Engineering Notes
Thoughts and Ideas on AI by Muthukrishnan
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05
Nov 2025
Agent Debugging and Observability for Seeing Inside the Black Box
Master the art of understanding, debugging, and monitoring AI agents through tracing, logging, and observability patterns
05
Nov 2025
Run Pre-Mortems, Not Post-Mortems
Most engineering teams are great at post-mortems—dissecting what went wrong after a failure. But elite teams do somethi...
04
Nov 2025
Design Ownership Boundaries, Not Org Charts
Most engineering managers scale teams by drawing org charts. The best ones design ownership boundaries first, then let ...
04
Nov 2025
Temporal Difference Learning and Q-Learning as the Engine of Agent Intelligence
**Temporal Difference (TD) Learning** and its most prominent variant, **Q-Learning**, are among the most influential al...
25
Oct 2025
Scaling Agent Intelligence Through Specialization with Mixture of Experts
**Mixture of Experts (MoE)** is an architectural pattern built around dynamic routing: instead of one generalist model ...
25
Oct 2025
Transform Failures Into Capability, Not Bureaucracy
Every organization faces failures: outages, security incidents, missed deadlines, botched releases. The critical questi...
24
Oct 2025
Build Leverage Through Documentation as Code
The best engineering managers don't just build products—they build systems that make knowledge transfer automatic, deci...
24
Oct 2025
Policy Gradient Methods and Actor-Critic Architectures
Master the mathematics and implementation of policy gradient methods and actor-critic architectures—the foundation of modern agent learning systems.
23
Oct 2025
Debug Organizational Velocity, Not Individual Productivity
Most engineering managers obsess over individual productivity. They measure story points, track commit frequency, and o...
23
Oct 2025
Decision-Making Under Partial Observability with POMDPs
**Partially Observable Markov Decision Processes (POMDPs)** are the mathematical framework for making optimal decisions...
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