[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-8e760cba47215e0d-customize-vs-code-copilot-agents-for-repeatable-wo-summary":3,"summaries-facets-categories":379,"summary-related-8e760cba47215e0d-customize-vs-code-copilot-agents-for-repeatable-wo-summary":3948},{"id":4,"title":5,"ai":6,"body":13,"categories":329,"created_at":331,"date_modified":331,"description":321,"extension":332,"faq":331,"featured":333,"kicker_label":331,"meta":334,"navigation":360,"path":361,"published_at":362,"question":331,"scraped_at":363,"seo":364,"sitemap":365,"source_id":366,"source_name":367,"source_type":368,"source_url":369,"stem":370,"tags":371,"thumbnail_url":331,"tldr":376,"tweet":331,"unknown_tags":377,"__hash__":378},"summaries\u002Fsummaries\u002F8e760cba47215e0d-customize-vs-code-copilot-agents-for-repeatable-wo-summary.md","Customize VS Code Copilot Agents for Repeatable Workflows",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","x-ai\u002Fgrok-4.1-fast",8619,2616,40938,0.0030093,{"type":14,"value":15,"toc":320},"minimark",[16,21,30,37,43,49,53,64,70,101,107,113,118,122,129,134,151,156,170,180,190,195,199,206,211,237,247,269,275,280,284],[17,18,20],"h2",{"id":19},"access-and-manage-all-customizations-from-one-ui","Access and Manage All Customizations from One UI",[22,23,24,25,29],"p",{},"VS Code's new Customization UI centralizes management of AI behaviors for Copilot Chat, accessible via Command Palette (\"chat customizations\") or the gear icon in Chat view. This dashboard lists built-in and custom items like agents, skills, instructions, hooks, and prompts. Click any to view\u002Fedit details, generate new ones, or delete. Generate via UI buttons or Chat slash commands like ",[26,27,28],"code",{},"\u002Fcreate instructions","—Copilot drafts the file based on your description, scopes it to user\u002Fworkspace, and auto-applies to relevant files (e.g., HTML\u002FCSS for accessibility rules).",[22,31,32,36],{},[33,34,35],"strong",{},"Key principle",": Customizations persist across sessions, reducing repetition. Without them, every prompt requires re-explaining context, styles, or rules, leading to inconsistent results and trial-and-error. With them, define once (e.g., \"Apply SOLID principles to all refactors\") and Copilot enforces automatically, confirming application in responses.",[22,38,39,42],{},[33,40,41],{},"Common mistake",": Scattering files across folders—instead, use the UI for discovery. Test by reloading VS Code after creation. For teams, workspace-level instructions ensure consistent naming, formatting, and architecture, cutting review time.",[22,44,45,48],{},[33,46,47],{},"Quote",": \"Customization changes that. It lets you define behavior once, reuse it everywhere, and get consistent outputs.\"",[17,50,52],{"id":51},"enforce-rules-and-styles-with-custom-instructions","Enforce Rules and Styles with Custom Instructions",[22,54,55,56,59,60,63],{},"Custom instructions are Markdown files acting as a \"rule book\" for Copilot, applied automatically to matching file types (defined in ",[26,57,58],{},"apply_to"," metadata). Structure: metadata (description, glob patterns like ",[26,61,62],{},"**\u002F*.js","), then bullet-point rules.",[22,65,66,69],{},[33,67,68],{},"Steps to create",":",[71,72,73,80,95,98],"ol",{},[74,75,76,77,79],"li",{},"In Chat: ",[26,78,28],{}," + description (e.g., \"Ensure UI meets WCAG standards, confirm in chat\").",[74,81,82,83,86,87,90,91,94],{},"Copilot generates ",[26,84,85],{},".instructions.md"," (user: ",[26,88,89],{},"~\u002F.vscode-customizations\u002F","; workspace: ",[26,92,93],{},".vscode-customizations\u002F",").",[74,96,97],{},"Review\u002Fedit in UI: Add confirmation phrases like \"Confirmation: Applied WCAG standards.\"",[74,99,100],{},"Test: Ask Copilot to edit code (e.g., \"Refactor this script\" or \"Make UI 80s arcade style\")—it analyzes, applies rules, and confirms.",[22,102,103,106],{},[33,104,105],{},"Example before\u002Fafter",": Original calculator JS lacked SOLID separation; post-refactor: Single Responsibility (separate concerns), confirmed in chat. UI update auto-added ARIA labels, alt text for WCAG.",[22,108,109,112],{},[33,110,111],{},"Quality criteria",": Instructions must be specific (e.g., \"Use semantic HTML, keyboard nav\") not vague; include triggers (\"when generating\u002Frefactoring UI\") and confirmation for verification. Benefits scale to teams: Repo-wide consistency without manual reviews.",[22,114,115,117],{},[33,116,47],{},": \"Imagine every developer in the repo having Copilot follow the same coding conventions... This saves a lot of time.\"",[17,119,121],{"id":120},"specialize-agents-with-skills-and-custom-agents","Specialize Agents with Skills and Custom Agents",[22,123,124,125,128],{},"Agent skills are folders (",[26,126,127],{},"skill.md"," + resources\u002Fscripts) for domain-specific tasks, loadable across Copilot tools (VS Code, CLI). Custom agents build on skills, assigning personas (e.g., \"Security Reviewer\") with tools\u002Finstructions.",[22,130,131,69],{},[33,132,133],{},"Build a skill",[71,135,136,142,148],{},[74,137,138,141],{},[26,139,140],{},"\u002Fcreate skill"," + task (e.g., \"Update README on feature add, confirm in chat\").",[74,143,144,145,147],{},"Copilot creates folder with ",[26,146,127],{}," (description, related skills, rules like \"Extract feature from convo, append to README features section\").",[74,149,150],{},"Test: Add feature (e.g., \"Add dark\u002Flight jingle\")—skill auto-updates README.",[22,152,153,69],{},[33,154,155],{},"Build custom agent",[71,157,158,161,167],{},[74,159,160],{},"Ask Copilot for prompt: \"Suggest custom agent for arcade calculator.\"",[74,162,163,166],{},[26,164,165],{},"\u002Fcreate agent"," + persona (e.g., \"Arcade App Builder: Knows retro aesthetics, sound effects, HTML\u002FJS\u002FCSS stack\").",[74,168,169],{},"Select from Chat dropdown (@agentname); it uses codebase knowledge for tasks like \"Build tip calculator.\"",[22,171,172,175,176,179],{},[33,173,174],{},"Example",": Security agent reviews JS for vulns (categorizes low\u002Fmedium\u002Fhigh); Arcade agent clones styles\u002Fsounds to new app. ",[33,177,178],{},"Trade-off",": Domain-focused (great for projects) but overkill for one-offs.",[22,181,182,185,186,189],{},[33,183,184],{},"Mistake to avoid",": Not scoping (user vs. workspace)—use workspace for teams. ",[33,187,188],{},"Quality",": Clear description, minimal tools, architecture awareness.",[22,191,192,194],{},[33,193,47],{},": \"Custom agents enable you to configure the AI to adopt different personas tailored to specific development roles and tasks.\"",[17,196,198],{"id":197},"automate-repetitive-tasks-with-hooks-and-prompt-files","Automate Repetitive Tasks with Hooks and Prompt Files",[22,200,201,202,205],{},"Hooks run shell commands at agent lifecycle events (e.g., ",[26,203,204],{},"post_tool_use","). Prompt files are reusable templates.",[22,207,208,69],{},[33,209,210],{},"Create hook",[71,212,213,216,234],{},[74,214,215],{},"UI > Generate hook + spec (e.g., \"Run Prettier on post_tool_use\").",[74,217,218,219,222,223,226,227,230,231,94],{},"Edits ",[26,220,221],{},".vscode-customizations\u002Fhooks\u002Fprettier.hook.json",": Define ",[26,224,225],{},"events"," (array), ",[26,228,229],{},"command"," (e.g., ",[26,232,233],{},"npx prettier --write .",[74,235,236],{},"Reload VS Code; test: Edit README—hook auto-formats.",[22,238,239,242,243,246],{},[33,240,241],{},"Prompt files",": ",[26,244,245],{},"\u002Fcreate prompt"," for templates (e.g., code review); reference in skills.",[22,248,249,252,253,242,256,259,260,259,263,265,266,268],{},[33,250,251],{},"Principle",": Automate validation (security, formatting) without manual invocation. ",[33,254,255],{},"Events",[26,257,258],{},"start_session",", ",[26,261,262],{},"user_prompt_submit",[26,264,204],{},". ",[33,267,178],{},": Shell reliance—test commands; no timeout for long runs.",[22,270,271,274],{},[33,272,273],{},"Full workflow example",": Build app from scratch—use instructions for styles, agent for features, hook for formatting, skill for docs. Results: Arcade calculator with themes, sounds, WCAG, auto-README, formatted.",[22,276,277,279],{},[33,278,47],{},": \"Hooks enable you to execute custom shell commands at life cycle points during agent sessions... automate workflows, enforce security policies.\"",[17,281,283],{"id":282},"key-takeaways","Key Takeaways",[285,286,287,290,296,299,305,308,311,314,317],"ul",{},[74,288,289],{},"Open Customization UI via gear or \"chat customizations\" to manage everything in one place.",[74,291,292,293,295],{},"Start with custom instructions for persistent rules: ",[26,294,28],{}," + glob patterns + confirmations.",[74,297,298],{},"Use agent skills for tasks (e.g., README updates) and custom agents for personas—select via @dropdown.",[74,300,301,302,304],{},"Automate with hooks on lifecycle events like ",[26,303,204],{}," for formatters; reload to activate.",[74,306,307],{},"Generate via Copilot slash commands to skip manual writing; always review\u002Fedit.",[74,309,310],{},"Scope user\u002Fworkspace for personal\u002Fteam use; test on real edits\u002Frefactors.",[74,312,313],{},"Check Awesome Copilot repo for community examples.",[74,315,316],{},"Avoid repetition: Customizations turn Copilot into a context-aware system.",[74,318,319],{},"For apps: Chain features—instructions for compliance, agents for domain logic, hooks for polish.",{"title":321,"searchDepth":322,"depth":322,"links":323},"",2,[324,325,326,327,328],{"id":19,"depth":322,"text":20},{"id":51,"depth":322,"text":52},{"id":120,"depth":322,"text":121},{"id":197,"depth":322,"text":198},{"id":282,"depth":322,"text":283},[330],"AI & LLMs",null,"md",false,{"content_references":335,"triage":355},[336,341,345,348,352],{"type":337,"title":338,"url":339,"context":340},"other","VS Code Customization Overview","https:\u002F\u002Faka.ms\u002FVSCL-Cust-Overview","mentioned",{"type":337,"title":342,"url":343,"context":344},"Awesome Copilot","https:\u002F\u002Faka.ms\u002FAwesomeGC","recommended",{"type":337,"title":346,"url":347,"context":340},"VS Code Learn Playlist","https:\u002F\u002Faka.ms\u002Fvsc-learn",{"type":349,"title":350,"url":351,"context":340},"tool","Custom Instructions Docs","https:\u002F\u002Faka.ms\u002Fcustom-instructions",{"type":349,"title":353,"url":354,"context":340},"Custom Agent Skills","https:\u002F\u002Faka.ms\u002Fcustom-agent-skills",{"relevance":356,"novelty":357,"quality":357,"actionability":356,"composite":358,"reasoning":359},5,4,4.55,"Category: AI & LLMs. The article provides a detailed guide on customizing VS Code Copilot agents, addressing practical applications for developers looking to streamline their workflows. It includes specific steps for creating custom instructions, making it immediately actionable for the audience.",true,"\u002Fsummaries\u002F8e760cba47215e0d-customize-vs-code-copilot-agents-for-repeatable-wo-summary","2026-05-06 14:00:14","2026-05-06 16:10:56",{"title":5,"description":321},{"loc":361},"ab488a3c329a1bb7","Visual Studio Code","article","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=9PUt81AjfmA","summaries\u002F8e760cba47215e0d-customize-vs-code-copilot-agents-for-repeatable-wo-summary",[372,373,374,375],"agents","prompt-engineering","ai-tools","dev-productivity","Use VS Code's Customization UI to build custom instructions, agent skills, agents, hooks, and prompt files—define behaviors once for consistent AI outputs across chats, teams, and projects without 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Keys to Agent-First Dev in VS Code",{"provider":7,"model":8,"input_tokens":3953,"output_tokens":3954,"processing_time_ms":3955,"cost_usd":3956},5479,1525,19888,0.00139105,{"type":14,"value":3958,"toc":4010},[3959,3963,3970,3973,3977,3980,3983,3987,3990,3993,3997,4000,4004,4007],[17,3960,3962],{"id":3961},"the-5-part-formula-for-reliable-agent-results","The 5-Part Formula for Reliable Agent Results",[22,3964,3965,3966,3969],{},"Agents aren't magic—they follow a formula: ",[33,3967,3968],{},"harness + model + prompts + tools + context",". Tune these to avoid vague outputs and achieve tasks matching your codebase standards. The harness (VS Code's GitHub Copilot Chat) wires the model to tools, files, and actions, like a car's wiring distributing engine power. Without specifics, agents fail; with this setup, they handle full software development lifecycles.",[22,3971,3972],{},"Start sessions in Copilot Chat: select a model (e.g., Sonnet, Codex), set thinking effort (low for boilerplate, medium for refactoring, high for architecture\u002Fdebugging—high balances speed and reasoning), craft detailed-but-not-overwhelming prompts, enable relevant tools, and add context.",[17,3974,3976],{"id":3975},"model-and-effort-selection-drives-reasoning-quality","Model and Effort Selection Drives Reasoning Quality",[22,3978,3979],{},"Choose from developer-preferred models in Copilot Chat (e.g., Sonnet at high effort as default). Low effort suits quick tasks like formatting; medium handles straightforward refactors; high tackles complex architecture or debugging. This trades speed for depth—use high for non-trivial work to get accurate code generation and reasoning.",[22,3981,3982],{},"Prompts must specify tasks clearly: include details without minutiae, e.g., \"create to-dos and run Z shell command\" triggers tools automatically if enabled.",[17,3984,3986],{"id":3985},"curate-tools-to-match-your-task-avoid-overload","Curate Tools to Match Your Task, Avoid Overload",[22,3988,3989],{},"Agents execute via 100+ built-in and extension tools (e.g., from 152 to 55 by disabling irrelevant ones like Azure, Bicep, Mermaid). Key categories: delegate to sub-agents, browser interaction, file edits\u002Freads\u002Fsearches, terminal commands, to-do management, VS Code features, web search.",[22,3991,3992],{},"Granular control: enable only essentials (e.g., to-dos icon for task lists, terminal icon for shell runs). Over-enabling bloats sessions; under-enabling blocks actions—review tool picker per task. Demo: agent created to-dos and ran terminal commands because both were active.",[17,3994,3996],{"id":3995},"ground-agents-with-codebase-context","Ground Agents with Codebase Context",[22,3998,3999],{},"Models lack niche expertise—provide files\u002Ffolders via + icon (GitHub repos, MCP resources) or #filename in prompts. Agents auto-read directories (e.g., scanned project dir), incorporating specifics over general training data. This yields codebase-tailored results, e.g., reading dirs before commands.",[17,4001,4003],{"id":4002},"vs-code-layout-tweaks-for-agent-efficiency","VS Code Layout Tweaks for Agent Efficiency",[22,4005,4006],{},"Customize for visibility: right-click Explorer to swap primary sidebar (left\u002Fright), set activity bar to top (right-click > Activity Bar Position > Top). These position Copilot Chat, tools, and outputs optimally—default is left activity bar, but top aids multi-panel agent monitoring.",[22,4008,4009],{},"Next: approval levels (allow\u002Fskip commands) prevent unchecked runs.",{"title":321,"searchDepth":322,"depth":322,"links":4011},[4012,4013,4014,4015,4016],{"id":3961,"depth":322,"text":3962},{"id":3975,"depth":322,"text":3976},{"id":3985,"depth":322,"text":3986},{"id":3995,"depth":322,"text":3996},{"id":4002,"depth":322,"text":4003},[330],"In this video Gwyneth introduces and demos the 5 concepts you need to understand in order to kick off your first agent session! \n\nFollow along in this series to learn what the agent is doing, how to review changes, approval levels, different reasoning effort levels and build your first app! \n\n🔎 Chapters:\n00:00 Introduction to the Agent-First Development series\n00:55 Customizing your terminal\n01:50 The 5 concepts you need to understand to get started\n02:30 Harness\n03:30 Model\n04:28 Prompts\n05:17 Tools\n08:00 Context\n09:17 In Summary\n09:42 What's Next \n\n🎙️ Featuring: Gwyneth Peña-Siguenza (https:\u002F\u002Fx.com\u002Fmadebygps)\n\n📲 Follow VS Code:\nX: https:\u002F\u002Fx.com\u002Fcode\nBluesky: https:\u002F\u002Fbsky.app\u002Fprofile\u002Fvscode.dev\nYouTube:    \u002F code  \nLinkedIn:   \u002F 104107263  \nGitHub: https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fvscode\n\n#vscode #agents",{},"\u002Fsummaries\u002Fdca2dd1dce3d4b74-5-keys-to-agent-first-dev-in-vs-code-summary","2026-04-06 16:15:13","2026-04-06 16:40:13",{"title":3951,"description":4018},{"loc":4020},"dca2dd1dce3d4b74","video","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=uu4sf8z9n8c","summaries\u002Fdca2dd1dce3d4b74-5-keys-to-agent-first-dev-in-vs-code-summary",[372,373,374,375],"Master harness, model, prompts, tools, and context to run precise AI agent sessions in VS Code with GitHub Copilot, turning general models into codebase-specific developers.",[375],"K6ovWSdjurE_F6LFE4tVf7qEiKrlSF1n3ZilZbc-9Gs",{"id":4034,"title":4035,"ai":4036,"body":4041,"categories":4278,"created_at":331,"date_modified":331,"description":4279,"extension":332,"faq":331,"featured":333,"kicker_label":331,"meta":4280,"navigation":360,"path":4281,"published_at":4282,"question":331,"scraped_at":4283,"seo":4284,"sitemap":4285,"source_id":4286,"source_name":4287,"source_type":4026,"source_url":4288,"stem":4289,"tags":4290,"thumbnail_url":331,"tldr":4291,"tweet":331,"unknown_tags":4292,"__hash__":4293},"summaries\u002Fsummaries\u002F2f1b198f31045d7f-optimize-claude-md-to-10x-claude-code-efficiency-summary.md","Optimize Claude.md to 10x Claude Code Efficiency",{"provider":7,"model":8,"input_tokens":4037,"output_tokens":4038,"processing_time_ms":4039,"cost_usd":4040},8263,2083,15329,0.00240325,{"type":14,"value":4042,"toc":4270},[4043,4047,4050,4081,4084,4087,4091,4102,4116,4119,4122,4126,4129,4155,4158,4161,4164,4168,4171,4197,4200,4203,4207,4227,4230,4233,4236,4238,4267],[17,4044,4046],{"id":4045},"claudemds-four-core-functions-unlock-reliable-ai-agency","Claude.md's Four Core Functions Unlock Reliable AI Agency",[22,4048,4049],{},"Claude.md acts as the foundational system prompt in Claude Code (via VS Code extension or desktop app), injected at the top of every session. It transforms Claude from a generic coder into a specialized agent by serving four interconnected roles:",[71,4051,4052,4058,4064,4075],{},[74,4053,4054,4057],{},[33,4055,4056],{},"Knowledge Compression",": Summarizes your entire workspace into a succinct overview, avoiding token waste from Claude re-reading every file. Instead of scanning folders file-by-file, Claude references the claude.md summary for bird's-eye reasoning. Example: \"Reference the file from two weeks ago on X?\" Claude checks claude.md instantly.",[74,4059,4060,4063],{},[33,4061,4062],{},"User Preferences and Conventions",": Override defaults with your workflow tweaks. Specify file path formats (e.g., absolute paths for easy clicking), coding styles (OOP vs. functional, Rust over Python), or behaviors like \"Always read API docs first—past attempts without them wasted tokens and looped endlessly.\"",[74,4065,4066,4069,4070,4074],{},[33,4067,4068],{},"Capability Declarations",": Explicitly list what Claude ",[4071,4072,4073],"em",{},"can"," do to bypass hesitation. Claude often underestimates its agency, suggesting manual steps or overestimating timelines (e.g., \"This takes 3 months\" when it could build in seconds). Counter this: \"You can autonomously execute 10-15 minute plans, call APIs\u002Fdatabases, use browsers, scrape sites like LaserOver.\" This prevents loops like \"I don't have a way to do this—build from scratch?\"",[74,4076,4077,4080],{},[33,4078,4079],{},"Log of Failures and Successes",": Carve out 80% of the solution space by documenting what worked\u002Ffailed. Each project hard-wins knowledge (tokens + time); log it to focus future efforts on the viable 20%. Viewed mathematically: Shrink the vast possibility space to planetary \"habitable zones\" of proven paths.",[22,4082,4083],{},"\"A claude.md is... knowledge compression... your own preferences... a declaration of capabilities... a log of failures and successes.\"",[22,4085,4086],{},"These functions compound: Compression saves tokens, prefs align outputs, capabilities boost agency, logs prune errors—yielding tighter workspaces where prompts like \"Scrape LaserOver\" execute flawlessly.",[17,4088,4090],{"id":4089},"global-vs-local-scopes-for-scalable-prompt-engineering","Global vs. Local Scopes for Scalable Prompt Engineering",[22,4092,4093,4094,4097,4098,4101],{},"Claude Code loads prompts hierarchically: ",[33,4095,4096],{},"Global claude.md"," (root-level file) injects universally across all workspaces; ",[33,4099,4100],{},"Local .claude\u002Fclaude.md"," (project-specific) adds workspace details.",[285,4103,4104,4110],{},[74,4105,4106,4109],{},[33,4107,4108],{},"Global (High-Level Reasoning)",": Personal context, beliefs, strategies. Include who you are (\"I'm Nick Saraev, generating $4M\u002Fyear profit with Claude agents\"), reasoning frameworks you grok, token-saving rules (\"Load Chrome DevTools MCP for JS-heavy API docs\"), and evergreen capabilities (\"You handle browser automation autonomously\").",[74,4111,4112,4115],{},[33,4113,4114],{},"Local (Low-Level Knowledge)",": Workspace summary (what's where, why built), project-specific prefs (e.g., paste full GoHighLevel API docs to avoid external calls), and tools like .claude\u002Finsights for auto-summaries.",[22,4117,4118],{},"Strategy: Global for cross-project consistency (e.g., always OOP in Rust); local for repo nuances. Both minimize tool calls, latency, and inaccuracies.",[22,4120,4121],{},"\"Global: high-level reasoning, personal beliefs. Local: low-level knowledge like workspace compression.\"",[17,4123,4125],{"id":4124},"local-workflow-iterative-feature-development-loop","Local Workflow: Iterative Feature Development Loop",[22,4127,4128],{},"For any task (code feature, email summary, website design), run this loop to evolve local claude.md dynamically:",[71,4130,4131,4137,4143,4149],{},[74,4132,4133,4136],{},[33,4134,4135],{},"Plan the Feature",": Loose definition—any deliverable.",[74,4138,4139,4142],{},[33,4140,4141],{},"Instantiate",": Claude builds\u002Fexecutes.",[74,4144,4145,4148],{},[33,4146,4147],{},"Compile Learnings",": Extract failures (rabbit holes, token wastes) and successes into high-density bullets.",[74,4150,4151,4154],{},[33,4152,4153],{},"Update Local claude.md",": Inject compressed insights.",[22,4156,4157],{},"Repeat: First loop takes full time (X); second shaves 10% (0.9X) by pruning search space; iterates to human-speed dev. Prerequisites: Basic Claude Code setup (VS Code extension from Anthropic, login).",[22,4159,4160],{},"Common Mistake: Static prompts—Claude restarts from scratch, wasting tokens. Quality Check: Does next plan reference prior learnings without re-explaining?",[22,4162,4163],{},"\"Plan → Instantiate (fail\u002Fsucceed) → Compile learnings → Update claude.md. Time drops: X → 0.9X → 0.8X...\"",[17,4165,4167],{"id":4166},"global-workflow-cross-project-insight-distillation","Global Workflow: Cross-Project Insight Distillation",[22,4169,4170],{},"Elevate local wins to global after 100+ runs:",[71,4172,4173,4179,4185,4191],{},[74,4174,4175,4178],{},[33,4176,4177],{},"Pull \u002Finsights",": Auto-compile consistent patterns (e.g., \"Claude always skips docs across projects\").",[74,4180,4181,4184],{},[33,4182,4183],{},"Manual Review",": Human-in-loop critical—AI chains compound errors (0.9^3 = 73% accuracy). Scrutinize for global applicability.",[74,4186,4187,4190],{},[33,4188,4189],{},"Add High-ROI Bullets",": Token-efficient prefs\u002Fconventions.",[74,4192,4193,4196],{},[33,4194,4195],{},"Update Global claude.md",": Propagate to all future work.",[22,4198,4199],{},"Infinity Loop: Local → Global → Local. Spend human time here—impacts every session.",[22,4201,4202],{},"\"After hundreds of runs... \u002Finsights compiles global trends. Manually review: More AI steps = compounded probabilities of failure.\"",[17,4204,4206],{"id":4205},"avoiding-pitfalls-in-advanced-claude-code","Avoiding Pitfalls in Advanced Claude Code",[285,4208,4209,4215,4221],{},[74,4210,4211,4214],{},[33,4212,4213],{},"Performance Fluctuations",": Claude varies; declare capabilities firmly to enforce agency.",[74,4216,4217,4220],{},[33,4218,4219],{},"Token Bloat",": Compress knowledge, log failures early.",[74,4222,4223,4226],{},[33,4224,4225],{},"Agency Gaps",": Always remind \"You build this autonomously—no manual CLI prompts.\"",[22,4228,4229],{},"Before: Vague prompt → 20k tokens, stumbles. After: Optimized claude.md → Instant execution.",[22,4231,4232],{},"Tools: VS Code + Claude extension (anti-gravity IDE mentioned), desktop app for mobile\u002Fdev flexibility. Practice: Start new project (e.g., VS Code example folder), generate initial claude.md via workflow.",[22,4234,4235],{},"\"Claude lacks agency... 'How long to build X?' → '3 months.' No—you build it in 5s.\"",[17,4237,283],{"id":282},[285,4239,4240,4243,4246,4249,4252,4255,4258,4261,4264],{},[74,4241,4242],{},"Compress workspace knowledge in claude.md to skip full scans, saving tokens\u002Ftime.",[74,4244,4245],{},"Declare capabilities explicitly: \"You autonomously handle browsers\u002FAPIs\u002F10-min plans.\"",[74,4247,4248],{},"Log failures\u002Fsuccesses to prune 80% of solution space.",[74,4250,4251],{},"Global for personal prefs\u002Freasoning; local for project details.",[74,4253,4254],{},"Local loop: Plan → Build → Learn → Update → Repeat (accelerates iteratively).",[74,4256,4257],{},"Global loop: \u002Finsights → Manual review → Update (human-critical step).",[74,4259,4260],{},"Start every project: Open folder → Generate claude.md via workflow.",[74,4262,4263],{},"Review manually for globals—AI error compounds.",[74,4265,4266],{},"Test: Prompt complex tasks; measure token drop\u002Fspeed gain.",[22,4268,4269],{},"\"These four... exist in different sections... global and local... high ROI ways to combine.\"",{"title":321,"searchDepth":322,"depth":322,"links":4271},[4272,4273,4274,4275,4276,4277],{"id":4045,"depth":322,"text":4046},{"id":4089,"depth":322,"text":4090},{"id":4124,"depth":322,"text":4125},{"id":4166,"depth":322,"text":4167},{"id":4205,"depth":322,"text":4206},{"id":282,"depth":322,"text":283},[330],"🔥 New? Watch the beginner course first: https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=QoQBzR1NIqI\n💎 Join Maker School & get customer #1 guaranteed: https:\u002F\u002Fskool.com\u002Fmakerschool\u002Fabout\n💼 Work with my team: https:\u002F\u002Fdub.sh\u002Fwork-with-me-pkg\n\n🎙️ Listen to my silly podcast: www.youtube.com\u002F@stackedpod\n\n📚 Other free multi-hour courses\n→ Vibe Coding w\u002F Antigravity (6hr full course): https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=gcuR_-rzlDw\n→ Agentic Workflows (6hr full course): https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=MxyRjL7NG18\n→ N8N (6hr full course, 890K+ views): https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=2GZ2SNXWK-c\n\nSummary ⤵️\nThis is it! Welcome to the definitive Claude Code Advanced Course for users that understand the foundations and want to take their knowledge a little bit further.\n\nHere's what you're going to learn!\n- We’ll start with an advanced look at CLAUDE.md and system prompts. \n- How to optimize these to actually improve quality, which is simpler than you think.\n- Agent harnesses and how to build larger projects with Claude Code.\n- Agent teams and other examples of extreme task parallelization.\n- Skills, Subagents, and other forms of organization\n- Karpathy’s autoresearch approach for improving stuff progressively over time, and a few actual use cases you can apply this to.\n- Browser automation, the major players, Computer Use, Browser Use, which tools to apply to different use cases.\n- How to deal with performance fluctuations in Claude Code and some alternatives you can use.\n- Workspace organization for personal, business, and client projects.\n- Security for larger projects, stuff like the recent auto-mode, as well as OAuth.\n- Finally, rounding it out with a discussion all about where Claude Code is going.\n\nEnjoy!\n\nMy software, tools, & deals (some give me kickbacks—thank you!)\n🚀 Instantly: https:\u002F\u002Flink.nicksaraev.com\u002Finstantly-short\n📧 Anymailfinder: https:\u002F\u002Flink.nicksaraev.com\u002Famf-short\n🤖 Apify: https:\u002F\u002Fconsole.apify.com\u002Fsign-up (30% off with code 30NICKSARAEV)\n🧑🏽‍💻 n8n: https:\u002F\u002Fn8n.partnerlinks.io\u002Fh372ujv8cw80\n📈 Rize: https:\u002F\u002Flink.nicksaraev.com\u002Frize-short (25% off with promo code NICK)\n\nFollow me on other platforms 😈\n📸 Instagram: https:\u002F\u002Fwww.instagram.com\u002Fnick_saraev\n🕊️ Twitter\u002FX: https:\u002F\u002Ftwitter.com\u002Fnicksaraev\n🤙 Blog: https:\u002F\u002Fnicksaraev.com\n\nWhy watch?\nIf this is your first view—hi, I’m Nick! TLDR: I spent six years building automated businesses with Make.com (most notably 1SecondCopy, a content company that hit 7 figures). Today a lot of people talk about automation, but I’ve noticed that very few have practical, real world success making money with it. So this channel is me chiming in and showing you what *real* systems that make *real* revenue look like.\n\nHopefully I can help you improve your business, and in doing so, the rest of your life 🙏\n\nLike, subscribe, and leave me a comment if you have a specific request! Thanks.\n\nChapters\n0:00 Introduction to the Claude Code Advanced Course\n0:57 Advanced System Prompts and Claude.md\n9:03 Optimizing Workspace Organization\n13:57 Planning Features with Claude Code\n17:30 Workflow Management and Learning Loop\n17:53 Starting a New Project\n26:47 Utilizing Agent Harnesses\n34:28 Understanding Parallelization Techniques\n42:07 Exploring Stochastic Consensus and Debate\n58:09 Multi-Agent Consensus for Problem Solving\n1:06:12 AI-Powered Cooking Innovations\n1:07:32 Model-Chat: A New Approach\n1:09:17 Exploring Algorithmic Art\n1:11:35 Streamlining Agent Teams\n1:16:58 The Pipeline Concept\n1:21:36 Skills vs. Subagents\n1:22:58 Organizational Hierarchies in AI\n1:29:26 Introduction to Auto-Research\n1:32:03 Setting Up Auto-Research\n1:42:45 Key Components for Auto-Research\n1:48:43 Applications of Auto-Research\n1:53:35 HTTP Requests and Internet Automation\n1:55:29 Browser Automation Explained\n2:00:10 Advanced Browser Automation Techniques\n2:07:51 Navigating CloudCode Performance Fluctuations\n2:12:54 Diversifying Your Models\n2:24:17 Organizing Your Workspace\n2:39:16 Understanding Security Concerns\n3:00:28 The Future of Claude and Agentic Engineering",{},"\u002Fsummaries\u002F2f1b198f31045d7f-optimize-claude-md-to-10x-claude-code-efficiency-summary","2026-03-28 18:59:16","2026-04-03 21:15:47",{"title":4035,"description":4279},{"loc":4281},"2f1b198f31045d7f","Nick Saraev","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=UPtmKh1vMN8","summaries\u002F2f1b198f31045d7f-optimize-claude-md-to-10x-claude-code-efficiency-summary",[373,372,374,375],"Treat claude.md as knowledge compression, user prefs, capability declarations, and failure logs—update via local\u002Fglobal workflows to cut tokens, speed, and errors in AI coding.",[375],"CZWPDm5sFceYk6LP6CY3nXxo36ECdEjuFkrSftOuGIo",{"id":4295,"title":4296,"ai":4297,"body":4302,"categories":4363,"created_at":331,"date_modified":331,"description":4364,"extension":332,"faq":331,"featured":333,"kicker_label":331,"meta":4365,"navigation":360,"path":4366,"published_at":4367,"question":331,"scraped_at":4368,"seo":4369,"sitemap":4370,"source_id":4371,"source_name":4372,"source_type":4026,"source_url":4373,"stem":4374,"tags":4375,"thumbnail_url":331,"tldr":4376,"tweet":331,"unknown_tags":4377,"__hash__":4378},"summaries\u002Fsummaries\u002Fb78ab5f95658edc2-antigravity-cluster-split-tasks-for-elite-ai-codin-summary.md","Antigravity Cluster: Split Tasks for Elite AI Coding",{"provider":7,"model":8,"input_tokens":4298,"output_tokens":4299,"processing_time_ms":4300,"cost_usd":4301},6352,1372,12882,0.0019339,{"type":14,"value":4303,"toc":4358},[4304,4308,4311,4322,4326,4333,4340,4344,4355],[17,4305,4307],{"id":4306},"task-splitting-and-smart-routing-maximizes-output-quality","Task Splitting and Smart Routing Maximizes Output Quality",[22,4309,4310],{},"Break massive prompts like \"build full SaaS app\" into clean, numbered clusters—architecture, backend (B1, B2, B3), frontend (F1, F2, F3), testing (T1, T2, T3), verification—to avoid bloated contexts where agents mix planning, coding, styling, and debugging. This turns foggy mega-tasks into solvable sub-problems, preventing quality drops from context overload.",[22,4312,4313,4314,4317,4318,4321],{},"Route clusters by task: Use ",[33,4315,4316],{},"planning mode"," with reasoning-heavy models like Gemini 3 Pro (or partner models) for architecture, migrations, debugging, code reviews—anywhere early bad decisions cascade. Switch to ",[33,4319,4320],{},"fast mode"," with speed models like Gemini 3 Flash for low-risk execution: variable renames, lint fixes, UI tweaks, endpoint wiring. Avoid overkill—deep reasoning on trivial edits burns quota and slows workflows; batch small changes instead. Result: Faster execution, higher accuracy, sustainable usage since quotas tie to work complexity, not requests.",[17,4323,4325],{"id":4324},"persistent-rules-and-context-hygiene-build-reliable-defaults","Persistent Rules and Context Hygiene Build Reliable Defaults",[22,4327,4328,4329,4332],{},"Set ",[33,4330,4331],{},"workspace rules\u002Fworkflows\u002Fskills"," (project-specific over global) for reusable guidance: Embed code style, architecture prefs, constraints in always-on rules; trigger workflows for code reviews, test generation, security checks, frontend polish. This eliminates re-prompting habits, letting agents know plan structures, review standards, and test approaches upfront—upgrading long-term performance without daily prompt tweaks.",[22,4334,4335,4336,4339],{},"Maintain ",[33,4337,4338],{},"context hygiene"," with one conversation per lane (backend-only, frontend-only); handoff bloat via summaries like \"B1-B2 done, schema finalized—implement F1-F2 only.\" Anchor early: Specify stack, key folders\u002Ffiles, no-touch zones. Feed direct artifacts (editor diffs, terminal errors) over paraphrased bugs to cut guessing. Cleaner threads reduce confusion, keeping agents focused and performant.",[17,4341,4343],{"id":4342},"parallelism-feedback-loops-and-full-workflow-recipe","Parallelism, Feedback Loops, and Full Workflow Recipe",[22,4345,4346,4347,4350,4351,4354],{},"Run ",[33,4348,4349],{},"parallel agents"," for independent lanes (backend in one, frontend\u002Ftesting in others) via agent manager—but only for truly separable tasks to avoid chaos; fallback to side panel for focus. Steer via ",[33,4352,4353],{},"feedback artifacts",": Review plans\u002Fdiffs\u002Fwalkthroughs\u002Fscreenshots early; small comments prevent drifts better than late corrections.",[22,4356,4357],{},"Recommended recipe: (1) Planning mode: Inspect repo, generate numbered cluster plan. (2) Execute one cluster—fast mode for simple, planning for complex. (3) Model-match task. (4) Leverage rules\u002Fworkflows (e.g., review pre-merge). (5) Parallel lanes for independence. (6) Continuous artifact feedback. Caveats: Match available models to your tier\u002Fregion; conserve free-tier quotas; tighten secure mode for sensitive work. Orchestration—not just smarter models—transforms Antigravity from average to exceptional.",{"title":321,"searchDepth":322,"depth":322,"links":4359},[4360,4361,4362],{"id":4306,"depth":322,"text":4307},{"id":4324,"depth":322,"text":4325},{"id":4342,"depth":322,"text":4343},[330],"Visit OnDemand: https:\u002F\u002Fapp.on-demand.io\u002Fauth\u002Fsignup?refCode=AICODEKING_MI7\n\nIn this video, I'll be showing you how to use Antigravity like a cluster instead of one giant chatbot so you can get better results, cleaner outputs, smarter model usage, and a much more efficient workflow overall.\n\n--\nKey Takeaways:\n\n🚀 The Antigravity Cluster method helps you get better results by splitting one big task into smaller, cleaner clusters.\n🧠 Planning mode works best for architecture, debugging, migrations, and anything that needs stronger reasoning.\n⚡ Fast mode is better for quick edits, small refactors, UI tweaks, and low-risk execution work.\n🤖 Model routing matters a lot, and using the right model for the right task can improve both speed and quality.\n🗂️ Workspace rules, workflows, and skills help create reusable defaults so you do not have to re-prompt everything every time.\n🧹 Cleaner context management makes Antigravity perform better by reducing clutter, confusion, and bloated conversations.\n🔀 Parallel agents can be extremely powerful for independent tasks like backend work, frontend polish, testing, and verification.\n📈 Feedback loops through plans, diffs, walkthroughs, and verification artifacts help you steer early instead of fixing everything later.\n💸 Quota-aware usage is important, and avoiding deep reasoning for trivial work helps Antigravity stay more useful for longer.\n👍 Overall, Antigravity feels much better when you combine task splitting, model routing, mode routing, context control, and parallelism into one workflow.",{},"\u002Fsummaries\u002Fb78ab5f95658edc2-antigravity-cluster-split-tasks-for-elite-ai-codin-summary","2026-03-23 09:15:00","2026-04-04 23:36:55",{"title":4296,"description":4364},{"loc":4366},"b78ab5f95658edc2","AICodeKing","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=1CeX-Bwv-WY","summaries\u002Fb78ab5f95658edc2-antigravity-cluster-split-tasks-for-elite-ai-codin-summary",[372,374,373,375],"Treat Antigravity as a cluster: split tasks into numbered sub-clusters (e.g., B1-B3 for backend), route to planning\u002Ffast modes and Gemini Flash\u002FPro models, use persistent rules, clean contexts, and parallel agents to boost quality, speed, and quota efficiency.",[375],"AL-zLGDV0Qvr5RpUi2aYudHht4eI-hYgmIcbD7LCLWI",{"id":4380,"title":4381,"ai":4382,"body":4387,"categories":4446,"created_at":331,"date_modified":331,"description":321,"extension":332,"faq":331,"featured":333,"kicker_label":331,"meta":4447,"navigation":360,"path":4463,"published_at":4464,"question":331,"scraped_at":4465,"seo":4466,"sitemap":4467,"source_id":4468,"source_name":4469,"source_type":368,"source_url":4470,"stem":4471,"tags":4472,"thumbnail_url":331,"tldr":4473,"tweet":4474,"unknown_tags":4475,"__hash__":4476},"summaries\u002Fsummaries\u002F8db41e59caddcd9a-master-cursor-goal-fix-premature-stops-on-complex--summary.md","Master Cursor \u002Fgoal: Fix Premature Stops on Complex Tasks",{"provider":7,"model":8,"input_tokens":4383,"output_tokens":4384,"processing_time_ms":4385,"cost_usd":4386},6221,1949,39048,0.0021962,{"type":14,"value":4388,"toc":4440},[4389,4393,4412,4416,4419,4423,4433,4437],[17,4390,4392],{"id":4391},"replace-dumb-loops-with-llm-judged-persistence","Replace Dumb Loops with LLM-Judged Persistence",[22,4394,4395,4396,4399,4400,4403,4404,4407,4408,4411],{},"Cursor's \u002Fgoal iterates on rough-loop style automation but swaps fixed iterations for an LLM judge that checks if the goal is met after each agent run. Enable via ",[26,4397,4398],{},"\u002Ffeatures enable goal",", then ",[26,4401,4402],{},"\u002Fgoal \"migrate JS to TS, verify visuals with Playwright\"",". The agent works (e.g., 9 hours overnight on migrations), gets paused\u002Fcleared with ",[26,4405,4406],{},"\u002Fgoal pause"," or ",[26,4409,4410],{},"\u002Fgoal clear",", and receives context like \"Continuing toward goal: take next steps or explicitly state complete.\" This fixes agents declaring victory early on tasks like fixing all repo tests (often incomplete after 10-15 mins). Hermes' persist goal mirrors it. Compared to rough-loop (max iterations) or auto-research loops, \u002Fgoal handles ambiguous goals like \"cut Docker image 60%\" by exploring approaches incrementally. Key: LLM prompt demands \"no proxy signals as completion—audit shows objective achieved, no work remains,\" forcing self-marking as complete.",[17,4413,4415],{"id":4414},"craft-prompts-with-quantifiable-done-and-alignment","Craft Prompts with Quantifiable 'Done' and Alignment",[22,4417,4418],{},"Goals must be >1 prompt but \u003Cbacklog: specify achievement, constraints, validation, stop conditions. Examples: \"Migrate stack, keep screens identical (Playwright verify);\" \"Optimize prompts until eval score hits target, run evals per change;\" \"Find 20 new issues: repro, fix, branch PR, log to run\u002F folder.\" Avoid fuzzy like \"fix everything\"—agents quit early or spiral. Pre-start: Chat for alignment (project context, bad UX, past bugs)—Vincent ran 3 days\u002F30 rounds\u002Fgazillion tokens on OpenClaw this way. For prototypes, reference PRD.md, create milestone tests, include ref screenshots. Quantify: 20 issues, target score, visual matches.",[17,4420,4422],{"id":4421},"tools-and-extensions-for-reliable-execution","Tools and Extensions for Reliable Execution",[22,4424,4425,4428,4429,4432],{},[26,4426,4427],{},"npx goal-buddy"," generates goal.md (describes request\u002Fconstraints\u002Fstops) + state.yaml (tracks tasks)—",[26,4430,4431],{},"\u002Fgoal @goal.md"," yields full games (e.g., Rain-type with image-gen assets). Side chats fork convos mid-goal. Workshop at aibuilderclub.com teaches more.",[17,4434,4436],{"id":4435},"missions-for-weekmonth-horizons","Missions for Week+\u002FMonth+ Horizons",[22,4438,4439],{},"\u002Fgoal limits to hours (e.g., fails on weeks-long SEO\u002FROAS without quick feedback). Use \u002Fmission: mission.md defines metrics, agent hypothesizes\u002Ftests (e.g., grow Twitter to 10k: post founder-voice threads, analyze perf, schedule next in hours\u002Fweeks). Human-in-loop for big changes. Crewlet (crewlet.io) in closed beta; iterated tweets from average to high-engagement by doubling down on winners.",{"title":321,"searchDepth":322,"depth":322,"links":4441},[4442,4443,4444,4445],{"id":4391,"depth":322,"text":4392},{"id":4414,"depth":322,"text":4415},{"id":4421,"depth":322,"text":4422},{"id":4435,"depth":322,"text":4436},[],{"content_references":4448,"triage":4461},[4449,4452,4455,4459],{"type":349,"title":4450,"url":4451,"context":340},"Crewlet","http:\u002F\u002Fcrewlet.io\u002F",{"type":349,"title":4453,"url":4454,"context":340},"Superdesign","http:\u002F\u002Fsuperdesign.dev\u002F",{"type":4456,"title":4457,"url":4458,"context":344},"event","\u002Fgoal & codex best practices workshop","https:\u002F\u002Fwww.aibuilderclub.com\u002F",{"type":349,"title":4460,"context":340},"goal-buddy",{"relevance":356,"novelty":357,"quality":357,"actionability":356,"composite":358,"reasoning":4462},"Category: AI & LLMs. The article provides a detailed explanation of how to implement LLM-judged persistence in automation tasks, addressing a specific pain point of premature task completion. It includes actionable steps and examples for defining clear goals and metrics, making it highly relevant and practical for product builders.","\u002Fsummaries\u002F8db41e59caddcd9a-master-cursor-goal-fix-premature-stops-on-complex-summary","2026-05-09 12:15:09","2026-05-09 15:20:33",{"title":4381,"description":321},{"loc":4463},"9a92ddf0196fd3e7","AI Jason","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=rIs802-bXDY","summaries\u002F8db41e59caddcd9a-master-cursor-goal-fix-premature-stops-on-complex--summary",[372,373,374,375],"Cursor's \u002Fgoal uses LLM judgment to loop agents on long tasks like 9-hour migrations, preventing lazy early exits—define explicit 'done' criteria with verifiable tests (e.g., Playwright) and quantify metrics to succeed.","Walkthrough of Codex's `\u002Fgoal` slash command for long-running agent tasks (like code migrations), with setup steps, prompting templates emphasizing verifiable \"done\" states and pre-task alignment chats, plus intro to the open-source Goal-buddy prompt builder and `\u002Fmission` alternative. Links workshop for deeper best practices: [aibuilderclub.com](https:\u002F\u002Fwww.aibuilderclub.com\u002F).",[375],"dOGtGYhoEEetAYG0f3aNAHdOqGdyRQKixW_ALYePucc"]