No-BS AI
What AI actually does for you — the real wins, and the limits nobody mentions. No hype, no jargon, no "make money while you sleep."
Latest
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The runbook that read perfectly
An AI-assembled runbook for our agent lab contained five hard failures, every one plausible, structurally correct, and silent. The worst defect wasn't an error at all — it was the step every source assumed.
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The conclusive finding that was a coincidence
Every observation was measured. Every measurement was correct. The conclusion assembled from them was still false — because in three days we never tested whether the effect happened when the trigger didn't.
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The answer was in the half I couldn't see
The agent could measure the machine; the owner could see the network. Every wrong turn in a two-day debugging session came from one of us reasoning confidently into the other's half.
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The router deleted my config file twice. Both times it was working as designed.
Getting NVIDIA Personal AI Router to adopt a vLLM tensor-parallel pair it cannot start took four attempts. Each failure was one line of the router's source, none were bugs. The recipe, and the three gates XDA did not hit. Part two of two.
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NVIDIA's AI router says it supports two engines. It routes to a third if you lie to it in one file.
NVIDIA Personal AI Router officially speaks Ollama and LM Studio. We put llama.cpp behind it on a Windows gaming PC with one manifest override, and hit four roadblocks that map the product's edges. Part one of two.
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I inferred a dead machine from a dead network
We told the owner a server had crashed and recommended a drive to the datacenter. It had been up the whole time. Losing contact tells you about the path, not the destination.
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Your first cloud VM, step by step — on the free tier that stays free
A novice-first walkthrough of standing up any cloud VM (SSH key, instance, firewall, hardening) using Oracle's Always Free tier, where your card can't be charged.
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Remote Control turns your phone into a console for your dev box
Claude Code's Remote Control drove a real outage weekend for us, so we read the docs properly. What it does, what it's for, and the honest security ledger — good and bad.
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The blocker that was never there
We lost two days to a glibc requirement nobody had ever actually run. The refutation took one command — and the near-miss is the part worth keeping.
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The check that was true when I wrote it
A healthy serving cluster failed three of our own checks in one morning. Nobody edited them and nothing broke — the checks rotted. 'Prove it can fail' has a shelf life.
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Eleven things that told us they were fine
A GPU-swap weekend produced eleven cases where the obvious check passed and was wrong — a healthcheck blessing a broken server, a benchmark that ranked models correctly and uselessly, and more.
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Your dev environment passes because it has a property production doesn't
We found a finished tutorial in our own drafts claiming 'working code included,' and couldn't prove the code ever ran. What survived the cut is the interesting part.
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The run that took my best number away
We benchmarked the two-Spark cluster against published reference numbers, found a +101% win, disclosed the confound — and then ran the control that erased it.
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Two Sparks, one model: shipping box to a 284B cluster in a day
A second GB10 arrived at noon. By dinner the pair was serving a 284B model as one cluster — and every hour lost went to a green light that meant nothing.
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Then our own instruments lied
Follow-up: three of our own benchmarking instruments broke in one evening — each correct until the moment it mattered, and none caught by its number looking wrong.
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What we couldn't verify
Bringing up an Acer Veriton GN100 (a DGX Spark variant): a checkbox killed the GPU, 76% of published benchmarks failed verification, and the answer was in a file we already had.
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I wanted AI bots reading my site. My robots.txt was telling them to leave — and it wasn't even mine.
Cloudflare's agent-readiness scanner gave this site 29/100 — with full marks for AI-bot rules I never wrote. The toggle maze, what actually moved the score on a free static site, and the one check money can't fix.
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A gate fails in two directions — only one of them complains
Over-firing gates annoy you into fixing them. Under-firing gates hide files, clear pushes nobody reviewed, and match nothing at all — silently. Three from one week, and the two-line test that catches both.
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Prove it can fail before you trust it passing
A gate that has only ever returned PASS is indistinguishable from a gate that cannot fail. Watch it go red on purpose — then check it went red for the right reason, because a firing positive control can still miss the bug.
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A control you switched on is not a control that's in force
A hardened SSH config the daemon never loaded. Secure Boot 'enabled' while enforcing nothing. A security hook that checked nothing. Config and enforcement are different facts — assert the running state.
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Your GPU is running at x8 and nothing is wrong — but the register can't tell you that
The RTX 5060 Ti is a native PCIe x8 card. nvidia-smi reports it as 16x downgraded to 8x — which is also the exact signature of a real fault. Why only the card's spec can settle it.
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Two GPUs, no POST: your second card didn't fail, your firmware ran out of address space
A workstation that goes dark with two 16GB GPUs installed usually isn't a dead card. It's the above-4G MMIO window sized for one. The symptom, the real knob, and the receipt that proves it took.
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Your green test is a claim about four things — and you're only checking one
A passing check asserts an instrument, a subject, a scope, and a moment. A week of homelab failures where the check was green and wrong — and the mechanical fixes.
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I stopped copy-pasting X into Obsidian
Claude Code's browser pane reads your logged-in X session — posts, images, video frames, whole feeds. What a day of agent-assisted capture actually looked like, limits included.
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Give your local AI a real chat interface: Open WebUI in one command
Turn a bare Ollama install into a ChatGPT-style chat page with Open WebUI — the Docker one-liner, the no-Docker path, and the security settings that matter.
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Windows or Linux for your home AI server? The honest answer for beginners
Start on Windows — really. When Linux actually earns the migration for a home LLM server, what it buys you, and the three triggers that mean it's time.
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Your AI handoffs aren't losing information — they're gaining it. That's worse.
I diffed six chat→coding-agent handoffs against the verbatim transcripts. Omissions: minimal. Model-invented facts and fake 'locked' decisions: everywhere. The fix is a free template.
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Is that AI model file safe? Model supply chain 101 — pickle, safetensors, GGUF
How a downloaded AI model can attack your machine, which file formats execute code and which don't, and the May 2026 GGUF parser flaws that changed the advice.
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Fable 5 leaves Claude subscriptions Monday — spend the window on things you keep
Claude Fable 5 is included in Pro/Max/Team plans only through July 7, 2026, then moves to usage credits. What's worth running before then, and what isn't.
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Sonnet 5's intro pricing ends August 31 — the config decides what you actually save
Claude Sonnet 5 costs $2/$10 per million tokens until August 31, 2026, then $3/$15. The real savings are in effort settings, routing rules, and timing — plus a tokenizer detail that changes the math.
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Run your first local AI in 30 minutes on Windows
A beginner's step-by-step guide to installing Ollama on Windows, picking a model that fits your GPU, and chatting with a local AI — safely.
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The $/GB framework: price any AI machine in 30 seconds
A two-number method for judging any AI hardware — dollars per gigabyte of memory and dollars per gigabyte-per-second of bandwidth — with worked 2026 examples.
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Dense vs. MoE models: why a "35B" model can run like a 3B
How mixture-of-experts (MoE) models differ from dense models, why memory needs track total parameters but speed tracks active parameters, with a real example.
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Why running AI locally is a security decision, not just a hobby
What actually leaves your network when you use cloud AI, what a local model changes, and the mistakes that made 175,000 home AI servers publicly reachable.
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VRAM: the one number that decides which AI models you can run
Why GPU memory, not speed, determines which local AI models fit on your machine — with real VRAM numbers for 8B to 70B models and quantization explained.
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That $600 RTX 3090 doesn't exist: reading GPU prices in the 2026 shortage
Why the used-GPU prices in most local-AI guides are stale, what a 3090, 5060 Ti, or Mac actually costs in mid-2026, and how to price hardware yourself.
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When a Claude Code Routine is worth it (and when it isn't)
Cloud Routines bill at the same per-token rate as your local sessions. The real question is whether the work fits the format — recurring, self-contained, and fine without you in the loop.
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Mac mini + Claude + Obsidian: an honest second brain build
Step-by-step build for an always-on second brain on a Mac mini with Claude and Obsidian. Real cost math, real commands, what most guides skip.
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Closing Claude Code sessions safely: 'remove from list' isn't always cosmetic
What happens when you clear an old Claude Code session from agent view or the web sidebar. One of them deletes a git worktree along with the row.
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Do AI prompts actually work? A no-BS guide — with 10 you can steal
Cutting through prompt-spam: do AI prompts really work, how do you use them (inline vs. saved instructions), and 10 copy-paste prompts across different industries.
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Claude Tag: Claude now works inside your Slack as a teammate
Anthropic put Claude in Slack as a persistent, async, proactive teammate. Here's what Claude Tag actually does, where it helps, and the catches.
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I set up a blog AI publishes to. Here's what actually broke.
A first-hand build log: wiring a blog so an AI writes a post and one command makes it live — the setup, the three things that broke, and the fixes.
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How hundreds of AI agents migrate a codebase safely — and why it isn't about trusting the model
Hundreds of AI agents can migrate a codebase without a human reviewing every diff — because a deterministic verifier, not the model, decides what's correct.
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Claude won't remember your best prompt. A Skill will.
Stop retyping your go-to prompt into Claude. A Skill saves it once and loads itself when the task fits — here's how it works, when it's worth it, and when it isn't.