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> $100 day should be more than enough. To exceed that you have to coming up with creative ways to waste it.

You do not need much creativity for that. Just forget to put build artifacts or node_modules in your agent's ignore list and it will happily burn through the cap in thirty minutes


> It’s also a “you can’t scrape us but we can scrape you” mentality these companies are getting into.

And the problem often isn't some advanced attack. It's enough to follow links with session params, generate endless urls or ignore robots.txt to turn a regular crawler into a load generator. A site owner needs crawler protection from specific behavior and not another list of known bot signatures


Quickly pulling up a manual through a chatbot offers only a surface-level grasp of an unfamiliar task


Our team migrated a chunk of internal parsers to local weights purely to kill off query costs. The cloud api bill dropped by two-thirds in a single month


> For example, the article suggests $1T from enterprise productivity tooling. A quick Google suggests the global enterprise productivity tooling market is only worth about $0.1T right now

We tried to justify enterprise assistant budget to the CFO last quarter. They sent us packing after asking exactly how many headcount reductions we could guarantee post-purchase, which stalled the conversation immediately...


Placing LLL inside the user message right ahead of the new query keeps the common conversation prefix fully intact


A timeline turns contradictory instructions into an orderly sequence of updates. Without it the model just gambles between the old guideline and the new one on every run


As long as the relative time parser is hardcoded for japanese, english sessions are stuck with manual ISO dates. Wiring up dateparser or duckling would take an evening , so leaving that on the roadmap is an odd choice


Tell that to the engineers doing 70 % more triage while their compensation stays flat


Stories about Tim Cook sitting there being surprised by sales are total marketing. They simply ran out of memory chips because of the global shortage, so they repacked supply delays into a nice story about insane hype among AI startups. And hit two birds with one stone by throwing shade at their competitors


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