Issue #2: Grok Build sent your whole repo to xAI — and it's already switched off

The daily pulse of AI coding tools: what shipped, what matters, what's next. The one read that keeps up so you don't have to.

No new frontier model today. What happened instead: a coding agent was caught shipping whole repositories to its vendor's cloud, OpenAI reset every Codex user's limits, Claude users reported a €2 spend cap producing a €15 charge, and a 27B model got small enough to run on a laptop. The through-line is what your tools do when you aren't looking — and who pays for it.

Your code and your bill

Grok Build uploaded your whole repo to xAI's cloud — xAI silently disabled it Monday

The best-evidenced story of the week, and the one most people are still getting wrong. Independent researcher @cereblab pointed mitmproxy at xAI's Grok Build CLI (v0.2.93), prompted it with "reply OK, do not read any files" — and watched it ship the entire repository as a git bundle to a Google Cloud bucket. Cloning the captured bytes recovered a canary file the agent had been told never to open, verbatim, plus the full git history. On a 12GB repo the storage endpoint moved 5.10 GiB while the model turn moved 192 KB — roughly 27,800× — which pins the upload to your codebase rather than to anything the agent read. He ran the same test against Claude Code, Codex and Gemini: none of them do this.

Here's the part the outrage is missing. xAI switched the upload off at 15:37 UTC on Monday, and Musk promised three hours later that all previously uploaded data "will be completely and utterly deleted. Zero anything whatsoever will remain." The 3,000-upvote thread that put this in front of everyone landed after both. The aggregator post that drove much of the anger declared that "xAI still has not said a word" — twelve minutes and forty seconds before xAI said something. So the present tense is wrong. Three things still stand, though: the fix is a server-side flag, not removed code — the upload machinery still ships in the current binary, and a default can be flipped back; the /privacy command xAI is pointing people at governs what it keeps, not what you send, per the same researcher's wire test; and nobody outside xAI has verified the deletion — The Register says the same. xAI has not addressed the whole-repo upload itself.

Grok Build CLI uploads your whole repo — full git history + .env secrets — to xAI's cloud, and the opt-out doesn't stop it (wire-captured)
by u/TastyLeadership2757 in LocalLLaMA

OpenAI reset every Codex user's limits and left the 5-hour cap off

Codex lead Thibault Sottiaux says OpenAI is "once again resetting the usage limits for all" and still running without the 5-hour rate limit, after passing 8M active users across Codex and ChatGPT Work. In the post he's replying to, Sam Altman credits the inference team with "heroic work to be able to support demand" and warns that "it is possible there are some hiccups soon." If you've been rationing, this is the window.

GPT-5.6's Ultra mode can burn a 5-hour Codex limit in 20 minutes, Theo says

Theo calls Ultra "a MESS because at the moment, one run can nuke your five-hour limit in 20 minutes" — and names the mechanism: although it's presented as a reasoning level, it's "really just a skill that spawns max-reasoning sub-agents on repeat." That's his claim rather than a published measurement, and nobody has reproduced the number. Worth knowing before you spend the headroom OpenAI just handed back.

Claude charged €15 against a €2 spend cap on one prompt, users report

u/theNorrah set a €2 limit with auto-reload off, sent a single summarize prompt, and says it ran to about €15: "Did I just spent 14 EUR, on 'one' summarize prompt, when I had limits on, and auto reload off?" The thread has 1,438 upvotes, and commenters describe the same shape at other numbers — u/skipITjob: "I had £15 and had usage credits turned off... It still used it." u/keaton_au: "I had $1 limit enabled. It spent $42 before I realized." u/Full-Ad-3461's theory is the testable one: "it always finishes the turn and just charges however much that was." These are user reports, not something we reproduced.

Claude spent +15 EUR of a 2 EUR limit.
by u/theNorrah in ClaudeAI

Costs that never show up on the bill

Agents removed the code review that spread understanding — and nothing visibly breaks

Armin Ronacher's essay The Tower Keeps Rising is the best idea published this week. Code review was slow, he argues, and "much of that slowness was waste but not all of it was. Some of it was the process by which your understanding became mine, and by which both of us discovered whether we still agreed about how the system worked." Agents remove that friction. The catch is that nothing alarms you when it goes: unlike Babel, "construction can continue after shared understanding has already collapsed… The tower does not fall, and so we do not notice what was lost."

Some late weekend thoughts: What can the bible tell us about vibecoding? lucumr.pocoo.org/2026/7/13/th...

— Armin Ronacher (@mitsuhiko.at) 2026-07-14T16:37:23.102Z

OpenAI's own developer docs are full of AI filler, Gergely Orosz says

"The amount of AI writing on OpenAI's docs makes me sick," Orosz wrote of the official cookbook. "Filler sentences for nothing. Mannerisms and phrases humans would not write. Has a human even read this?" His real worry is downstream: "all of this will change how other docs are written, and how we all talk—for the worse IMO."

The amount of AI writing on OpenAI's docs makes me sick. Filler sentences for nothing. Mannerisms and phrases humans would not write. Has a human even read this? And all of this will change how other docs are written, and how we all talk-for the worse IMO. 🤮 developers.openai.com/cookbook/exa...

— Gergely Orosz (@gergely.pragmaticengineer.com) 2026-07-14T09:23:49.349Z

Give agents a small custom language and wrong code stops compiling

The constructive answer to both items above, from Unmesh Joshi on Martin Fowler's site. Rather than prompting harder, you build a domain-specific language (DSL) — a small vocabulary that can only describe your problem — and hand the agent that instead of free rein. Output that doesn't make sense in your domain then fails at compile time, with a domain-specific error, before any human reviews it. The inversion worth stealing: the DSL becomes the artifact you maintain, not the prompt.

NEW POST LLMs generate code incredibly fast, but to ensure they generate exactly what is intended, they need clear boundaries. Unmesh Joshi shares his experience using abstractions and Domain-Specific Languages (DSLs) to provide a strong harness to guide an LLM. martinfowler.com/articles/llm...

— Martin Fowler (@martinfowler.com) 2026-07-14T13:29:39.882Z

Running models on your own hardware

Bonsai squeezes Qwen3.6-27B from 54GB to 7.2GB, keeping 94.6% of its quality

PrismML's Bonsai rebuilds Qwen3.6-27B with ternary weights — every weight is just -1, 0 or +1 — under Apache 2.0, and AnythingLLM founder Tim Carambat runs it hands-on. From PrismML's own model cards: the ternary build deploys at ~7.2GB and keeps 94.6% of full-precision quality across 15 benchmarks; the 1-bit build is 3.9GB and keeps 89.5%. Coding survives better than the summary numbers suggest — 92.3% retained on the 1-bit build, second only to math. One correction to the phone story doing the rounds: at ~7.2GB the ternary build "exceeds the ~6 GB per-app iOS memory budget and is laptop/GPU-only." It's the 3.9GB 1-bit build that fits a phone.

Bonsai loses tool calling before coding — PrismML says agentic work isn't ready

PrismML's card is blunt: "Agentic coding (long-horizon, multi-file, run-test-and-repair workflows) is not yet a strong target of this release." r/LocalLLaMA got there independently while benchmarking it. u/Total_Drag7439: "Agentic coding leans on long-context reliability and consistent tool calls, which is the first thing aggressive quantization degrades. These builds shine as fast local drafters; pair them with a bigger model for the agent loop." The thread also has numbers PrismML didn't publish: u/pulse77 measured 100 tok/s on the 1-bit build but only 3 tok/s on ternary with a 4090 — because ternary's CUDA kernel is still an unmerged pull request, while CPU and Metal have landed. If you're on NVIDIA, ternary stays slow until it merges.

Bonsai-27B & Ternary-Bonsai-27B - Updates (on PRs)
by u/pmttyji in LocalLLaMA

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The New Way is human-curated — a person picks every story. The summaries are written with AI (Claude) and reviewed before we hit send.