Just trying to see what a kontext lora can do at the moment
PROMPT ENGINEERING
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Training AI Models for Retro Video Game Live Action Conversion
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I've tried a few trainings since in the attempt to get a more natural old video game look, but nothing has paid off, yet. For my second pass I took video game screenshots, and asked 4o to make them live action. Then switched them for training (left/start > right/end, "make it an
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LangChainJS Integrates Gemini 2.5 Thinking Mode for Enhanced AI Reasoning
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Gemini 2.5 Thinking Mode LangChainJS integrates Gemini 2.5's thinking budget, giving developers precise control over AI reasoning steps to boost problem-solving accuracy. Discover the implementation: https://
medium.com/@afirstenberg/
langchainjs-and-gemini-2-5-thinking-mode-b066af008209
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Remove UI and black bars from training data
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flux kontext pro: > remove the UI and the black bars Handy for cleaning up training data.
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Fine-tuning Flux LoRA for PS1 video game style
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Some first tests with making a flux kontext lora for a PS1 style. I used face to many to make a dataset with 12 image pairs. Example: https://
replicate.com/p/z2e7ern65hrm
c0cqqd4vmrkqjg
… I used the fal trainer at 1000 steps ($2.50), took about 20 mins. Prompt:
"make it a ps1 video game" Left: Pro
Right: -
Training Flux LoRA for PS1 Video Game Style
By
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Some first tests with making a flux kontext lora for a PS1 style. I used face to many to make a dataset with 12 image pairs. Example: https://
replicate.com/p/z2e7ern65hrm
c0cqqd4vmrkqjg
… I used the fal trainer at 1000 steps ($2.50), took about 20 mins. Prompt:
"make it a ps1 video game" Left: Pro
Right: -
AI Design Workflow From Concept to UI With Four Tools
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— VISION IA (@vision_ia) 29 juin 2025
Use case for all designers who want to speed up their workflow: Reve → Midjourney → Topaz Astra → Figma
From concept to final UI in record time. All prompts are in this thread — save it for later! -
Building Effective AI Systems with Reasoning and Tools
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a little loop with reasoning
some tools and auth as seasoning
memory and self reflection
objectives give it good direction -
Making LLMs Work: Beyond Out-of-the-Box Limitations
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Studies of LLMs keep looking at the (very real) failures of LLMs working out-of-the-box in complex use cases. I am always surprised that naked LLMs can get so far as generalist systems But if you want to really make an agent handle a complex workflow, you can often figure it out
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Practical Solutions for AI Agent Reliability and Error Reduction
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In practice, for many useful applications, many of the various obvious problems with AI agents (drift, hallucination, compounding errors) are more solvable than they are in theory Clever prompting, tool use, constrained topics,
LLM judges & organizational process close some gaps