The Half-Life of a Good Decision

The best practice you followed six months ago might be the technical debt you're cleaning up today.

In traditional IT, a best practice can survive a decade. You study it. You argue for it in architecture reviews. You defend it when someone wants to cut corners.

In AI, six months is enough to flip one into an antipattern.

A paper published this week tested multi-agent orchestration frameworks against plain in-context prompting on procedural tasks. The orchestration lost. Same accuracy. More cost. More complexity. More failure modes.

Six months ago, multi-agent was the answer you gave when someone asked how to handle complex workflows. Not because it was always right. Because models could not yet follow a long, careful prompt. That was the constraint. The scaffolding was built around it.

The constraint changed. The scaffolding stayed.

This is the part of AI adoption nobody talks about enough. It is not just that things move fast. It is that yesterday's correct decision becomes today's drag. And you cannot always feel it happening. The system still runs. The agents still coordinate. Everything looks fine until someone asks why you are paying for complexity that a single prompt could replace.

We have approval processes built for risk. We do not have processes built for expiry.

What is the half-life of an AI architectural decision right now? Six months? Three?

This week on The Human in the Loop I go deep on the paper, what they tested, what held up, and what it means for teams running agent pipelines today.

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Episoder(43)

Your AI Agent Doesn't Know What Its Code Does

You trust your AI coding agent to understand what its code does once it runs. A new benchmark says that trust is misplaced most of the time.Researchers built SWE-Flux to test it: 480 questions across ...

27 Sep 18min

It Stopped This Time

Your test environment can probably reach more than you think.Gemini is the example this week. In May, during a cybersecurity exercise, it got into the systems of three real companies. It guessed one p...

20 Sep 22min

GPT-6 Astra a generational leap toward AGI

OpenAI called GPT-6 Astra a generational leap toward AGI.That was the headline. Here's what came out days later.Its own evaluation agents had compromised RubyGems infrastructure back in May. Nobody me...

14 Sep 20min

The Harness Problem

This week's biggest AI upgrade wasn't a model. It was someone reviewing code differently.Grok, Gemini, and GPT all shipped new versions in the same seven days. I skimmed the benchmarks. Forgot most of...

23 Aug 22min

The Tokenpocalypse Is Here

JetBrains just said their AI spend went up 10x in six months. Not 10%. 10x.My first guess: engineers burning through Claude Code and Copilot credits.Wrong guess. There's a leaked recording from an int...

9 Aug 23min

Ponytail Activation 0%

Advertised 54%. Measured 15%. Activated 0%JetBrains benchmarked a popular open-source Claude Code skill called Ponytail. It pushes the agent to write less code. The authors has promised 54% less code,...

2 Aug 20min

The Shortest Path Ran Through Someone Else's Servers

Hugging Face spotted something moving through its systems on July 16. It contained the activity without knowing whose agent it was. Five days later, OpenAI confirmed the agent was theirs.Internal cybe...

27 Jul 19min

Three stayed local. One didn't

Four coding CLIs went behind a proxy. Three stayed local. One uploaded the entire workspace.A developer got suspicious about their tools and watched what they actually sent over the network.Grok CLI w...

20 Jul 20min