A Breaking Change blog post on building tooling to build the tooling — an honest walkthrough of automating a small side business with AI assistance.
Why I recommend it: A good antidote to launch-day stories: most of the work is plumbing, and this shows the plumbing.
This is the only entry from Building a T-Shirt Factory Factory in the hub so far.
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Free collection of cart-abandonment studies, calculation notes and checkout findings. Baymard reports an unweighted 70.22% average across 50 studies from 2006–2025; differing definitions and samples mean this is not a target every store should expect. Paid research products are separate.
A KDnuggets tutorial by Bala Priya C with five beginner Python scripts for automating repetitive tasks, including organizing files, processing images and simplifying everyday workflows, with code and explanations.
A KDnuggets guide by Vinod Chugani that goes round by round through current data science hiring processes, including AI-assisted coding rounds and generative AI evaluation questions, and lists ways candidates can prepare.
A Built In survey of job seekers on how AI tools shape which employers they find and consider. Among respondents who use AI for employer research, 66% say they applied to a company they had not considered and 53% say they decided not to apply somewhere because of what AI showed them. Built In sells employer branding services.
Artificial Analysis reports Muse Ember benchmark scores and task-cost estimates, including an Intelligence Index score of 36 and $0.14 per task in its evaluation. These are evaluator-specific results, not a verified Meta launch announcement or evidence of free model access.
Epoch AI explains an Inference Performance Index for estimating chip capacity across agentic workloads and output-speed requirements. Its modeled comparisons, expressed in GB300 equivalents, depend on workload and hardware assumptions and are not universal real-world performance guarantees.
