Developer tag | eYssen AI

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Documentation You Will Actually Maintain

Krisztian Eyssen, Krisztian Eyssen

Documentation You Will Actually Maintain

Two independent measurements say the same thing, and both contradict received wisdom: **bad documentation is measurably worse than none**, and the machine-generated "repo tour" **lowered the success rate while making runs 20–23% more expensive**. This post is about what survives all that — not much, but it works.

Intermediate Developer Recipe Coding & Development

Sep 13, 2026

Debugging with AI: A Reproducible Method

Krisztian Eyssen, Krisztian Eyssen

Debugging with AI: A Reproducible Method

On a synthetic, self-contained bug, models get the location right 38–53% of the time. In a real repository, **from the code alone, 1–5%.** The text of the bug report on its own is worth six to thirteen points, and the **order** of the input as much as thirty-seven. This post is about how you hand the bug over.

Intermediate Developer Troubleshooting Coding & Development

Sep 13, 2026

AI in Code Review: Which Bots Are Worth It

Krisztian Eyssen, Krisztian Eyssen

AI in Code Review: Which Bots Are Worth It

In an independent measurement, the precision of AI review agents is **3.2–5.1%** — roughly one comment in twenty lands. In a peer-reviewed vendor study, meanwhile, **38.7%** of the comments triggered a code change and PR turnaround got **30.8%** shorter. Both are true. They are not measuring the same thing — and that is what this post is about.

Advanced Developer Tool review Coding & Development

Sep 13, 2026

DevOps and Infrastructure with AI

Krisztian Eyssen, Krisztian Eyssen

DevOps and Infrastructure with AI

The same model that solves 86% of Python tasks manages barely a **fifth** of infrastructure-as-code tasks. And there is a measurement that took the result from 14% to **93%** — of the 79-point gain, **48.9 points** came from retrieved documentation, prompt structure and the scanner's feedback, **21.5 points** from switching models, and **8.6 points** from letting the model **see the rule**.

Advanced Developer How-To Coding & Development

Sep 13, 2026

Refactoring Safely with AI

Krisztian Eyssen, Krisztian Eyssen

Refactoring Safely with AI

Roughly **one AI refactoring in twenty changes the behaviour while the tests stay green.** That is not an estimate: it falls out of multiplying two published measurements. And that number is the reason the order of your checks matters more than the prompt here.

Advanced Developer How-To Coding & Development

Sep 13, 2026

Your First Task with a Coding Agent

Krisztian Eyssen, Krisztian Eyssen

Your First Task with a Coding Agent

There is a metric for how long a task an agent solves with a 50% chance of success. For the best model that is roughly **five hours of human work**. Fifty percent means it gets every second one wrong. Do not put your first task there — and give it something it can run itself.

Beginner Developer How-To Coding & Development

Sep 13, 2026

Choosing an AI Coding Setup: IDE, Terminal or Cloud

Krisztian Eyssen, Krisztian Eyssen

Choosing an AI Coding Setup: IDE, Terminal or Cloud

In the summer of 2026 one popular AI editor vanished as a product name, and another changed owners. Their pricing stayed; their names did not. Which is why you are not choosing a product but an **architecture** — and there are four questions to settle up front: where the code runs, when you look at it, how much it asks, and who trains on it.

Intermediate Developer Comparison Coding & Development

Sep 13, 2026

Autocomplete, Chat, Agent: Three Modes of AI Coding

Krisztian Eyssen, Krisztian Eyssen

Autocomplete, Chat, Agent: Three Modes of AI Coding

The difference between the three modes is not the model — the same model runs in all three. The difference is **whose hands the filesystem is in**. In the first it is yours, in the second it is on the clipboard, in the third it is the tool's — and from there the only question is when it asks.

Beginner Developer Explainer Coding & Development

Sep 13, 2026

Testing and Monitoring Your Agents

Krisztian Eyssen, Krisztian Eyssen

Testing and Monitoring Your Agents

In a survey of 1,300 practitioners, **39.8%** of respondents ran offline evaluation and **32.5%** ran it online — while everyone named **quality** as the main obstacle to getting into production, more than twice as often as cost or security. Everybody logs. Measuring whether the agent is doing a good job is something most people cannot do. This article is about how you can.

Advanced Developer How-To Agents & Automation

Sep 13, 2026

Multi-Agent Systems: When More Agents Help

Krisztian Eyssen, Krisztian Eyssen

Multi-Agent Systems: When More Agents Help

Five real multi-agent systems were measured in the same study. The best one scored **84.8%**, the worst **13.3%** — and in the middle of the field sit two systems that got **three quarters of the tasks wrong**. The difference did not come from the model. It came from the pattern. This article is about **which four patterns pay back the cost of coordination, and which two do not.**

Advanced Developer Explainer Agents & Automation

Sep 13, 2026

Agent Memory: What to Store and What to Forget

Krisztian Eyssen, Krisztian Eyssen

Agent Memory: What to Store and What to Forget

Memory is the weakest agent capability there is. On the best independent measurement, **the average of 109 models fails to reach 30% on any memory strategy** — the very same models score 86–91% on simple tool calls. That measurement also shows that **there is no universally good memory architecture**. And there is a second reason for caution: memory is an **attack surface** — in one study an attacker planted a persistent false memory with a **98.2% success rate**, using nothing but questions.

Advanced Developer Explainer Agents & Automation

Sep 13, 2026

Subagents and Parallel Work

Krisztian Eyssen, Krisztian Eyssen

Subagents and Parallel Work

The most quoted number says a multi-agent setup is **90.2% better** than a single-agent one. The same source also writes that it uses **fifteen times as many tokens**, and that **80% of the performance difference is explained by token consumption alone**. And a 2026 paper showed it formally: **at an equal token budget, the single-agent system wins.** The value of splitting a task is not parallelism — it is **clean context**.

Advanced Developer How-To Agents & Automation

Sep 13, 2026

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