308+ test edilmiş prompt şablonu; yazıdan koda, görsel üretiminden kariyere kadar. Değişkenleri ({böyle}) kendinize göre doldurup doğrudan kullanın.
A productive workday begins with intentional mental alignment before tasks take over your attention. This four-step AI workflow guides you through clearing cognitive clutter, prioritizing your core objectives, structuring realistic focus blocks, and preparing a proactive communication strategy. Mental Brain Dump and Priority Extraction This is the first step of your morning rou
Looking for the best prompt to give ChatGPT, Gemini, Perplexity, or any AI tool that instructs it to act as a **prompt engineering professional**. I need it to generate robust, conversational, and production-ready prompts that sound like a real person thinking—not robotic or generic. What's the prompt that works best for this? Any recommendations? Thanks. submitted by /u/Ok-Sci
We’ve built two release systems for one support agent and now we’re struggling to figure out which prompt is actually in production. PMs tune the conversational parts in a playground. Engineers keep fallback text, tool instructions and safety rules in code. Both workflows are reasonable on their own. But, last week a hotfix changed the system prompt and unfortunately, the evalu
I'm starting to believe that keeping production prompts in the codebase is one of those decisions that feels harmles until you have to explain a quality drop. At the moment, we’ve got prompts scattered all over the place. Some are in config files, some live in helper functions and a few are buried who knows where. Then someone tweaks the prompt, someone else changes the model a
If you have built autonomous agents or multi-step tool-calling workflows with LLMs, you have likely run into the standard failure modes that break production agents: Premature Action Bias: The model fires off tool calls or answers the user before mapping out prerequisites and the logical order of operations. Fragile Error Handling: When an API call fails or returns unexpected d
so i noticed something annoying. whenever i asked AI to write something - email subject, product description, whatever - the result was always fine. never bad, never great. just fine kept tweaking the prompt. "make it punchier." "more casual." still fine then one day i was too lazy to write a prompt so i just pasted 5 subject lines id written myself and asked which one was best
One of the easiest ways to improve AI outputs isn't writing longer prompts. It's giving examples. Instead of this: «Write a product description.» Try this: «Write a product description following this structure: - A short opening hook - Three benefit-focused bullet points - A professional but friendly tone - End with a clear call to action» Notice what's different. You're no l
trying to figure out the least stupid way to do this. same company needs: - landing page - pitch deck - 30sec promo video my first instinct was one giant master brief and then reuse it for all 3. but i think thats wrong. some stuff should probably be **fixed context**: company facts product audience positioning approved claims / proof brand voice + real examples stuff it absolu
Junior product analyst at a fintech. Building the deck stopped being the hard part a while ago. The hard part is standing in the room when a VP asks the one question I did not think about. So before every review I run this on my own deck or summary. ``` You are a skeptical senior executive reviewing my analysis before I present it. Here is what I am presenting: {paste your key
