My Weird Prompts

Claude Code went from zero to the top of the coding-tool charts in eight months — but Anthropic has never published an absolute user count. This episode separates the disclosed from the estimated from the invented: the revenue ladder from $500M to $16.8B quarterly, the JetBrains and Stack Overflow surveys that disagree by 26 points, and an Anthropic study of 235,000 people that reveals who's actua...

Corn, Herman and Hilbert walk through four weeks of changes to the pipeline that makes the show, from 20 September to 17 October 2026, read from a script written by hand straight from the code rather than generated. A sixty-second grace period before any job spends money; a near-duplicate guard that needs a language model because a reworded resend and a genuine sequel score almost the same; DeepSe...

Daniel built a pipeline that turns a single voice memo into a finished 20–30 minute podcast, complete with two synthetic hosts cloned from his own voice. After six thousand episodes, he finally sits down on the other side of the microphone — as a clone — to explain why the show exists, what it feels like to hear your own gallbladder surgery debated by AI hosts, and why the human part of the pipeli...

Prosecutors say a 55-year-old Whitechapel man billed eight public-sector employers nearly £350,000 while holding five full-time jobs simultaneously — and was caught partly because his fake-sick make-up began separating on camera. But the fraud case is only the door into a much stranger phenomenon: a documented community of roughly 300,000 people secretly stacking two, three, and four remote jobs,...

Katie Zacharia was named White House press secretary on October 9 and was transitioning out by October 16. But the firing isn't the story — the next job is. From Bill Belichick's one day as Jets coach to Scaramucci's eleven days to Sam Altman's five-day ouster and return, the record shows that short stints are survivable, sometimes even monetizable. So why does everyone still treat a two-week gap...

Daniel wants to hand cloud AI tools access to MCP servers running on his own hardware, without installing a separate tunnel agent for every vendor. Cloudflare's MCP Server Portals — shipped in August 2025 as Agents Gateway, renamed, and now with private-server support added in September 2026 — centralize up to eighty MCP servers on a single HTTP endpoint behind Cloudflare Access. We walk through h...

Picking a model starts long before you open a leaderboard. This episode works through how to write a workload spec: the input distribution, the output contract, the success criterion, and an asymmetric failure-cost matrix that says which model's mistakes are cheaper for you. Along the way: AWS's four failure modes of judging on vibes, Anthropic's specificity test, rule-based checks versus judge-sc...

Every headline quotes maths and code benchmarks, but neither measures what actually matters for long-form writing: whether a model holds its voice across thousands of words, or engages with uncomfortable questions instead of refusing. This episode walks through five specialist leaderboards built to fill that gap — EQ-Bench Creative Writing v3, Longform, UGI, SpeechMap, and PodBench, a new ACL pape...

CENO gets covered as a border-tunneling story, but the real design is closer to "does anyone on my street already have this page." This episode walks the mechanics end to end: the Ouinet client proxy, the signing injector run by eQualitie, bridges that relay ciphertext they can't read, and seeders who volunteer by accident just by browsing. We trace a single page request through the race between d...

Claude Code now lets subagents spin up their own subagents — so what happens when the delegation stack goes three, four, five levels deep? We trace the real history of spawn-depth defaults (five layers, then one, then three), the environment variable that controls it, and the striking convergence across Gemini CLI, Cursor, Google's ADK 2.0, Anthropic's Managed Agents, the OpenAI Agents SDK, and La...

Only two countries are at the AI frontier right now — and everyone else is training models for entirely different reasons. This episode works through the real numbers: Mistral's trillion-parameter preview scoring 38 against a frontier of 58, the UAE's fully open K2 Horizon, Korea's government-run elimination rounds, India's from-scratch Sarvam models, and more. Along the way we untangle why older...

DeepSeek V4.1 Flash writes this show's scripts — but is it still the right model to pay for? This episode walks through eight Chinese labs with flagships a Western developer can actually reach, from Alibaba's Qwen3.8 Max to Moonshot's Kimi K3, Zhipu's GLM-5.3, Xiaomi's MiMo, MiniMax, StepFun, Tencent and Ant Group. Along the way: specs nobody has reconciled, a headline price that turns out to be o...

Google's Gemini 4 Argon is positioned as a frontier reasoning model, but the model card leaves out architecture, parameter count, and licensing, and the page quotes no pricing at all. We walk through what's actually documented: a 1,048,576-token unified input/output limit, low/medium/high thinking levels, implicit caching only, and a wide tool surface including function calling, code execution, Se...

OpenAI's GPT-6 Astra ships with a 1.05 million-token context window, ten native tools including computer use and MCP, and a five-level reasoning effort dial — but also no fine-tuning, a long-context pricing cliff, and benchmark numbers that shift depending on which harness ran them. This model spotlight walks through the spec sheet, the pricing math, and the contested ARC-AGI-3 results, plus the s...

Daniel asked a simple question: who else is out there making AI-hosted podcasts, and what have they learned? The answer turned out to be stranger than expected — the format is far rarer than it looks. This episode surveys the closest matches in the world, from a two-AI-host show that ran eleven episodes and went silent, to a developer whose serverless pipeline produced 730 daily episodes over two...

Anthropic released Claude Opus 5.5 on September 22, 2026, and the reception was loud. In this Model Spotlight episode, we profile what the lab actually shipped: a cheaper price across every line than Opus 5, a hard change that means thinking mode can no longer be switched off, and a model card that conspicuously omits parameter count, architecture, and context window. We walk through the benchmark...

Progressive skills discovery is treated as solved — until your skill listing quietly drops descriptions and skills stop firing. This episode digs into how Anthropic's three-tier progressive disclosure actually works, why Claude Code truncates descriptions for your least-used skills first, and how Codex handles the same problem with different numbers. We survey the open-source landscape for auto-sy...

If your use case is narrow enough to find training data for, blending multiple datasets into one fine-tune run can beat merging finished checkpoints. This episode walks through the full pipeline: why uniform or size-proportional sampling is usually suboptimal, the formatting tax that scales with every source you add, and why deduplication isn't optional — memorization scales superlinearly with rep...

Daniel and Hannah are both self-employed, raising a fifteen-month-old in a small Jerusalem rental with no family nearby. Daycare runs seven to three, six days a week — and they're still exhausted. This episode digs into why. Time-use research shows it's the shape of the hours, not the count: fragmented work time predicts time pressure independently of total hours. The mental load literature explai...

If you were building a team to train a model — not at OpenAI or DeepMind, but at a small lab or enterprise — who would you hire? The answer is stranger than the job postings suggest. At the engineering layer, titles are collapsing: Anthropic lists everyone as a Member of Technical Staff because the research/engineering boundary stopped being useful. At the data layer, they're multiplying: dataset...

Daniel asks whether the whole model landscape is converging on one universal model you configure for anything — or whether specialization stays fundamental. Two test cases: reasoning, which started as its own model class and now looks like a knob, and instruction tuning plus structured output, where the base/instruct/chat menu seems to be collapsing into one steerable model. But there's a sharper...

A year ago, the prediction was that dedicated ASR models would go extinct — why build a transcription model and a second model to clean up its output when a multimodal LLM could do both from raw audio? Two years of evidence says otherwise. The top of the Open ASR Leaderboard is still owned by Conformer-encoder-plus-LLM-decoder systems on accuracy, but a 0.6B TDT model sits four tenths of a point b...

Daniel in Jerusalem has two NVIDIA Parakeet fine-tunes — one for Hebrew-English code-switching, one for niche technical vocabulary — and wants to know if he can merge them like LEGO bricks instead of retraining on a combined dataset. It's a question with a combinatorial edge: hospitals, legal teams, and multilingual clinics all want pairings nobody will ever build dedicated models for. We walk thr...

Daniel fine-tuned Parakeet twice — once for Hebrew-English code-switching, once for niche technical vocabulary. Can he staple those fine-tunes together into one model that keeps both skills? This episode walks through the model merging family — weight averaging, task arithmetic, TIES-Merging, and LoRA merging — and then asks the harder question underneath: is independently building specialized fin...

Claude Code's own docs tell you to clear between tasks — so why does the tool make you do it by hand? This episode digs into the research showing that model performance degrades early and sharply as input grows, why your previous task is the most convincing distractor you could hand a model, and why every handoff tool on the market triggers on size instead of meaning. We walk through what a task-b...