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How to Build an Advanced Agentic AI System with Planning, Tool Calling, Memory, and Self-Critique Using OpenAI API
TOOLS = { "calc": lambda expression: _safe_calc(expression), "kb_search": lambda query, k=3: _kb_search(query, int(k)), "extract_json": lambda text: _extract_json(text), "write_file": lambda path, content: _write_file(path, content), } TOOL_SCHEMAS…
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Six Choices Every AI Engineer Has to Make (and Nobody Teaches)
teach you how to make a model accurate. They rarely teach you…
One Flexible Tool Beats a Hundred Dedicated Ones
when you wanted an LLM agent to talk to a system at…
How to Maximize OpenAI’s Codex
articles about Anthropic’s Claude Code, and how I use it for programming,…
NVIDIA Introduces a 4-Bit Pretraining Methodology Using NVFP4, Validated on a 12B Hybrid Mamba-Transformer at 10T Token Horizon
Pretraining frontier-scale LLMs in FP8 is now standard practice, but moving to…
A Coding Implementation to Compress and Benchmark Instruction-Tuned LLMs with FP8, GPTQ, and SmoothQuant Quantization using llmcompressor
import subprocess, sys def pip(*pkgs): subprocess.check_call() pip("llmcompressor", "compressed-tensors", "transformers>=4.45", "accelerate", "datasets") import…
Pandas Isn’t Going Anywhere: Why It’s Still My Go-To for Data Wrangling
learning data science in 2020, Pandas was one of the most popular…
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