الذكاء الاصطناعي

Chain-of-thought, few-shot, role prompting, RAG — a practical guide to getting consistent outputs.

Abstraction has a cost. Here's when rolling your own is the right call.

A deep dive into the capabilities and failure modes of vision-language models.

I ran both through 200 coding tasks across Python, TypeScript, and SQL. Here are the results.

Why making AI do what we actually want is harder than it sounds — and why it matters.

Token costs, latency, error rates — the real numbers from a product serving 10k daily active users.

Fine-tuning is not magic. Here's what the research actually shows about when it helps.

I've tested 12 different agent frameworks. Here's my honest take on the state of the ecosystem.

Benchmarks lie. Here's how to build your own eval set that actually measures what matters.

No PhD required. Here's how vector similarity search actually works.

Both sides of the debate, backed by actual productivity data from engineering teams.

Stack: OpenAI API + Supabase + a bit of Node. It now handles 70% of our tickets automatically.

If you're self-hosting, here's what the benchmarks look like on real hardware.

From LLMs to autonomous agents, from research papers to real-world applications. This is your space.