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I built Calybris Core because I kept running into the same uncomfortable question in decision-heavy systems: After the system says "yes", "no", or "use this instead", what exactly can we prove later? Not prove in the formal-methods sense. I mean the practical engineering version: Which policy was ac
When I started preparing for the Claude Certified Architect Foundations (CCA-F) exam, the first thing that surprised me was how many people were studying for it the way you'd study for a generic LLM cert: heavy on prompt engineering tricks, light on the actual architecture material. The published bl
I'm a data science student learning how AI APIs are priced. I run agentic coding sessions through OpenRouter, where every code-generation loop pulls a fresh batch of tokens from a model I picked from a list of 300+ names I barely understood. Some loops cost a few cents. Some cost dollars. The total
We've all seen the archetypes: the developer who boasts about knowing seven different programming languages, the interview prep champion who can solve a LeetCode Hard in their sleep, and the coding bootcamp graduate eager to write thousands of lines of code. Early in a software engineering journey,
When organizations build AI infrastructure, GPUs usually get all the attention. Teams invest in the latest accelerators, add high speed networking, and expect training jobs to scale effortlessly. Yet many AI clusters deliver disappointing performance despite having powerful hardware. The surprising
Check this out: how I Stopped Worrying About AI API Bills: A Data-Driven Breakdown of Startup vs Enterprise Routes I've spent the last six months running inference workloads for two different projects — one a scrappy Series A startup, the other a mid-size enterprise procurement contract. Both teams
Your agent deleted something it shouldn't have at 2am. The alert fired. Now answer three questions: what did it do, why did it do it, and what did it touch. If you're grepping JSON for the next 30 minutes, you don't have tracing. You have logs with a worse UI. This is the part nobody instruments unt
I run a small WordPress + Cloudflare agency. Two recurring pains finally pushed me to build something instead of complaining: Pain 1: contractor access drift. I'd hand a contractor root SSH for "just this one task". Three jobs later, I'd realize four ex-contractors still had access I never rotated.
At a recent conference, Lenovo reps said that the higher memory prices are the new normal and won't be going away anytime soon.
All the ways to watch Uruguay vs Spain, as Marcelo Bielsa's strugglers target the win that would send them through to the knockout phase at the World Cup 2026.
All the ways to watch Cape Verde vs Saudi Arabia, as these two Group H underdogs target a place in the round of 32 at the World Cup 2026.
Following last month’s wider rollout of the Liquid Glass redesign on iPhone, WhatsApp is now testing the updated look on iPad, while a separate version remains in development for Mac. Here are the details.
Yet another patent troll wants to get paid by Samsung. Tau Ceti Ventures LLC has filed a lawsuit against Samsung in the US District Court for the Eastern District of Texas, alleging that the company infringed upon ten of its patents relating to making displays brighter, preventing screen burn-in, im
In a video published on YouTube Shorts today, Joanna Stern called out Apple over AI-generated knockoffs of her book that continue to appear on Apple Books. Here are the details.
If you own a Google TV Streamer or plan to get one, you have an exclusive audio option in the Google Home Speaker. Connecting two of them gets you spatial audio, and it’s certainly a step up from some more expensive options.
AI spend per employee just became a line item that bosses watch, and the number that kicked off the conversation is wild: one worker running up a $30,000-a-year rate on Claude. That figure comes from Rippling CEO Parker Conrad, who told TechCrunch about an employee who used the assistant to read the
Open a new session with Claude Code, Cursor, or Copilot and it has no idea what you were doing yesterday. Your stack, your decisions, the bug you spent an hour explaining — gone. So you re-explain. Again. The root cause is simple: your AI's memory only lasts one conversation. Close the terminal and
lg logger It is very convenient if you do not need to drag zap, logrus with you, but just make go get and use it as log, only write lg (which is even shorter) and with error levels, backlight. The backlight can be turned off with one function. The tests are written, the linter is there, CI/CD is con
Messy text is everywhere: support tickets, lead forms, emails, contracts, incident reports, call notes, Slack messages. The annoying part is that the useful data is usually in there somewhere, but not in a shape your app can trust. I built a small Python example that uses Telnyx AI Inference to turn
I usually write backend stuff in Go, so I prefer strict typing, predictable performance, and explicit code. However, I wanted to see if the recent hype around AI-assisted development ("vibecoding") is actually useful for building production-ready apps, or if it's just for quick MVPs. To test it fair
