AI engineers, on average, spend 60-70% of their time writing and refining a prompt, instead of using those prompts to get what they really want → reliable outputs from their LLMs!
Before Future AGI-
→ write system instructions
→ token overhead kills context budget
→ optimize for fewer tokens
→ semantic meaning gets lost
→ add few-shot examples
→ examples don't cover edge cases
→ implement structured output
→ parsing breaks on complex responses
⚠️ This cycle ends here!
We have built an intelligent Prompt Optimizer Agent at Future AGI, to automate the hardest part of prompt engineering. Just describe your objective in natural language, and the agent instantly generates a structured, optimized prompt - what might've taken you days to iterate on manually. How it helps:
After Future AGI-
Input ->
Raw user objective as natural language query
Process ->
Powered by evals & synthetic data, our agent creates the perfect first version of your prompt
Output ->
Professional prompts with all necessary context and examples covering edge cases
No technical expertise required. No more wasted time on trial and error. Just get the results you actually want, instantly.
👉 Generate your perfect prompt today - https://shorturl.at/2mNu5
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