Artificial Intelligence

Where to invest: a maturity model for your team

A 5-part series — Part 5/5 The most common mistake isn’t picking the wrong discipline. It’s investing in a layer above where your team actually sits. People want to build a sophisticated harness when they don’t even have a test bench for their prompts. They stack autonomous agents on foundations that are taking on water.…

Artificial Intelligence

Harness engineering: the model is the smallest part

A 5-part series — Part 4/5 – Harness engineering When the Claude Code source leaked in late March 2026, people could finally measure something practitioners had suspected without proof: across roughly 512,000 lines of TypeScript, the model interaction itself is a tiny fraction. Everything else, the vast majority, is the harness. That sums up the…

Artificial Intelligence

Context engineering: the window is a scarce resource

A 5-part series — Part 3/5 Here’s the most counterintuitive idea in the whole series: giving a model more information can make it worse. It’s tempting to picture the context window as a big bag where you cram everything that might help. In practice it’s a budget. Every token you add spends another, and past…

Artificial Intelligence

Prompt engineering: what still holds up in 2026

A 5-part series — Part 2/5 We buried prompt engineering a little too fast. The discipline isn’t dead, it’s been demoted. It now sits at the innermost layer of the diagram from Part 1: how you phrase a request, inside a single call. That’s small. It’s also the first place everything can go wrong. In…

Artificial Intelligence

Prompt, context, harness: the three ages of LLM engineering

A 5-part series — Part 1/5 Three years ago, knowing how to “talk” to a model was a rare and slightly magical skill. People traded screenshots of prompts that worked and passed around phrasings like cooking recipes. Andrej Karpathy summed up the era in a line that stuck: the hottest new programming language was English.…

Artificial Intelligence

Prompt, Context, Harness : les trois âges de l’ingénierie des LLM

Série en 5 épisodes — Épisode 1/5 Il y a trois ans, savoir « parler » à un modèle était une compétence rare et un peu magique. On s’échangeait des captures d’écran de prompts qui marchaient, on se refilait des tournures comme des recettes de cuisine. Andrej Karpathy a résumé l’époque d’une formule devenue culte…

Artificial Intelligence

Claude Fable 5 : Le premier modèle « Au-dessus d’Opus » que vous pouvez réellement utiliser aujourd’hui

Anthropic a lancé Claude Fable 5 hier, et je veux être prudent sur la façon dont j’en parle, car la ferveur marketing entourant les lancements de modèles est désormais fixée en permanence sur « cela change tout ». La plupart du temps, ce n’est pas le cas. Celui-ci a plus de chances d’avoir une réelle…

Artificial Intelligence

Claude Fable 5: The First “Above-Opus” Model You Can Actually Use Today

Anthropic shipped Claude Fable 5 yesterday, and I want to be careful about how I talk about it, because the marketing temperature on model launches is now permanently set to “this changes everything.” Most of the time it doesn’t. This one is closer to actually mattering, and not entirely for the reasons the launch post…

Artificial Intelligence

Beyond the Benchmark: 5 Surprising Truths About Anthropic’s New Claude Opus 4.8

Introduction: The Post-Launch Reality Check In the hyper-accelerated cadence of the AI industry, “new” is beginning to feel synonymous with “incremental.” With Claude Opus 4.7 having arrived only a month prior, many developers initially greeted the May 28, 2026, release of Claude Opus 4.8 with a measure of release fatigue. At first glance, another flagship…