[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-tim-deschryver-practical-ai-workflow-devs-en":3,"tags-tim-deschryver-practical-ai-workflow-devs-en":37,"related-lang-tim-deschryver-practical-ai-workflow-devs-en":48,"related-posts-tim-deschryver-practical-ai-workflow-devs-en":52,"series-tools-6731f008-d0b5-431c-8b1f-720f947e4875":89},{"id":4,"title":5,"content":6,"summary":7,"source":8,"source_url":9,"author":10,"image_url":11,"keywords":12,"language":18,"translated_content":10,"views":19,"is_premium":20,"created_at":21,"updated_at":21,"cover_image":11,"published_at":22,"rewrite_status":23,"rewrite_error":10,"rewritten_from_id":24,"slug":25,"category":26,"related_article_id":27,"status":28,"google_indexed_at":29,"x_posted_at":10,"tweet_text":10,"title_rewritten_at":10,"title_original":10,"key_takeaways":30,"topic_cluster_id":34,"embedding":35,"is_canonical_seed":36},"6731f008-d0b5-431c-8b1f-720f947e4875","Tim Deschryver’s practical AI workflow for devs","\u003Cp data-speakable=\"summary\">Tim Deschryver says simple project rules make \u003Ca href=\"\u002Fnews\u002Fmistral-cloud-coding-agents-vibe-medium-35-en\">coding agents\u003C\u002Fa> far more useful.\u003C\u002Fp>\u003Cp>Tim Deschryver says he rewrote a project from scratch with \u003Ca href=\"\u002Ftag\u002Fagentic-ai\">agentic AI\u003C\u002Fa> over the last month, and the result was fast enough to matter while still needing human judgment. His point is blunt: you do not need a giant prompt stack to get value from AI in software development.\u003C\u002Fp>\u003Cp>Instead, he treats the \u003Ca href=\"\u002Ftag\u002Fagent\">agent\u003C\u002Fa> like a strong assistant on a cycling team, with the developer still calling the shots on architecture, scope, and quality. That framing matters because it keeps the work practical: the AI writes more code, but the human keeps control of the finish line.\u003C\u002Fp>\u003Ctable>\u003Cthead>\u003Ctr>\u003Cth>Workflow piece\u003C\u002Fth>\u003Cth>What it does\u003C\u002Fth>\u003Cth>Why Tim uses it\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Ctd>AGENTS.md\u003C\u002Ftd>\u003Ctd>Stores project instructions, commands, and conventions\u003C\u002Ftd>\u003Ctd>Keeps every agent request grounded in the same rules\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Skills\u003C\u002Ftd>\u003Ctd>Task-specific markdown guidance for tools and frameworks\u003C\u002Ftd>\u003Ctd>Loads only when needed, which keeps context focused\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>OpenSpec\u003C\u002Ftd>\u003Ctd>Generates proposal.md, design.md, and tasks.md\u003C\u002Ftd>\u003Ctd>Turns feature requests into a clear implementation plan\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003Ch2>He starts with architecture, not prompts\u003C\u002Fh2>\u003Cp>Before letting an agent write code, Tim sets up the project structure himself. His example uses an \u003Ca href=\"https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Faspnet\u002Fcore\u002Fweb-api\u002F?view=aspnetcore-8.0\" target=\"_blank\" rel=\"noopener\">ASP.NET Core API\u003C\u002Fa> backend, an \u003Ca href=\"https:\u002F\u002Fangular.dev\" target=\"_blank\" rel=\"noopener\">Angular\u003C\u002Fa> frontend, and \u003Ca href=\"https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fdotnet\u002Faspire\u002Fget-started\u002Faspire-overview\" target=\"_blank\" rel=\"noopener\">.NET Aspire\u003C\u002Fa> to orchestrate the system.\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778553048153-0mhc.png\" alt=\"Tim Deschryver’s practical AI workflow for devs\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>That setup choice is doing a lot of work. By deciding on vertical slices, clear boundaries, and a front end built around Angular Signals, he gives the agent a target it can follow instead of a blank page it can wander across.\u003C\u002Fp>\u003Cp>The practical lesson is simple: if your codebase is already shaped well, the agent has less room to produce weird output. Tim even says he prefers slices because they make it easier to rewrite or delete code when requirements change, which is exactly the kind of pressure software teams face after the first release.\u003C\u002Fp>\u003Cul>\u003Cli>Backend: ASP.NET Core API\u003C\u002Fli>\u003Cli>Frontend: Angular with Signal APIs\u003C\u002Fli>\u003Cli>Orchestration: .NET Aspire\u003C\u002Fli>\u003Cli>Architecture style: vertical slices\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>AGENTS.md is the first file he wants in the repo\u003C\u002Fh2>\u003Cp>Tim treats \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fagents.md\" target=\"_blank\" rel=\"noopener\">AGENTS.md\u003C\u002Fa> as the default instruction sheet for the coding agent. The file carries project rules, build and test commands, structure notes, and anything else the agent needs every time it works in the repository.\u003C\u002Fp>\u003Cp>He also points out that different tools use different names. \u003Ca href=\"\u002Ftag\u002Fgithub-copilot\">GitHub Copilot\u003C\u002Fa> may use instructions.md, Claude uses CLAUDE.md, and \u003Ca href=\"https:\u002F\u002Fdocs.anthropic.com\u002Fen\u002Fdocs\u002Fclaude-code\" target=\"_blank\" rel=\"noopener\">Claude Code\u003C\u002Fa> can read a referenced AGENTS.md file through a symlink or @AGENTS.md. The naming detail matters less than the habit: put the rules in one place, keep them current, and let every request start from the same baseline.\u003C\u002Fp>\u003Cblockquote>“The use of the term dates back to 1911, although such riders had existed before then.”\u003C\u002Fblockquote>\u003Cp>That quote is from Tim’s cycling explanation of a domestique, and it fits the article’s main idea. The developer is still the team leader, while the agent does the hard pulling in the background.\u003C\u002Fp>\u003Cp>He also recommends putting a Mermaid database diagram into AGENTS.md when the data model gets complex. That is a smart move for \u003Ca href=\"\u002Fnews\u002Fgithub-agentic-workflows-ai-github-actions-en\">agentic workflows\u003C\u002Fa> because the model can read a dense diagram better than a human skimming a wall of text, and the file can be updated after each new concept in the same session.\u003C\u002Fp>\u003Cul>\u003Cli>AGENTS.md is always in context\u003C\u002Fli>\u003Cli>It can include commands, conventions, and architecture notes\u003C\u002Fli>\u003Cli>Mermaid diagrams help describe data models\u003C\u002Fli>\u003Cli>Tim updates it whenever the project changes\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>Skills keep the context smaller and the output tighter\u003C\u002Fh2>\u003Cp>Tim’s next layer is \u003Ca href=\"https:\u002F\u002Fskills.sh\" target=\"_blank\" rel=\"noopener\">skills\u003C\u002Fa>, which are markdown files that can also include scripts. Unlike AGENTS.md, skills are pulled in only when the agent thinks they are relevant. That makes them better for focused tasks like creating a component, writing a test, or generating documentation.\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778553063529-v21e.png\" alt=\"Tim Deschryver’s practical AI workflow for devs\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>He uses official skills for \u003Ca href=\"https:\u002F\u002Fangular.dev\" target=\"_blank\" rel=\"noopener\">Angular\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fdotnet\u002F","Tim Deschryver shows how AGENTS.md, skills, and specs make coding agents faster and more 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