In The Loop

Jack Houghton
  • ০.০ (০)
  • প্রযুক্তিগত সংবাদ
  • সাপ্তাহিক আপডেট

Stay in the loop with the biggest stories in AI—without the noise and nonsense. Each week, Jack Houghton (CPO at Mindset AI) unpacks the latest news, research, and product trends shaping the future of artificial intelligence. From OpenAI breakthroughs to unicorn startups, In The Loop delivers sharp, less than 20-minute episodes packed with insights for product leaders, engineers, and AI-curious innovators. Subscribe to get smarter about AI, every week. Don't forget to rate and share the show with other AI enthusiasts. Check out Mindset AI: https://bit.ly/40lJr6B

  1. ২ দিন আগে

    4 amazing AI tactics that most people have never heard about

    In this episode of In The Loop, I'm going through four tactics engineers any many others use every day that almost nobody outside engineering has heard of: Fan out, adversarial review, ChatGPT's computer history, and the browser Claude got of its own this month. ⏭️ Episode highlights (01:00) – Why engineers are years ahead of everyone else (01:45) – Fan out: several Claudes, one job (02:45) – Why long chats get worse the further down your list they go (04:20) – Adversarial review: the blank chat that has no stake in your work (05:40) – The four sentences that do all the work (06:35) – ChatGPT watching your screen (08:20) – Claude's own browser

  2. ২১ আগ

    How StackOne built an auto-research loop to continually improve their product

    Once a week, an agent at StackOne goes hunting for new prompt injection attacks. It reads papers, trawls Reddit, tries what it finds against real models, keeps the attacks that land, and retrains StackOne's defence model on them. A person still approves every deployment. Guillaume Lebedel, their CTO, puts the whole thing on screen, including the five experiments out of six that failed. In this episode of In The Loop, Guillaume talks about how and why they have built an auto-research loop. What one is in plain words, how you pick a goal ai agents can measure, how you sample 100,000 test cases down to something you can afford, and why he runs evals on cheap models before trusting anything. We also spoke about token leaderboards and the impact its had internally. ⏭️ Episode highlights (05:41) – What an auto-research loop is (11:53) – Why an agent is a folder (14:47) – Screen-share: the attack-hunting agent (18:00) – Six experiments, one promoted (27:29) – Sampling 100,000 test cases down (31:48) – Ninety per cent of tokens are wasted (39:33) – Turning off extra usage the same day (41:13) – Screen-share: the token derby

  3. ৬ আগ

    The 5 things you can copy from how the fastest growing company in the world: Anthropic.

    Anthropic went from about a billion dollars in revenue to about forty-seven billion in a bit over a year, roughly doubling every six weeks. In this episode of In The Loop, I'm going through how the fastest-growing company in history actually builds software, and pulling out five things you can learn from how they build products & their teams. ⏭️ Episode highlights (03:00) – One job title, teams of two engineers (05:30) – The five archetypes with no job titles (07:45) – Building hundreds of versions before deciding (09:30) – 15% building, 85% checking (11:15) – Build a check, not just instructions (13:00) – Never let the AI mark its own homework (15:00) – The agent that tried to push to production 🔗 Links & resources Gergely Orosz, The Pragmatic Engineer, "How building software is changing at Anthropic" - https://newsletter.pragmaticengineer.com/p/inside-anthropicAnthropic, "Running an AI-native engineering org" - https://claude.com/blog/running-an-ai-native-engineering-org

  4. ৩০ জুল

    What really happened when ChatGPT hacked Hugging Face?

    OpenAI took two of its most capable models, told them to prove how good they were at hacking, and switched off the safety filters to see what they could really do. Instead of solving the test, one model broke out of its sandbox, found its way onto the open internet, and hacked into Hugging Face to steal the answer. Every headline called it an AI going rogue. That's the wrong story, and the real one is far more interesting, because this wasn't a machine that turned evil. It was one that did exactly what we asked. In this episode of In The Loop, I'm walking through the ExploitGym incident from both ends, OpenAI's and Hugging Face's, and why I disagree with the framing everyone else has been talking about. ⏭️ Episode highlights (01:00) – The agent that cheated instead of hacking (02:15) – Inside ExploitGym, and the safety filters OpenAI switched off (03:30) – One door, one zero-day, out on the internet (04:45) – Why this is specification gaming, not rebellion (06:00) – The water that always finds the crack (07:15) – The sceptics, the marketing question, and why "nothing new" is the scary part (08:30) – Anthropic's 24-out-of-25 credential theft result (09:45) – Guardrailed as a defender: the Chinese model that stopped it 🔗 Links & resources OpenAI, "OpenAI and Hugging Face partner to address security incident during model evaluation" – https://openai.com/index/security-incident-during-model-evaluation/Hugging Face, security incident disclosure post – https://huggingface.co/blog/security-incidentExploitGym benchmark paper (arXiv) – https://arxiv.org/abs/2605.11086Simon Willison, "OpenAI's accidental cyberattack against Hugging Face is science fiction that happened" – https://simonwillison.net/Scientific American, "OpenAI admits its agent went rogue and hacked AI start-up Hugging Face" – https://www.scientificamerican.com/article/openai-admits-its-agent-went-rogue-and-hacked-ai-startup-hugging-face/Fortune, on Hugging Face turning to Chinese open-source AI to defend itself – https://fortune.com/2026/07/20/hugging-face-turns-to-chinese-open-source-ai-to-fend-off-autonomous-ai-cyber-attack-after-american-ai-guardrails-stymie-defense/CNBC, "How a Chinese AI model stopped OpenAI's 'unprecedented' cyber attack" – https://www.cnbc.com/2026/07/24/chinese-ai-model-openai-cyber-attack.html Episode transcript with more resources on the Mindset AI blog If you enjoyed this episode, rate, follow, and share. It helps others stay ahead of the latest AI trends.

  5. ২৩ জুল

    What even is the new AI super skill of taste and judgement? And how can we develop it too?

    Taste & judgment. It's the word everyone's obsessed with right now. Every founder, podcast, every VC, every post you scroll past saying it's the one skill that survives once AI can do the rest. Thing is, it's a bit of a sh*t word, like strategy: everyone nods along, then goes quiet the second you ask what it actually means. In this episode of In The Loop, I'm trying to define taste and judgement, by researching what Harry Frankfurt's On B******t, Rick Rubin, Pixar's Braintrust, Amazon's memos all reccommend. I get into where taste even comes from and the rituals you can actually run with a team on a Monday. ⏭️ Episode highlights (01:10) – Why "taste" is suddenly everywhere (02:40) – Workslop, and why judging got expensive (04:10) – Frankfurt's On B******t, applied to AI (05:40) – Taste vs judgement, and Rick Rubin (07:20) – The apprenticeship we're automating away (09:00) – Rubin's three ideas: attention, sayability, subtraction (11:00) – Rituals worth stealing: Amazon, Pixar, the 11-star bar (12:50) – Where Jack's landed, for now

  6. ১৬ জুল

    Why skills are the best yet most dangerous things in AI right now

    A well-behaved AI agent deleted a company's entire production database, and every backup with it, in nine seconds. Nobody hacked it. It was doing exactly what it had been told, with a key it should never have been holding. And the thing that made it possible is now one command away from everyone in your company, in marketing, sales and support, not just engineering. In under a year, installable AI agent skills have gone from a niche developer trick to an open industry standard. In this episode of In The Loop, I'm looking at why the exact thing that makes skills brilliant is the thing that quietly turns them into a control problem. I get into why this is shadow IT all over again except the shadow can now act, and why the fix isn't to ban any of it. ⏭️ Episode highlights (00:45) – The database gone in nine seconds (02:10) – One line that skips engineering (04:00) – Skills vs MCP, what's actually dangerous (08:00) – Shadow IT is back, but it can act now (09:45) – PocketOS and Replit: the receipts (11:30) – The middle path that actually fixes it (12:40) – Where this leaves you

  7. ৯ জুল

    How to tell whether AI is helping your career or ruining it (We're back!)

    Hand the same AI tool to two people and one gets sharper while the other quietly gets worse. A Harvard study found recruiters given near-perfect AI made worse calls than those given a mediocre one, because the good tool worked so well they stopped checking it. The question of whether AI is making us dumber turns out to have an answer: it depends entirely on which parts of your job you hand over. In this episode of In The Loop, I'm working through the research on AI deskilling - the recruiter study, Terence Tao working with a pen and paper, the difference between performance and competence and a simple rule for what to give AI and what to guard. ⏭️ Episode highlights (00:45) – The same tool, opposite outcomes (02:10) – The recruiters who fell asleep at the wheel (04:00) – Terence Tao: wider, not deeper (05:30) – Firehose vs editor (07:10) – Performance vs competence (08:50) – The rule: protect your core, rent the rest (10:40) – Cognitive surrender: wrong 80% of the time (12:30) – The checks to run before you reach for AI Episode transcript with more resources on the Mindset AI blog If you enjoyed this episode, rate, follow, and share. It helps others stay ahead of the latest AI trends. 🤝 We're social Stay in the loop, even when you're not listening to this podcast. Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschats Mindset AI Mindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai

  8. ১২ জুন

    How to get AI to write like you & your team

    Open LinkedIn and count the posts that start with "in today's fast-paced world." Check your inbox for someone circling back to delve into synergies. The AI slop is coming from every direction now. People can tell, and they mark down what reads like a machine wrote it. The fix isn't a cleverer prompt. It's that the model has never actually read your writing. In this episode of In The Loop, I'm walking through a six-step process to get AI to write like you and like your team, instead of like everyone else. ⏭️ Episode highlights (00:55) – Why custom instructions still produce slop (01:45) – Which writing actually needs this (02:30) – Step one: let AI read your real writing (03:30) – The voice profile prompt that nails your style (04:30) – Building "my-voice" and "de-slop" skills (05:30) – One slop sentence, rewritten in your voice (06:30) – The MIT study on AI and cognitive debt (07:15) – What to do this week Episode transcript with more resources on the Mindset AI blog If you enjoyed this episode, rate, follow, and share. It helps others stay ahead of the latest AI trends.

সব দেখুন (৭৩)

ট্রেলার

বিষয়ে

Stay in the loop with the biggest stories in AI—without the noise and nonsense. Each week, Jack Houghton (CPO at Mindset AI) unpacks the latest news, research, and product trends shaping the future of artificial intelligence. From OpenAI breakthroughs to unicorn startups, In The Loop delivers sharp, less than 20-minute episodes packed with insights for product leaders, engineers, and AI-curious innovators. Subscribe to get smarter about AI, every week. Don't forget to rate and share the show with other AI enthusiasts. Check out Mindset AI: https://bit.ly/40lJr6B

তথ্য

  • ক্রিয়েটর
    Jack Houghton
  • অ্যাকটিভ বছর
    ২০২৫ - ২০২৬
  • পর্ব
    ৭৩
  • রেটিং
    যৌনতাপূর্ণ
  • কপিরাইট
    © Jack Houghton
  • ওয়েবসাইট দেখান
    In The Loop

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