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From Vibe Coding to Production: How to Build a Traceable PRD-to-Prompt Workflow for Shipping Maintainable AI Code A concrete, repeatable workflow that closes the gap between AI-generated prototypes and production deployment by linking Product Requirement Documents directly to agent prompts and enfor
A bot was firing Subscribe and Purchase events from Telegram straight to Meta's Conversions API, and every call came back with a 400: "error_user_title": "Missing Messaging Channel Parameter", "error_user_msg": "A messaging channel parameter is required when provided action source is business_messag
If you bill per result, there is one design decision that quietly decides whether customers trust you: what you do when you could not get an answer. Most usage-billed APIs collapse the world into two states. The call worked, or it failed. Valid or invalid. Found or not found. That binary is where th
Embeddings are behind search, recommendations, and most of modern AI, and they are usually explained with intimidating diagrams. The core idea is simple and worth building yourself: an embedding turns a thing (a word, a document, a product) into a list of numbers (a vector) so that similar things en
Nearly 65% of enterprise AI failures in 2025 traced back to context drift or memory loss during multi-step reasoning. Not model capability issues. Not hallucinations from weak training data. The agent simply lost track of what it was doing because its context window filled up with conversation histo
Look, the Developer's Guide to AI Translation Without Going Broke I still remember the first time I looked at my translation API bill. Three hundred and forty-seven dollars. For one week. Just for translating product descriptions into four languages. That's when I went down this rabbit hole, and her
I told myself it would be fine. I had been using AI coding assistants for suggestions and autocomplete for months — and it worked great. So when a new project came up with a tight deadline, I thought: why not let AI handle the whole backend? I set up a Cursor workspace, wrote a detailed spec, and hi
Autonomous AI agents are powering everything from customer support to high-frequency trading—but as they gain more control, the threats grow sharper. Too many agent security stacks depend on brittle prompt instructions, leaving gates open for jailbreaks and unintended command execution. Kakunin’s ne
The Democratization of the Security Operations Center Historically, Security Operations Centers (SOCs) were the exclusive domain of large enterprises, requiring massive capital expenditures, dedicated climate-controlled server rooms, and a small army of analysts. In the contemporary cybersecurity la
You don't really ever have to explain why a universal remote is a good idea. You have a bunch of stuff that needs controlling; this thing controls them all. Many companies have set out to build a product worthy of this idea, and one product came much closer than most. It was called the Harmony, and
Alphy Kottaram and Geordie Keating are back for more crime-solving adventures — here's how to watch "Grantchester" season 11 online and potentially for free.
The tools Linux developers love are coming to Windows.
A systems-level deep dive into the hidden microarchitectural costs of Kubernetes GPU time-slicing, and what it actually costs to co-locate Agentic AI workloads. The post GPU Time-Slicing for Concurrent LLM Agents on Kubernetes appeared first on Towards Data Science.
Upgrade your video calls with your Android phone's camera
If you are coming from the PHP world, you might be used to thinking that when a request reaches the web server, everything is parsed and processed from scratch. In Python, however, the behavior is a little different. A Python web server (for example, Gunicorn) starts one or more worker processes and
I recently took on a side project that needed to tap into multiple AI models – GPT-4 for complex reasoning, Claude for creative writing, and a local Llama 2 for quick drafts. My naive plan was to just call each API directly from my Python backend. Three days later, I had a tangled mess of authentica
A major runtime just got machine-translated to a completely different language and merged in under two weeks. Let me say that again slowly. Bun, the JavaScript runtime that the community keeps considering for a serious relationship, finished a rewrite of itself, from Zig to Rust. The rewrite was com
Repo: github.com/AmmarHassona/trainsafe I was working on fine-tuning an open-source small language model (SLM) on Arabic using DPO. I had the data, the pipeline, and everything set up for training. I was fairly confident that this training run would improve the model and align it further to what I w
We wanted to know when LLM is guessing versus when it actually knows the answer. LLM models expose logprobs - after every word they generate, you can request the top alternative tokens and their probabilities. Low entropy means the model was certain, high means it was guessing. I tested two models u
Two n8n issues that look harmless but silently break your workflows: The HTTP Request node shows a green ✅ but returns empty output Your workflow times out before finishing — and you're not sure where to change the limit Both are quick fixes once you know where to look. n8n marks an HTTP Request as
