github.com/FlowiseAI/Flowise… [Translated from EN to English]
→ View original post on X — @flowiseai, 2025-12-05 15:39 UTC
OPEN SOURCE
-
Flowise 3.0.12 Release: Gemini 3, Code Interpreter, Structured Output
By
–
3.0.12 is out!
— FlowiseAI (@FlowiseAI) 5 décembre 2025
🍌 Nano Banana Pro
Use Gemini 3 with Nano Banana Pro – with support of multi turn conversation
🖥️ Gemini Code Interpreter
Use built in Gemini Code Interpreter and enables the model to generate and run Python code
📜 Agent Structured Output
Agent node can now… pic.twitter.com/97HLu1CDTa3.0.12 is out! 🍌 Nano Banana Pro Use Gemini 3 with Nano Banana Pro – with support of multi turn conversation 🖥️ Gemini Code Interpreter Use built in Gemini Code Interpreter and enables the model to generate and run Python code 📜 Agent Structured Output Agent node can now support returning structured JSON output More bugfix and details in release note 👇
→ View original post on X — @flowiseai, 2025-12-05 15:38 UTC
-
Techniques to Reduce Hallucinations and Boost Accuracy
By
–
You can use these techniques RIGHT NOW I've been using these with Claude Sonnet 4.5, GPT-4, and Gemini 2.0 Flash for 6 months. Results: – 100% reduction in hallucinations on technical docs
– 3x faster iteration on code generation
– 90%+ accuracy on complex analysis tasks The -
Meta-Prompting: The Nuclear Option
By
–
Technique 10: Meta-Prompting (The Nuclear Option) This is what OpenAI's red team uses to break their own models and find edge cases. You ask the AI to generate the perfect prompt for itself. Template: I need to accomplish: [high-level goal] Your task:
1. Analyze what would -
Context Injection with Boundaries
By
–
Technique 6: Context Injection with Boundaries Anthropic engineers inject massive context but set clear boundaries on what matters. Template: [CONTEXT]
[paste your documentation, code, research paper] [FOCUS]
Only use information from CONTEXT to answer. If the answer isn't in -
Technique 5: Confidence-Weighted Prompting
By
–
Technique 5: Confidence-Weighted Prompting Google DeepMind uses this technique for high-stakes decisions. Ask the model to rate its confidence and provide alternative answers. Template: Answer this question: [question] For your answer, provide:
1. Your primary answer
2. Confidence level -
Structured Thinking Protocol for GPT-5
By
–
Technique 4: Structured Thinking Protocol
— God of Prompt (@godofprompt) 5 décembre 2025
OpenAI's GPT-5 team uses this for complex reasoning tasks.
Force the model to think in layers before responding.
Template:
Before answering, complete these steps:
[UNDERSTAND]
– Restate the problem in your own words
– Identify what's… pic.twitter.com/yFXgwVm5acTechnique 4: Structured Thinking Protocol OpenAI's GPT-5 team uses this for complex reasoning tasks. Force the model to think in layers before responding. Template: Before answering, complete these steps: [UNDERSTAND]
– Restate the problem in your own words
– Identify what's… -
CoVe Technique to Reduce Hallucinations
By
–
Technique 2: Chain-of-Verification (CoVe) Google's research team uses this method to eliminate hallucinations. The model generates an initial answer, then creates verification questions, answers them, and refines the original response. Template: Task: [your question] Step 1: Provide your…
-
AI Market Splits Premium Models Versus Cheap Open Source
By
–
The "commodity AI" thesis is wrong. The API market is splitting into two modalities: – Premium models (Claude) dominate programming and high-stakes work. Users pay $2+/M tokens because correct code > cheap code. – Cheap open models own roleplay and creative tasks. Volume is
