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Find the most practical, hands-on and comprehensive AI Engineering and AI for Work mastery courses at academy.towardsai.net - pathways for any experience. Since 2019 Towards AI has provided an open platform for sharing information, educational content and research on AI. It has more than 2,000 authors and benefits from hundreds of thousands of followers in the AI community. The platform is a leadi
Most AI agents never make it past Level 1.
The difference between a demo and a production-ready agent comes down to architecture:
Level 1: One model, every tool, one endless loop.
Level 2: Clear guardrails, scoped tools and a clean failure path.
Level 3: An orchestrator delegates messy work to specialised sub-agents.
The result? Cleaner context, lower costs and agents that can run without choking on their own history.
Follow for more practical AI engineering tips.
Interviewed another candidate today.
I asked her how LLM APIs charge.
She replied:
Per token — input tokens and output tokens, usually priced differently.
Then I asked how to reduce cost.
She said:
Shorter prompts, smaller models for easy tasks, caching, batching.
Then I asked a follow-up:
Your API bill doubled last month.
Traffic is flat.
Name the first three things you'd check.
What would your answer be?
07/10/2026
OpenAI’s latest smaller model, GPT‑5.6 Luna, was trained by its flagship model, GPT‑5.6 Sol! 🤯
07/09/2026
GPT-5.6 coding benchmarks
slight edge over fable at terminal bench
Interviewed another candidate today.
I asked her what embedding search is.
She replied:
You convert text into vectors and find documents whose vectors are closest to the query.
Then I asked how you measure retrieval.
She said:
Recall@k — whether the relevant document appears in the top k results.
Then I asked a follow-up:
Your recall@10 is 92%, but users say answers are wrong half the time.
Where's the gap?
What would your answer be?
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