Why Your AI Agent Is a Compulsive "Spender": The Truth About Token Consumption
Autonomous agents can turn a trivial task into a financial black hole because token consumption is massive, stochastic, and difficult to predict.
Section
Archive
All published posts.
The Agentic Coding Trap: Why the Productivity Promise Is Burning Developers Out
The pace of software development has undergone unprecedented compression. What was once simply programming is now trad coding: line-by-line work shaped by human problem-solving time.
When Context Betrays You: Deriving Contexts for Optional Operations in Go
In Go, context.Context is the standard mechanism for propagating cancellation, deadlines, and values across Goroutines and function calls. But passing context forward has a subtle trap.
Why Does Your AI Fail? The Secret Is Not in the Model, But in the "Agent Harness"
You have probably experienced this: one moment, GPT or Claude solves a complex coding problem in seconds; the next, the same AI forgets basic context or invents nonexistent information.
Building Real AI Agents with the Copilot SDK in Go
If you follow the GitHub Copilot ecosystem, you have probably heard of *.agent.md files. They are great for simple things, basically a boosted prompt that runs inside Copilot
DORA, SPACE, and the Science of Performance in the Age of Agility and AI
The paradox of modern speed We live in the paradox of technical abundance: in the age of Artificial Intelligence, we generate code in minutes, but organizations still struggle to convert that volume into real value.
The Illusion of Sequence: Why Hierarchy Is the Next Leap in AI Inference
There is an efficiency gulf between biological architecture and silicon. While a 12-year-old child already masters human language, models like GPT-3 require far more data.
3 Not-So-Intuitive Principles in Developer Experience (DX)
Engineering leaders and developers are constantly searching for more productivity. The pressure to deliver faster is relentless, but the path to that speed is rarely clear.
Taking AI Engineering to the Next Level with RAG
If you are starting to venture into AI Engineering and want to go beyond the basics, you need to deeply understand what **Retrieval-Augmented Generation (RAG)** is.
Multi-Agent AI Systems: When to Use Them, How to Build Them, and Why So Many Fail
You know when you are trying to solve a complex problem with AI and it feels like a single model cannot handle the job? Multi-agent systems help, but only in the right cases.