Prompt engineering is dead.
Anthropic recently released the real playbook for building AI agents that actually work.
It’s a 30+ page deep dive called The Complete Guide to Building Skills for Claude and it quietly shifts the conversation from “prompt engineering” to real execution design.
Here’s the big idea:
A Skill isn’t just a prompt.
It’s a structured system.
You package instructions inside a SKILL .md file, optionally add scripts, references, and assets, and teach Claude a repeatable workflow once instead of re-explaining it every chat.
But the real unlock is something they call progressive disclosure.
Instead of dumping everything into context:
• A lightweight YAML frontmatter tells Claude when to use the skill
• Full instructions load only when relevant
• Extra files are accessed only if needed
Less context bloat. More precision.
They also introduce a powerful analogy:
MCP gives Claude the kitchen.
Skills give it the recipe.
Without skills: users connect tools and don’t know what to do next.
With skills: workflows trigger automatically, best practices are embedded, API calls become consistent.
They outline 3 major patterns:
1) Document & asset creation
2) Workflow automation
3) MCP enhancement
And they emphasize something most builders ignore: testing.
Trigger accuracy.
Tool call efficiency.
Failure rate.
Token usage.
This isn’t about clever wording.
It’s about designing an execution layer on top of LLMs.
Skills work across Claude, Claude Code, and the API. Build once, deploy everywhere.
The era of “just write a better prompt” is ending.
Anthropic just handed everyone a blueprint for turning chat into infrastructure.
Download the guide here: https://t.co/Bf3j0GFRGu
@nodeguardians Hello.
Thanks for your site.
I had trouble verifying tests on the platform. Everiginhgs fine locally but "Unable to parse test entry" on website. Any idea? (github: scastrec)
Thanks
@MathieuEon Bonjour Mathieu,
J'ai vu votre recherche de freelance sur Linkedin: https://t.co/5JsljAV9XD
Si mon profil vous intéresse, n'hésitez pas à me contacter
https://t.co/7ZkjZo03H4
𝗧𝗼𝗽 𝟭𝟬 𝗖𝗹𝗲𝗮𝗻 𝗖𝗼𝗱𝗲 𝗥𝘂𝗹𝗲𝘀
In the probably most famous book of software engineering, "Clean Code," Uncle Bob Martin defined some guidances and rules we need to follow, especially when we're inexperienced. With more experience, some of the rules can be broken.
Here are the most important rules you need to follow.
🧵👇
Déjà 48 inscrits pour la soirée @FinistDevs jeudi🚀! Quelques places encore disponibles. Venez rencontrer la communauté dev brestoise, écouter @joyful_code sur l'accessibilité et m'écouter parler WASM sur K8s.
C'est ce jeudi, 18h chez @ZenikaBrest👉 https://t.co/ZOIVWwAlNP
Merci pour ce retour sur notre conférence 🙂, retrouvez le projet #TOCK ici https://t.co/1NBBUlzxR7
Notre modèle de fondation Open Sourcé aujourd'hui sur @huggingface https://t.co/xVrOSnwgUE cc @cmarkea
50% of StackOverflow traffic is gone!
Look at the attached chart. It tells a scary story that will not be limited to StackOverflow.
Right now, detecting AI-generated content is impossible.
Last week, OpenAI shut down the tool they created for this purpose. They launched it in January, and it's dead today, less than seven months later.
Their statement: "The AI classifier is no longer available due to its low rate of accuracy."
I'm not surprised about any of these two events.
I don't remember the last time I visited StackOverflow. Why would I when tools like Copilot and ChatGPT answer my questions faster without making me feel bad for asking?
And I'm even less surprised about OpenAI killing their tool: Many believe detecting AI-generated text is impossible. I'm one of them.
Here's what OpenAI had to say about this:
"We are (...) currently researching more effective provenance techniques for text, and have made a commitment to develop and deploy mechanisms that enable users to understand if audio or visual content is AI-generated."
Notice how they differentiate text from audio and visual content. For the latter, they seem confident they'll find a way to recognize humans from AI. For text, they are not and are word-salad'ing us with a vague "researching more effective provenance techniques."
StackOverflow famously banned any AI-generated answers from the site.
That's the wrong move.
Instead, we need to find a way where human and AI-generated content coexist and benefit from each other. There's no putting the genie back in the bottle, so how can we get the most out of it?
Do you think StackOverflow will survive? What can they do to fend off what seems to be a life-threatening event?
L’ambiance actuelle me pousse à une petite réflexion.
J’ai 34 ans. Je bosse depuis 12 ans. Je suis idéologiquement « Janco-compatible » (sauf sur ses saucisse sur les nouvelles techno / internet)
4. Until 2013 alone, nuclear power is estimated to have saved 1.8 million lives through reduced air pollution from fossil fuels.
Source: https://t.co/awHmRMpKP9
Some people said that closed APIs were winning...
but we will never give up the fight for open source AI ⚔️⚔️
Today is a big day as we launch the first open source alternative to ChatGPT:
HuggingChat 💬
Powered by Open Assistant's latest model – the best open source chat model right now – and @huggingface Inference API.
Try it out now:
https://t.co/npBD1NRvQL
Vous aimez #PeerTube ? On a besoin d'aide !
L'ami @davduf (épaulé de @OctopuceFR) nous propose de faire un test de charge du direct... pour voir comment ça tient quand on est plein.
RDV vendredi 30/12, 10h30 pour faire péter les scores et les serveurs !
https://t.co/lffzuWpjGz