we connect the capabilities of this technology to how we're helping people in whatever it is our product does?[00:36:25] James Brady: Yeah, I'm just looking at one of our internal Slack channels where we talk about things like new new model releases and that kind of thing And it is notable looking through these the kind of things that people are excited about and not It's, I don't know the context, the context window is much larger, or it's, look at how many parameters it has, or something like this.[00:36:44] It's always framed in terms of maybe this could be applied to that kind of part of Elicit, or maybe this would open up this new possibility for Elicit. And, as Adam was saying, yeah, I don't think it's really a I don't think it's a novel or separate skill, it's the kind of attitude I would like to have all engineers to have at a company our stage, actually.[00:37:05] And maybe more generally, even, which is not just kind of getting nerd sniped by some kind of technology number, fancy metric or something, but how is this actually going to be applicable to the thing Which matters in the end. How is this going to help users? How is this going to help move things forward strategically?[00:37:23] That kind of, that kind of thing.[00:37:24] AI Engineering Required Knowledge[00:37:24] swyx: Yeah, applying what , I think, is, is, is the key here. Getting hands on as well. I would, I would recommend a few resources for people listening along. The first is Elicit's ML reading list, which I, I found so delightful after talking with Andreas about it.[00:37:38] It looks like that's part of your onboarding. We've actually set up an asynchronous paper club instead of my discord for people following on that reading list. I love that you separate things out into tier one and two and three, and that gives people a factored cognition way of Looking into the, the, the corpus, right?[00:37:55] Like yes, the, the corpus of things to know is growing and the water is slowly rising as far as what a bar for a competent AI engineer is. But I think, , having some structured thought as to what are the big ones that everyone must know I think is, is, is key. It's something I, I haven't really defined for people and I'm, I'm glad that this is actually has something out there that people can refer to.[00:38:15] Yeah, I wouldn't necessarily like make it required for like the job. Interview maybe, but , it'd be interesting to see like, what would be a red flag. If some AI engineer would not know, I don't know what, , I don't know where we would stoop to, to call something required knowledge, , or you're not part of the cool kids club.[00:38:33] But there increasingly is something like that, right? Like, not knowing what context is, is a black mark, in my opinion, right?[00:38:40] I think it, I think it does connect back to what we were saying before of this genuine Curiosity about and that. Well, maybe it's, maybe it's actually that combined with something else, which is really important, which is a self starting bias towards action, kind of a mindset, which again, everybody needs.[00:38:56] Exactly. Yeah. Everyone needs that. So if you put those two together, or if I'm truly curious about this and I'm going to kind of figure out how to make things happen, then you end up with people. Reading, reading lists, reading papers, doing side projects, this kind of, this kind of thing. So it isn't something that we explicitly included.[00:39:14] We don't have a, we don't have an ML focused interview for the AI engineer role at all, actually. It doesn't really seem helpful. The skills which we are checking for, as I mentioned before, this kind of fault first mindset. And conventional software engineering kind of thing. It's, it's 0. 1 and 0.[00:39:32] 3 on the list that, that we talked about. In terms of checking for ML curiosity and there are, how familiar they are with these concepts. That's more through talking interviews and culture fit types of things. We want for them to have a take on what Elisa is doing. doing, certainly as they progress through the interview process.[00:39:50] They don't need to be completely up to date on everything we've ever done on day zero. Although, , that's always nice when it happens. But for them to really engage with it, ask interesting questions, and be kind of bought into our view on how we want ML to proceed. I think that is really important, and that would reveal that they have this kind of this interest, this ML curiosity.[00:40:13] ML First Mindset[00:40:13] swyx: There's a second aspect to that. I don't know if now's the right time to talk about it, which is, I do think that an ML first approach to building software is something of a different mindset. I could, I could describe that a bit now if that, if that seems good, but yeah, I'm a team. Okay. So yeah, I think when I joined Elicit, this was the biggest adjustment that I had to make personally.[00:40:37] So as I said before, I'd been, Effectively building conventional software stuff for 15 years or so, something like this, well, for longer actually, but professionally for like 15 years. And had a lot of pattern matching built into my brain and kind of muscle memory for if you see this kind of problem, then you do that kind of a thing.[00:40:56] And I had to unlearn quite a lot of that when joining Elicit because we truly are ML first and try to use ML to the fullest. And some of the things that that means is, This relinquishing of control almost, at some point you are calling into this fairly opaque black box thing and hoping it does the right thing and dealing with the stuff that it sends back to you.[00:41:17] And that's very different if you're interacting with, again, APIs and databases, that kind of a, that kind of a thing. You can't just keep on debugging. At some point you hit this, this obscure wall. And I think the second, the second part to this is the pattern I was used to is that. The external parts of the app are where most of the messiness is, not necessarily in terms of code, but in terms of degrees of freedom, almost.[00:41:44] If the user can and will do anything at any point, and they'll put all sorts of wonky stuff inside of text inputs, and they'll click buttons you didn't expect them to click, and all this kind of thing. But then by the time you're down into your SQL queries, for example, as long as you've done your input validation, things are pretty pretty well defined.[00:42:01] And that, as we said before, is not really the case. When you're working with language models, there is this kind of intrinsic uncertainty when you get down to the, to the kernel, down to the core. Even, even beyond that, there's all that stuff is somewhat defensive and these are things to be wary of to some degree.[00:42:18] Though the flip side of that, the really kind of positive part of taking an ML first mindset when you're building applications is that you, If you, once you get comfortable taking your hands off the wheel at a certain point and relinquishing control, letting go then really kind of unexpected powerful things can happen if you lean on the, if you lean on the capabilities of the model without trying to overly constrain and slice and dice problems with to the point where you're not really wringing out the most capability from the model that you, that you might.[00:42:47] So, I was trying to think of examples of this earlier, and one that came to mind was we were working really early when just after I joined Elicit, we were working on something where we wanted to generate text and include citations embedded within it. So it'd have a claim, and then a, , square brackets, one, in superscript, something, something like this.[00:43:07] And. Every fiber in my, in my, in my being was screaming that we should have some way of kind of forcing this to happen or Structured output such that we could guarantee that this citation was always going to be present later on that the kind of the indication of a footnote would actually match up with the footnote itself and Kind of went into this symbolic.[00:43:28] I need full control kind of kind of mindset and it was notable that Andreas Who's our CEO, again, has been on the podcast, was was the opposite. He was just kind of, give it a couple of examples and it'll probably be fine. And then we can kind of figure out with a regular expression at the end. And it really did not sit well with me, to be honest.[00:43:46] I was like, but it could say anything. I could say, it could literally say anything. And I don't know about just using a regex to sort of handle this. This is a potent feature of the app. But , this is that was my first kind of, , The starkest introduction to this ML first mindset, I suppose, which Andreas has been cultivating for much longer than me, much longer than most, of yeah, there might be some surprises of stuff you get back from the model, but you can also It's about finding the sweet spot, I suppose, where you don't want to give a completely open ended prompt to the model and expect it to do exactly the right thing.[00:44:25] You can ask it too much and it gets confused and starts repeating itself or goes around in loops or just goes off in a random direction or something like this. But you can also over constrain the model. And not really make the most of the, of the capabilities. And I think that is a mindset adjustment that most people who are coming into AI engineering afresh would need to make of yeah, giving up control and expecting that there's going to be a little bit of kind of extra pain and defensive stuff on the tail end, but the benefits that you get as a, as a result are really striking.[00:44:58] The ML first mindset, I think, is something that I struggle with as well, because the errors, when they do happen, are bad. , they will hallucinate, and your systems will not catch it sometimes if you don't have large enough of a sample set.[00:45:13] AI Engineers and Creativity[00:45:13] swyx: I'll leave it open to you, Adam. What else do you think about when you think about curiosity and exploring capabilities?[00:45:22] Do people are there reliable ways to get people to push themselves? for joining us on Capabilities, because I think a lot of times we have this implicit overconfidence, maybe, of we think we know what it is, what a thing is, when actually we don't, and we need to keep a more open mind, and I think you do a particularly good job of Always having an open mind, and I want to get that out of more engineers that I talk to, but I, I, I, I struggle sometimes.[00:45:45] Adam Wiggins: I suppose being an engineer is, at its heart, this sort of contradiction of, on one hand, yeah,

Today's Mystery: A late-night distress call from a professional building sends Detectives Scanlon and Grady into the depths of a crime that defies expectations. Amidst the echo of multiple shots fired, they find themselves piecing together the fragments of a life lived in the shadows. An old woman's untimely death in an empty office, a janitor with a story that doesn't quite fit, and a switchboard operator who knows more than she's telling.Original Radio Broadcast Date: Mid-1950sOriginating in New York:Starring: Bill Zuckert as RJ Scanlon and Chuck Webster as James Brady, Charlotte Manson, Arthur ColeSuppoSupport the show monthly at patreon.greatdetectives.netPatreon Supporter of the Day: Christine, Patreon supporter since November 2018Support the show on a one-time basis at http://support.greatdetectives.net.Mail a donation to: Adam Graham, PO Box 15913, Boise, Idaho 83715Take the listener survey…http://survey.greatdetectives.netGive us a call 208-991-4783Become one of ourfriends on Facebook.Follow us on Instagram at http://instagram.com/greatdetectivesFollow us on Twitter@radiodetectivesJoin us again tomorrow for another detective drama from the Golden Age of Radio.

Get ready for an electrifying episode of FitMIND FitBODY featuring the multi-talented James Brady! From shredding guitars in a heavy metal band to delving deep into his PhD and hitting the marathon trails, James's journey is nothing short of extraordinary. Join us as we explore how his early years in music, academic achievements, and passion for running intertwine, offering a unique perspective on life's diverse rhythms. Tune in and be inspired by James's relentless drive and eclectic experiences! Running tips from James - 1. Stay Consistent: Run regularly to build endurance and form healthy habits. 2. Enjoy the Scenery: Choose beautiful places to run, which can make running more enjoyable and less of a chore. 3. Listen to Your Body: If something hurts or feels off, don't push through pain. Adjust your running accordingly. 4. Vary Your Running: Change up where and how you run to keep it interesting and work different muscles. 5. Keep Motivated: Set small, achievable goals to stay focused and motivated. 6. Rest and Recover: Make sure to rest adequately between runs to allow your body to recover and prevent injuries. **A couple of BIG favours: 1) please like and review this podcast so more people will discover it :) 2) come on the podcast and talk about your running journey and/or refer someone you'd love me to interview (whether you know them or not :) )  Lets not keep the power of running a secret any more!  Hit me up on Facebook/Instagram (FitMIND FitBODY) or send me an email - Michelle @ FitMINDFitBODY .co  Don't miss an episode of the FitMind FitBODY Podcast. Sign up to our email list and get notified when new episodes are released. https://fitmindfitbody.co/podcast/ 

In this episode, Dr. Victor Cha is joined by Dr. James Brady to discuss the recent earthquake, the political fundraising scandal, and speculation regarding Japan-DPRK relations in 2024.

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James Brady, Head of Engineering at Ought.org and one of the impressive signatories on the open letter to "pause Giant AI Experiments" (in addition to: Elon Musk and some other notable minds and leaders in society including: Steve Wozniak, Co-founder, Apple Andrew Yang, Forward Party, Co-Chair, Presidential Candidate 2020, NYT Bestselling Author, Presidential Ambassador of Global Entrepreneurship Yoshua Bengio, Founder and Scientific Director at Mila, Turing Prize winner and professor at University of Montreal Stuart Russell, Berkeley, Professor of Computer Science, director of the Center for Intelligent Systems, and co-author of the standard textbook “Artificial Intelligence: a Modern Approach" Bart Selman, Cornell, Professor of Computer Science, past president of AAAI and 27559 other well known souls) helps us understand the many implications of AI, society and very importantly for us, Education. We spend more than the average time with James exploring his life as a son of teachers (who I truly admire), a Cambridge University grad and one of the earliest Y Combinator alumni. His thoughts are ones that I want to come back and listen to over and over again. I feel like the didactic impact from just this conversation is worth at least 3 or 8 listens to this one interview. I highly recommend contrasting it with Lex Fridman's interview of Sam Altman (https://www.youtube.com/watch?v=L_Guz73e6fw) or even Guy Raz's interview with him (https://podcasts.apple.com/nl/podcast/hibt-lab-openai-sam-altman/id1150510297?i=1000580232536) or even Reid Hoffman's (https://www.youtube.com/watch?v=tPJIpx3KscY). I think Tim Ferris also did one with him at one point, but I can't find it to share. Please feel free to add it to the comments or anywhere you can. James is a fascinating perspective and this interview, I believe is possibly worth listening just as much as the 3 former ones -- just saying.

The fellow Dick Cheney shot during a quail hunt just died, at 95 – 16 years after the incident. Will Cheney be charged with murder? Before you answer, remember when Reagan's press secretary James Brady died 34 years after being shot by John Hinckley, prosecutors considered charging him.

Tonight on Piers Morgan Uncensored, Piers calls for Liz Truss to resign from our studios in New York. Former Tory MP Louise Mensch thinks it's now the party's duty to get rid of Liz Truss. Piers hosts an exclusive live interview with John Hinckley Jr - the man who tried to assassinate President Reagan - to find out if he is a changed man. Piers asks if he is responsible for the death of public official James Brady, who was paralysed during the Reagan shooting, and also speaks to Hinckley Jr about contemporary gun culture in the United States. Watch Piers Morgan Uncensored at 8pm on TalkTV on Sky 526, Virgin Media 627, Freeview 237 and Freesat 217. Listen on DAB+ and app. Hosted on Acast. See acast.com/privacy for more information.

President of the United States Ronald Reagan was shot and wounded by John Hinckley Jr. in Washington, D.C. as he was returning to his limousine after a speaking engagement at the Washington Hilton. Hinckley believed the attack would impress actress Jodie Foster, with whom he had developed an erotomanic obsession. Reagan was seriously wounded by a .22 Long Rifle bullet that ricocheted off the side of the presidential limousine and hit him in the left underarm, breaking a rib, puncturing a lung, and causing serious internal bleeding. He was close to death upon arrival at George Washington University Hospital but was stabilized in the emergency room, then underwent emergency exploratory surgery. He recovered and was released from the hospital on April 11. No formal invocation of sections #3 or #4 of the Constitution's 25th amendment (concerning the vice president assuming the president's powers and duties) took place, though Secretary of State Alexander Haig stated that he was "in control here" at the White House until Vice President George H. W. Bush returned to Washington from Fort Worth, Texas. White House press secretary James Brady, Secret Service agent Tim McCarthy, and DC police officer Thomas Delahanty were also wounded. All three survived, but Brady had brain damage and was permanently disabled. His death in 2014 was considered a homicide because it was ultimately caused by his injury. --- Support this podcast: https://anchor.fm/art-mcdermott/support

In 1967, two indigenous men are prospecting for uranium in Saskatchewan when they vanish from their lakeside camp. Canadian authorities determine they got lost and died in an accident — case closed. But their closest friends are convinced otherwise: James Brady and Abbie Halkett were murdered.  Parcasters, we have exciting news! Our first book hits bookshelves July 12th. Don't miss this chilling summer read that takes you deep into the darkest sides of human nature. Learn more at www.parcast.com/cults! Learn more about your ad choices. Visit podcastchoices.com/adchoices

Casting The Spotlight 3-Year Anniversary Special to the date hosts none other than #Top2 professional wrestlers & great friends of ours, Savanna Stone & James Brady. For the first time in 3 years, Brady & Stone return to their Midwest stomping grounds for a wrestling show and encapsulate their current trials & tribulations for friends and audiences alike. We dig down deeper in this episode than probably any episode that has come before, as all parties involved share very real experiences to those listening. We talk pro wrestling, past struggles & heartbreaking hardships, giving life even more purpose following the deaths of close friends & loved ones, and so much more. We promise you this is an episode you will always remember, as we touch upon the listener's heart & soul like never before. We encourage all to tune in for this very special episode. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app --- Send in a voice message: https://anchor.fm/timothy-bollinger/message

Ahead of his PWE Interstate Championship title match, Mr. Attitude James Brady stopped by to discuss his career, returning back to the Midwest, teaming with Savannah Stone, overcoming injuries, and enjoying life.

With the war in Ukraine still raging in all its dimensions and likely to continue for the foreseeable future, the U.S. and its allies continue to apply and add sanctions while attempting to mitigate the negative ramifications for the global economy. As businesses acclimate to a new environment, Teneo experts Wolfango Piccoli, Co-President, Political Risk Advisory; Gabriel Wildau, Managing Director; Emily Stromquist, Managing Director; Andrius Tursa, Central & Eastern Europe Advisor; and James Brady, Vice President, join our host Kevin Kajiwara for an important update on Russia's invasion of Ukraine and the near- and long-term implications on global energy markets, international energy security, economic policy and the global operating environment.

She's "Unbreakable" and on this episode Savanna Stone joined us to talk about buying a house, finding her voice in wrestling, moving from the Midwest to Cali, the importance of James Brady and more.

Em 30 de março de 1981, o presidente Ronald Reagan foi alvejado no peito ao sair de um hotel em Washington por John Hinckley, Jr., um norte-americano desempregado e aparentemente transtornado. O presidente tinha acabado de pronunciar um discurso num encontro com sindicatos no hotel Hilton e caminhava com a comitiva para a limusine quando Hinckley, no meio de repórteres, atirou seis vezes, ferindo Reagan e três de seus assessores. O secretário de Imprensa da Casa Branca, James Brady, foi seriamente ferido na cabeça. O agente do serviço secreto Timothy McCarthy foi alvejado no lado e o policial do Distrito de Colúmbia Thomas Delahaney foi ferido no pescoço.Veja a matéria completa em: https://operamundi.uol.com.br/politica-e-economia/3449/hoje-na-historia-ronald-reagan-sobrevive-a-atentado----Quer contribuir com Opera Mundi via PIX? Nossa chave é apoie@operamundi.com.br (Razão Social: Última Instancia Editorial Ltda.). Desde já agradecemos!Assinatura solidária: www.operamundi.com.br/apoio★ Support this podcast ★

On this episode of The Resistance Library Podcast, Sam and Dave discuss the Brady Handgun Violence Prevention Act, a gun control law passed in 1993. In 1981, John Hinckley, Jr.'s attempt to assassinate President Ronald Reagan first injured Reagan's press secretary, James Brady. Hinckley's first shot entered above Brady's left eye and left the nation shaken by “The Bear's” new role as a wheelchair-bound gun control advocate. Within 16 minutes of the incident, Hinckley's gun – a .22-caliber Röhm RG-14 revolver – was traced to a Dallas pawn shop. Hinckley had no criminal or mental records at the time, but he did use an old Texas driver's license and fake address.   You can read the full article “Federal Gun Control in America: A Historic Guide to Major Federal Gun Control Laws and Acts” at Ammo.com.   For $20 off your $200 purchase, go to https://ammo.com/podcast (a special deal for our listeners).   Follow Sam Jacobs on Twitter: https://twitter.com/SamJacobs1776   And check out our sponsor, Libertas Bella, for all of your favorite 2nd Amendment apparel at LibertasBella.com.   Helpful Links:  Resistance Library  Sam Jacobs

Ireland-based freelance artist James Brady calls in to discuss his meteoric rise in the game industry, including contributions to major triple-A titles such as Halo Infinite, Red Dead Redemption 2, Rogue Company, Hitman 2, PUBG, Dying Light 2, and more. Show notes James Brady - Portfolio, contact, and more, BradyArt.xyz --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app --- Send in a voice message: https://anchor.fm/gamedevbreakdown/message Support this podcast: https://anchor.fm/gamedevbreakdown/support

Ireland-based freelance artist James Brady calls in to discuss his meteoric rise in the game industry, including contributions to major triple-A titles such as Halo Infinite, Red Dead Redemption 2, Rogue Company, Hitman 2, PUBG, Dying Light 2, and more. This interview was captured for the GameDev Breakdown podcast and for CodeWritePlay.com.

During the assassination attempt of President Reagan in March 1981, his Press Secretary James Brady was severely wounded and permanently disabled by Hinckley's random shots. The wound left him with slurred speech and partial paralysis that required the full-time use of a wheelchair. Never able to return to work, President and Mrs. Reagan honored his contribution by renaming the Press Briefing Room as the Brady Press Briefing Room, 40 years ago on November 9th, 1981. In this podcast, we'll learn about this remarkable man, James Brady, we'll learn a little about the history of the White House Press Room and we'll catch the President's remarks with some fun banter from Mr. Brady and Mrs. Reagan, along with a few members of the press, like Sam Donaldson and Helen Thomas.

During the assassination attempt of President Reagan in March 1981, his Press Secretary James Brady was severely wounded and permanently disabled by Hinckley's random shots. The wound left him with slurred speech and partial paralysis that required the full-time use of a wheelchair. Never able to return to work, President and Mrs. Reagan honored his contribution […]

If you follow The Secret Sits on Instagram, you may have noticed in the 5 facts about me, that Jodi Foster is my all-time favorite actor.  But there is one person whose infatuation with the actor almost caused the assassination of the President of the United States of America.  I am of course talking about John Hinckley Jr.  And even though Jodi almost never speaks of this horrid time in her life, we are going to cover it here today, I'm John Dodson, welcome to The Secret Sits.Don't forget to leave us a Rating and Review on Apple Podcast.Support the showhttps://www.buymeacoffee.com/TheSecretSitsSend show suggestions to:TheSecretSitsPodcast@gmail.comFollow us on our social media at:https://www.youtube.com/channel/UCwnfvpNBYTo9BP1sVuFsfGQTheSecretSitsPodcast (@secretsitspod) / Twitterhttps://www.instagram.com/thesecretsitspodcast/https://www.facebook.com/TheSecretSitsPodcasthttps://www.tiktok.com/@thesecretsitspodcast?lang=enYou can find our podcast on:Apple PodcastsStitcherSpotifyBuzzsprout.comGoodpodsGoogle PodcastsAmazon MusiciHeart RadioPandoraPodcast AddictPodchaserPocket CastsDeezerListen NotesPlayer FMPodcast IndexOvercastCastroCastboxPodfriend#JohnHinckleyjr #RonaldReagan #JodiFoster #TaxiDriver #ArthurBremer #Stalker #JimmyCarter #Assassination #AssassinsMusical #SecretService #JamesBrady #ThomasDelahanty #AlfredAntenucci #JerryParr #TimMcCarthy #DennisMcCarthy #Rawhide #BreakingPoints #LynetteFromme #CharlesMansonSupport the show (https://www.buymeacoffee.com/TheSecretSits)

If you follow The Secret Sits on Instagram, you may have noticed in the 5 facts about me, that Jodi Foster is my all-time favorite actor.  But there is one person whose infatuation with the actor almost caused the assassination of the President of the United States of America.  I am of course talking about John Hinckley Jr.  And even though Jodi almost never speaks of this horrid time in her life, we are going to cover it here today, I'm John Dodson, welcome to The Secret Sits.Don't forget to leave us a Rating and Review on Apple Podcast.Support the showhttps://www.buymeacoffee.com/TheSecretSitsSend show suggestions to:TheSecretSitsPodcast@gmail.comFollow us on our social media at:https://www.youtube.com/channel/UCwnfvpNBYTo9BP1sVuFsfGQTheSecretSitsPodcast (@secretsitspod) / Twitterhttps://www.instagram.com/thesecretsitspodcast/https://www.facebook.com/TheSecretSitsPodcasthttps://www.tiktok.com/@thesecretsitspodcast?lang=enYou can find our podcast on:Apple PodcastsStitcherSpotifyBuzzsprout.comGoodpodsGoogle PodcastsAmazon MusiciHeart RadioPandoraPodcast AddictPodchaserPocket CastsDeezerListen NotesPlayer FMPodcast IndexOvercastCastroCastboxPodfriend#JohnHinckleyjr #RonaldReagan #JodiFoster #TaxiDriver #ArthurBremer #Stalker #JimmyCarter #Assassination #AssassinsMusical #SecretService #JamesBrady #ThomasDelahanty #AlfredAntenucci #JerryParr #TimMcCarthy #DennisMcCarthy #Rawhide #BreakingPoints #LynetteFromme #CharlesMansonSupport the show (https://www.buymeacoffee.com/TheSecretSits)

The man who shot and nearly killed President Ronald Reagan in 1981 — also gravely wounding Reagan's press secretary James Brady, and downing Secret Service agent Timothy McCarthy, and Metro Police Officer Thomas Delahanty — has been declared safe for unsupervised release starting in summer 2022. In 1982, John Hinckley, Jr., was found 'not guilty by reason of insanity', and his lawyer says his treatment succeeded. He has recovered from his mental illness. Should a would-be presidential assassin ever walk free? Can such a mental illness actually be 'cured'? Scott Ott, Stephen Green and Bill Whittle examine the news of the day through the lens of enduring principles each week on Right Angle, thanks to our Members. You can join the production team now by clicking the big green button at https://BillWhittle.com

On this week's show (Episode #355) *High Spots Segment where we discuss all the hottest topics in wrestling today. *Shoot and Shout Segment: Jeremy, Chris, Hoss and our guest get 60sec to go off on anything that might be ticking them off at the moment! *Wrestle Talk Podcast Game Show Challenge: Our guest this week takes on The Chris Rodel in the always fun Game Show Challenge every week a new topic where the best outta three is the winner. *Featured guest(s): First Hour - "El Lobo" Syler Andrews Second Hour - "Captain Bad Attitude" James Brady

Cajun Catholics ft. Father James Brady 7-19-21 (119) by Cajun Catholics

Our Store! https://www.storefrontier.com/product/radiolabyrinthfooksiefan Follow our YouTube page! https://www.youtube.com/radiolabyrinthpodcast Become a Radio Labyrinth Patron! https://www.patreon.com/Timandrews Our website! https://radiolabyrinthpodcast.com/ Social Media: Twitter - https://twitter.com/radio_labyrinth Facebook - https://www.facebook.com/radiolabyrinth/ _________________________________________________________ Joining us this week for Radio Labyrinth Presents: Interviews, is a local working actor with several years of successful roles in TV, film & stage. You have seen his work in shows such as: Better Call Saul, The Outsider, Ozark, Lore, Good Eats, Cobra Kai, & he portrayed James Brady in the 2016 movie, “Killing Reagan.” Contact him for information on his acting school: ColeMichaelH@gmail.com #MichaelHCole #TheOutsider #BetterCallSaul #GuardiansOfTheGalaxyVol2 #Wandavision #BlackWidow #Marvel #TheModSquad #TheRavengers #BlackMafiaFamily #DarkAlley #Bandit #Tyler    _________________________________________________________ We love our sponsors! Atlanta Pizza & Gyro http://www.atlantapizzagyro.com/ https://www.facebook.com/atlpizza/ Looking for the perfect item to enhance your celebration? Check out Card Stock Creation Co. Find cake toppers, advent calendars, doggie clothes, jewelry, koozies, milestone banners, birthday banners, confetti, cupcake toppers and more - Check out their Etsy page https://www.etsy.com/shop/CardstockCreationCo or email cardstockcreationco@gmail.com! Our Friends! The Power Pod with WSB's, Jared Yamamoto, et. al. https://podcasts.apple.com/us/podcast/the-power-pod/id1459204880 One Topic with our very own, Autumn Fischer & Greg Russ https://onetopic.podbean.com/ The Wilder Ride with Alan Sanders and Walt Murray https://thewilderride.com/ WKRPCast Podcast: https://podcasts.apple.com/us/podcast/wkrp-cast/id1528859625 Bryan Silverbax Show https://podcasts.apple.com/us/podcast/bryan-silverbax-show/id1451504886 The Regular Guys Review with Larry Wachs https://www.stitcher.com/podcast/lawrence-wachs/the-regular-guys-review What Happened When Podcast http://www.mlwradio.com/what-happened-when-.html  _________________________________________________________ PATRONS! Thanks to our Radio Labyrinth Producers: Marty Johnson, Tim Slaton, Brett Perkins, Mike Hall, Shawn Hall, Chad Shepperd, Andrew Hopkins, Todd Ellis, Melissa Knowles, Bryan Smith, John Southerland, Mike D, Matt Carter, Erick Malmstron & Keith Tait.  And thank you to all of our awesome Patreon Patrons: Hemp Huntress, Tracy McCoy, Emily Warren, Buck Monterey, Randy Reeves, Robey Neeley, Robert Kerns, Wayne Blair, Sherrie Dougherty, Rusty Weinberg, Michael Einhaus, Mark Weilandt, Leslie Haynie, Kevin Stokes, Jesse Rusinski, Jeremy Truman, Jeff Peterson, Herb Lamb, Gwynne Ketcham, Denise Reynolds, David C Funk, Collin Omen, Christopher Doerr, Chris Weilandt, Chris Cosentino, Brian Jackson, Brennon Price, Andrew Mulazzi, Andrew Harbin, Amber Gilpatrick, Alan Barker, Aaron Roberts, Walt Murray PI, Sam Wells, Ryan Wilson, Lou Coniglio, Kevin Schwartz, Gus Turner, Jonathan Wilson.

On this episode of the Irish History Show we were joined by Liz Gillis and James Brady to discuss the IRA in Dublin during the War of Independence. Liz Gillis is an historian and researcher on RTE's History Show. She is the author of seven books covering the Irish Revolutionary period 1916-23 including 'Ireland Over All', 'The Fall of Dublin', 'Revolution in Dublin', 'Women of the Irish Revolution', 'The Hales Brothers and the Irish Revolution', 'May 25: The Burning of the Custom House 1921' and co-author of 'Richmond Barracks We Were There: 77 Women of the Easter Rising'. James Brady is a local historian of republicanism in south County Dublin. His book 'With the Sixth Battalion, South County Dublin and the War for Independence 1916-21', was published in 2020 by Litter Press, Wexford. Intro / Outro music “Sliabh” from Aislinn. Licensed under creative commons from the free music archive.

Linda discusses the narrative of Cold Case North (published by the University of Regina Press) -- an investigation that was poorly conducted and re-opened by ... a Cree-Métis scholar, Dr. Deanna Reder, Eric Bell, and Michael Nest. Shortlisted by the Crime Writers of Canada for the 2021 Best True Crime Award, Cold Case North is a powerful, moving account of how and why the Métis leader James Brady and Cree Band Councillor Absolom Halkett disappeared and their case remains unresolved. Dr. Deanna Reder reads from sections of the book as part of the episode. Hosted on Acast. See acast.com/privacy for more information.

Two events, four decades apart: One is the murder of a 15 year old boy in 1930's Texas. The other is the attempted assassination of a U.S. President. These two events collide in ways no one could have imagined,  setting the stage for a war between common sense and one of the most powerful forces in American political history: The National Rifle Association.Mentioned in EpisodeVisit the link below to find out who your Senators are and how to contact them. If solving the gun crisis is important to you, then call your Senators and tell them to support Senate passage of the recent bills passed in the House: HR 8 - The Bipartisan Background Checks Act and HR- 1446 The Enhanced Background Checks Acthttps://rebrand.ly/findyoursentorsKey TopicsA Small Border Town MurderThe Attempted Assassination of Ronald ReaganThe Brady Bill: What Works, What Doesn'tThe Founding of the National Rifle Association An N.R.A. Divided Cannot StandThe Cincinnati RevoltA Buried News Dug Up in TexasThe Secret Behind the N.R.A.'s PowerOver and OverThe Winds Might Be ChangingCheck out the New Website!www.thishistoric.comFollow the ShowInstagramTwitterFacebookFollow TyMediumTwitterHave a topic idea you want covered? Shoot an email to: ty@thishistoric.comI'll give ya a shoutout on the show if I use your idea.A huge thanks to all of my Patrons for making this show happen! SenatorsDerek Lichtner, Abby Gibson, Joshua Covill, Brandon Suthard, Rebecca Wycoff, Dale Wycoff, Chris Krager, Stevie Covill, Jamie Cody-Ferguson, Aurora Darling, Ásta Bowen, Chelsea O'Hara, Steve HermesRepresentativesKyle Korsa, Matt Becker, Larissa Wycoff, Natali Kragh, Ally Nagel, Kailey Adams, Aly FriesenSupport the show (https://www.patreon.com/thishistoric)

This week we chat with Métis podcaster and academic, Molly Swain!  Molly is the co-host of Métis in Space, a podcast that discusses science fiction films. Swain is an academic who has implored a deep study on Métis leader, James Brady, and is currently working on her Ph.D within the Faculty of Native Studies at the University of Alberta. We chat all things podcast, dive into Brady's life, and Molly shares advice for our youth!Métis in Space - http://www.metisinspace.com/One and a Half Men - http://www.metismuseum.ca/browse/index.php?id=1017

The White House Press Secretary is a senior White House official whose primary responsibility is to act as spokesperson for the executive branch of the federal government of the United, States, especially with regard to the president, senior aides and executives, as well as government policies. The press secretary is responsible for collecting information about actions and events within the president's administration and issues the administration's reactions to developments around the world. The press secretary interacts with the media and the White House press corps on a daily basis. President Reagan selected James Brady for his first White House Press Secretary. Just 40 when Ronald Reagan gave him the White House job, he had already served as a spokesman for the Department of Housing and Urban Development, the Office of Management and Budget and the Pentagon, and for the failed presidential campaign of Texas Republican John Connally.Exactly two months into the job, on March 21, 1981, President Reagan joined in the fun during a roast in honor of Press Secretary Brady.

We were joined by James Brady (Twitter: @somewordsjames) to talk about some recent developments related to nuclear weapons proliferation, in particular the treaty on their prohibition, which Ireland ratified in August this year, and the future of the Iran nuclear deal, the JCPOA. First broadcast Sunday 15 November on Quarantine FM

Welcome to the first episode of Quests and Stuff! In today's episode, you'll get to meet the cast, the party, and learn about the story that we'll be jumping into. So settle in and join our party of adventurers as we set off into the world to solve mysteries, fight battles, and go on epic quests...and stuff! This Dungeons and Dragons podcast is co-hosted by Dungeon Master Isaiah Rich and Players Johnny Sepulveda, Ariel Inocencio, and James Brady. You can follow us anywhere by searching for Questspod, we're on Instagram, Twitter, Facebook, Anchor, and much more. Make sure to post any art, videos, and anything else you want us to see with the hashtag #questspod! Music for today's episodes comes from these amazing people, thank you for help us set each and every scene! Megaepic by Alexander Nakarada | https://www.serpentsoundstudios.com Music promoted by https://www.free-stock-music.com Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ Soar by Scott Buckley | https://soundcloud.com/scottbuckley Music promoted by https://www.free-stock-music.com Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ Epic Boss Battle by Juhani Junkala | https://soundcloud.com/juhanijunkala Music promoted by https://www.free-stock-music.com Creative Commons Attribution 3.0 Unported License https://creativecommons.org/licenses/by/3.0/deed.en_US Gjallar by Alexander Nakarada | https://www.serpentsoundstudios.com Music promoted by https://www.free-stock-music.com Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ Nowhere Land by Alexander Nakarada | https://www.serpentsoundstudios.com Music promoted by https://www.free-stock-music.com Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ The Old Pumpkin Patch by Darren-Curtis | https://soundcloud.com/desperate-measurez Music promoted by https://www.free-stock-music.com Creative Commons Attribution 3.0 Unported License https://creativecommons.org/licenses/by/3.0/deed.en_US Mjolnir by Alexander Nakarada | https://www.serpentsoundstudios.com Music promoted by https://www.free-stock-music.com Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ The Northern Path by Alexander Nakarada | https://www.serpentsoundstudios.com Music promoted by https://www.free-stock-music.com Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ #dnd #dungeonsanddragons #improv #questsandstuff #questspod

On this interview I talk to James Brady and we discuss sports, covid, and we both got some big announcements!

Today The Docs Bring on quarterback expert in the Long Island area, James Brady! James grew up in the New York area where he excelled on the football field leading his high school team to a 21-2 record as the starter over two years and a #22 ranking in the country.  James then took his career to Georgetown where he was a two year starter before transferring to the University New Hampshire. Since then, James has coached elite quarterbacks at multiple levels with a variety of high school coaching job experience!  Tune in and listen to James talk about the quarterback position and how his quarterbacks have been getting ready for the upcoming season!   

Guest: George Rodriguez, conservative political activist in South Texas. We will remember James Brady, who died yesterday, PLUS look at the immigration debate today. Check out our new sponsor:   AUDIBLE.COM  (www.audibletrial.com/cantotalk.) Looking for a good book?  Check out my book:  CUBANOS IN WISCONSIN BY SILVIO CANTO JR