Agents Meet Databases: The Future of Agentic Architectures https://
buff.ly/eJtpaMi
#AI #MachineLearning #DeepLearning #LLMs #DataScience
TOOLS
-
Agents Meet Databases: The Future of Agentic Architectures
By
–
-
Claude Usage Limits and Subscription Plan Options Discussion
By
–
My Claude limits reset at 3pm today; taking a little breather till then… or should I get another max 200 plan?
-
Claude Code used for SeaweedFS experimentation
By
–
It's working really well for me so far! I used it to experiment with SeaweedFS in Claude Code for web this morning
-
LoRA: Fine-tuning Large AI Models Efficiently Without Full Retraining
By
–
LoRA: Teaching Massive AI Models New Skills Without Retraining Everything
— Satya Mallick (@LearnOpenCV) 13 février 2026
In this episode of Artificial Intelligence: Papers and Concepts, we break down LoRA (Low-Rank Adaptation) – a breakthrough technique that makes fine-tuning large language models faster, cheaper, and far… pic.twitter.com/Zmw6e9lsnPLoRA: Teaching Massive AI Models New Skills Without Retraining Everything In this episode of Artificial Intelligence: Papers and Concepts, we break down LoRA (Low-Rank Adaptation) – a breakthrough technique that makes fine-tuning large language models faster, cheaper, and far
-
Kimi K2.5: Open-source SOTA model with agents and tools
By
–
Kimi K2.5 is THE BEST model for OpenClaw. It's open-source, SOTA on every benchamark, and SO AFFORDABLE!!! What you get:
✓ Vision reasoning (SOTA model)
✓ 100 parallel agents + 1,500 tool calls
✓ Expert Office outputs (Excel/PPT/Word/PDF)
✓ Video-to-code deployment
✓ -
Local open-source coding agent with AI workflow
By
–
Open-source coding agent that runs 100% locally.
— God of Prompt (@godofprompt) 13 février 2026
Unlike Claude Code:
✓ Fully unrestricted
✓ Transparent (Python-based)
✓ Accepts video as input
✓ No cloud dependency
Watch it build an autonomous driving data visualization through MCP:
→ Reads local datasets
→ Generates… pic.twitter.com/hlGz7pLOaaOpen-source coding agent that runs 100% locally. Unlike Claude Code:
✓ Fully unrestricted
✓ Transparent (Python-based)
✓ Accepts video as input
✓ No cloud dependency Watch it build an autonomous driving data visualization through MCP:
→ Reads local datasets
→ Generates -
AI agents research YouTube creators across niches
By
–
100 YouTube creators across 100 different niches.
— God of Prompt (@godofprompt) 13 février 2026
This would take you 8+ hours of manual research.
Kimi deployed 100 sub-agents simultaneously:
→ Each researched a specific niche
→ Found top creators
→ Scraped subscriber counts
→ Grabbed channel URLs
→ Compiled everything… pic.twitter.com/BmfkX1pQfi100 YouTube creators across 100 different niches. This would take you 8+ hours of manual research. Kimi deployed 100 sub-agents simultaneously:
→ Each researched a specific niche
→ Found top creators
→ Scraped subscriber counts
→ Grabbed channel URLs
→ Compiled everything -
Users report next-level experience with Kimi K2.5 and OpenClaw
By
–
People are already using Kimi K2.5 with OpenClaw. The experience is just at the next level, and it's so affordable!!! No stress, just build
-
LLM system replaces $4,200/month tools with $0 cost
By
–
I used to pay for Crayon, Klue, and Kompyte. $4,200/month combined.
Canceled all three. This LLM system is better because: Real-time (not quarterly reports)
Multi-source (not just press releases)
Reasoning-based (not just data dumps) $0/month The prompts are in this thread. -
Automated Weekly Competitive Intelligence Prompt for LLMs
By
–
Advanced – Automated Weekly Reports The Weekly Intel Protocol: Run this every Monday: Prompt: Create a competitive intelligence brief for [COMPETITOR]: SECTION 1: What Changed This Week
[Gemini output here] SECTION 2: Strategic Implications
[ChatGPT pattern analysis]