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Behind the Scenes of AI Observability in Production
What actually works after 6 months of trial and error
Feb 3
•
Alejandro Aboy
28
5
6
The Realistic Guide to Mastering AI Agents in 2026
From zero to production in 6–9 months. What to learn, what to skip, and why most tutorials fail.
Jan 6
•
Paolo Perrone
89
5
12
The Underrated Science of LLM Samplers
The secret sauce for balancing diversity, quality and precision
Nov 25, 2025
•
Shmulik Cohen
46
8
9
Stop Launching AI Apps Without This Framework
A practical guide to building an eval-driven loop for your LLM app using synthetic data, before you have users.
Oct 30, 2025
•
Hugo Bowne-Anderson
41
4
6
Building Reliable AI Agents with Durable Workflows
How to make agents resilient to any failure
Oct 23, 2025
•
Peter Kraft
and
Paul Iusztin
30
2
3
Escaping POC Purgatory: Evaluation-Driven Development for AI Systems
A new software development life cycle for LLMs
Oct 16, 2025
•
Hugo Bowne-Anderson
and
Stefan Krawczyk
24
8
3
The Top 11 Ways to Easily Improve Your AI Applications
AI Software Demands a New Approach
Oct 9, 2025
•
Hugo Bowne-Anderson
and
Hamel Husain
29
3
7
From Beginner to AI/ML Pro in 2025
The step-by-step roadmap that gets you hired
Sep 30, 2025
•
Paolo Perrone
122
10
25
AI Agents in 5 Levels of Difficulty
With full code implementation
Sep 23, 2025
•
Paolo Perrone
70
3
7
The 5-Star Lie: You Are Doing AI Evals Wrong
Why binary evals are better than likert scales
Sep 20, 2025
•
Hamel Husain
50
10
11
The Mirage of Generic AI Metrics
Why off-the-shelf evals sabotage your AI product
Sep 13, 2025
•
Hamel Husain
61
7
6
The Real Battle-Tested RAG Playbook
7-steps trusted by OpenAI, Anthropic & Google
Aug 12, 2025
•
Jason Liu
95
4
12
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