Doğal Dilden SQL Güvenlik Katmanı
Text-to-SQL özelliğinin veri sızıntısı ve pahalı sorgu risklerini sınırlar.
HAZIR VE KOPYALANABİLİR
Prompt Kütüphanesi
305+ test edilmiş prompt şablonu; yazıdan koda, görsel üretiminden kariyere kadar. Değişkenleri ({böyle}) kendinize göre doldurup doğrudan kullanın.
about 1 in 7 people have unclaimed money sitting in an official government database. asked claude to search every state i've lived in under my name and old names
This is the one that sounds fake and isn't. When a bank account goes dormant, a refund check never gets cashed, a utility deposit gets forgotten, an old paycheck goes uncollected, that money doesn't disappear. By law it gets handed to the state and held for you, sometimes for decades. The databases are public, official, and free to search. Almost nobody checks. Search my state'
Cached my agent's browser paths to save tokens, spent three days debugging wrong data instead
Seemed obvious. Agent kept re exploring the same sites so I cached what it found. Token spend dropped immediately. Then a site changed a form and the cached path kept running. Didn't error, didn't return empty, just returned the wrong field confidently for three days before I noticed. Moved to webcmd after that, which does the same explore-once-then-reuse thing but properly: co
Five very real, very cool, prompt-focused compositions of the 44 MIT-licensed tools I created that you can build yourself
I ran the whole set of 44 composable AI- and prompt-focused apps I just released on my website through my system and had it build out five real samples compositions that you can actually build today yourself, assuming you have the needed technical chops. Every one listed here uses only tools from the 44 and the system checked that the data actually flows; the port/typecheck/dec
I found a prompt that turns 80 pages of course material into 20 pages of comprehensive notes - Norra NotebookLM
So long story short notebookLM has been a game changer and has helped me get good grades and save tons of time and while I was exploring this is the best workflow that helped me huge chunks of data into small comprehensive course Phase 1: Preparation and Segmentation Split the Module (Crucial Step): I upload my module (usually 300–400 pages) to ILovePDF and split it into indivi
I made RouterDash, a free Prompt Playground to compare models & providers
I created this tool to help me test and evaluate different model responses: RouterDash. This allows me to compare models from OpenRouter, Groq and Cerebas. I used this to find the cheapest possible, high quality responses for another project. Fully client side, all data is stored in browser local storage for complete privacy. I recently added prompt templates and image attachme
i started putting wrong examples in my prompts. it works better than the right ones.
so i noticed something weird last week was building a prompt to classify support tickets. bug report vs feature request. standard few-shot, gave it 3 clean examples of each. worked fine on my test data then threw a real ticket at it and it got it wrong. "the export button is too slow, we need this fixed" - it called that a feature request. which, fair, it kind of is. but the cu
Stop making your prompts longer. The highest-impact fix is separating your instructions from your data.
keep seeing people respond to a bad output by adding three more paragraphs of instructions. Most of the time the prompt was not too short. It was mixed. The pattern that fixed the most for me: physically separate the instruction from the material it operates on. When you paste a task and the content it applies to as one blob, the model has to guess where your command ends and y
The cheapest prompt optimisation I found this year was deleting the navigation from context entirely
Spent a while trying to trim prompts for an agent that pulls data off a few sites daily. Tightened instructions, cut examples, and compressed the system prompt. Marginal gains at best. Then I actually looked at the token breakdown, and the prompt was never the problem. Navigation was DOM dumps, screenshots, and the model reasoning its way to a button it had already located in t
Sunum Veri Görseli Seçimi
Slaytlardaki veriyi doğru grafik ve ölçekle anlatmayı sağlar.