When it works doesn't mean it's good

<!-- SC_OFF --><div class="md"><p>It’s been somewhere between 1 and 1.5 years since I last wrote a line of code.</p> <p>I wrote everything from Assembly and C to Python and

<!-- SC_OFF --><div class="md"><p><a href="https://youtu.be/vczBo0AvbTI?si=pglMPmTjsq-TNJa9&amp;t=375">https://youtu.be/vczBo0AvbTI?si=pglMPmTjsq-TNJa9&amp;t=375</a></p>

<!-- SC_OFF --><div class="md"><p>We lost a client because our system said &quot;Good morning!&quot; to someone who had just called to complain.</p> <p>She called. Got no answer.

<!-- SC_OFF --><div class="md"><p>With the recent rise of MCP tools, I’ve been seeing more discussions about how people doing research or data scraping can now get usable datasets

<!-- SC_OFF --><div class="md"><p>I keep running into the same annoying gap.</p> <p>An AI workflow looks solid in the first run. The happy path works. Logs are clean enough that

<a href="https://news.ycombinator.com/item?id=48614631">Comments</a>

<!-- SC_OFF --><div class="md"><p>You could have William Shakespeare himself draft an email and ChatGPT will still say &quot;A few minor tweaks&quot; You could even fix those

<table> <tr><td> <a href="https://www.reddit.com/r/OpenAI/comments/1sw0vcf/stanford_researchers_fed_a_language_model_a_dna/"> <img alt="Stanford researchers fed a language model a