[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-bd814ed08d258184-4-step-audit-catches-ai-s-almost-right-errors-summary":3,"summaries-facets-categories":104,"summary-related-bd814ed08d258184-4-step-audit-catches-ai-s-almost-right-errors-summary":3674},{"id":4,"title":5,"ai":6,"body":13,"categories":68,"created_at":69,"date_modified":69,"description":62,"extension":70,"faq":69,"featured":71,"kicker_label":69,"meta":72,"navigation":84,"path":85,"published_at":86,"question":69,"scraped_at":87,"seo":88,"sitemap":89,"source_id":90,"source_name":91,"source_type":92,"source_url":93,"stem":94,"tags":95,"thumbnail_url":99,"tldr":100,"tweet":101,"unknown_tags":102,"__hash__":103},"summaries\u002Fsummaries\u002Fbd814ed08d258184-4-step-audit-catches-ai-s-almost-right-errors-summary.md","4-Step Audit Catches AI's 'Almost Right' Errors",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","x-ai\u002Fgrok-4.1-fast",6946,1940,20110,0.0023367,{"type":14,"value":15,"toc":61},"minimark",[16,21,25,28,32,35,39,46,52,58],[17,18,20],"h2",{"id":19},"reserve-audits-for-10-high-stakes-tasks-only","Reserve Audits for 10% High-Stakes Tasks Only",[22,23,24],"p",{},"AI outputs that are completely wrong are easy to spot, but 'almost right' ones—clean writing, mostly correct facts, subtle misrepresentations—are dangerous because they mislead in high-impact scenarios like contract reviews, due diligence on vendors\u002Fcompanies, or proposal comparisons with financial, legal, or brand risks. Skip this process for 90% of low-stakes uses to avoid wasting time; apply it only when stakes justify the effort, as simply asking 'Are you sure?' fails to catch hidden errors.",[22,26,27],{},"Use different AI models per step (e.g., Claude 3 Opus for creation\u002Frewrite, GPT-4o\u002FGPT-4.5 for splitting, Gemini 1.5 Pro for checking) in fresh conversations to minimize bias leakage and leverage each model's strengths\u002Fweaknesses for better error detection in extreme cases.",[17,29,31],{"id":30},"step-1-finish-the-output-before-auditing","Step 1: Finish the Output Before Auditing",[22,33,34],{},"Create your AI-generated artifact (document, Excel, PowerPoint) through iteration until satisfied and ready to ship. Pause here: if high-stakes, proceed to audit; otherwise, send it. This ensures you're auditing a polished version without premature over-analysis.",[17,36,38],{"id":37},"steps-2-4-split-claims-validate-and-rewrite","Steps 2-4: Split Claims, Validate, and Rewrite",[22,40,41,45],{},[42,43,44],"strong",{},"Step 2 - Split Claims:"," In a new high-end model chat (e.g., Claude 3 Opus\u002FGPT-4.5), paste this prompt: \"Break this write-up into small factual claims (one checkable fact each). List only factual claims from advice\u002Ftone\u002Fwording. Output table: Claim # | Exact Claim | Source Proving It.\" Attach\u002Fpaste the finished output. Result: table of all claims with cited sources, exposing unproven assertions.",[22,47,48,51],{},[42,49,50],{},"Step 3 - Validate Claims:"," New chat, same high-end model. Paste prompt: \"Check claims against provided source material only (treat as full evidence). Use 4 labels: 1) Supported (source proves it, action: keep); 2) Conflicts (directly opposes source, action: replace with source); 3) No Proof (source lacks it, action: remove\u002Fsoften); 4) Needs Human Judgment (prediction\u002Fcontext beyond source, action: human review). Output per claim: Label | Exact Source Quote | 1-Sentence Reason.\" Attach claims table + source. Result: audit report flags issues like overreaching (e.g., assuming enterprise customers drove 18% revenue growth without proof) or conflicts (e.g., claiming sales efficiency improved when source says opposite).",[22,53,54,57],{},[42,55,56],{},"Step 4 - Rewrite with Fixes:"," New chat. Paste prompt: \"Rewrite original write-up using audit below. Base only on original + audit (no external knowledge\u002Finternet). Keep structure\u002Fstyle. Rules: Supported=keep; Conflicts=use source facts; No Proof=remove\u002Fsoften; Needs Human=leave uncertain for review.\" Attach original + audit. Outcome: accurate version, e.g., changes 'revenue grew 18% driven by enterprise customers, sales more efficient' to 'revenue grew 18% (reason uncertain), sales efficiency declined per source.'",[22,59,60],{},"This chain catches plausible errors only domain experts or this process would spot, ensuring outputs match sources precisely.",{"title":62,"searchDepth":63,"depth":63,"links":64},"",2,[65,66,67],{"id":19,"depth":63,"text":20},{"id":30,"depth":63,"text":31},{"id":37,"depth":63,"text":38},[],null,"md",false,{"content_references":73,"triage":79},[74],{"type":75,"title":76,"url":77,"context":78},"other","The Most Dangerous AI Answer Is the One That's Almost Right (Presentation with prompts)","https:\u002F\u002Fd-squared70.github.io\u002FThe-Most-Dangerous-AI-Answer-Is-the-One-That-s-Almost-Right\u002F","mentioned",{"relevance":80,"novelty":81,"quality":81,"actionability":80,"composite":82,"reasoning":83},5,4,4.55,"Category: AI & LLMs. The article provides a practical framework for auditing AI outputs, specifically addressing high-stakes scenarios, which is a critical concern for the target audience. It outlines a clear, actionable 4-step process that developers can implement immediately to improve the reliability of AI-generated content.",true,"\u002Fsummaries\u002Fbd814ed08d258184-4-step-audit-catches-ai-s-almost-right-errors-summary","2026-05-09 18:00:46","2026-05-10 15:10:04",{"title":5,"description":62},{"loc":85},"c73c8b36026ee106","Dylan Davis","video","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=n9rNzM-I82U","summaries\u002Fbd814ed08d258184-4-step-audit-catches-ai-s-almost-right-errors-summary",[96,97,98],"prompt-engineering","ai-tools","dev-productivity","https:\u002F\u002Fi.ytimg.com\u002Fvi\u002Fn9rNzM-I82U\u002Fhqdefault.jpg","For high-stakes AI outputs (financial\u002Flegal), finish your artifact, then in fresh chats: split into factual claims, validate against source with 4 labels (supported\u002Fconflicts\u002Fno proof\u002Fneeds human), and rewrite fixes subtle lies that sound plausible.","Outlines a four-step AI workflow to catch subtle errors in high-stakes outputs like contracts or due diligence: finish the draft, extract claims into a table, validate against sources (supported\u002Fconflicts\u002Fno proof\u002Fneeds human judgment), rewrite. Copy-paste prompts are in the 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This fragments cognition: AI treats one mind as multiple personas, leading to inconsistent outputs that erode personal brand coherence. The fix distinguishes ",[42,3693,3694],{},"roots"," (stable psychological principles, philosophical defaults, aesthetic commitments true everywhere) from ",[42,3697,3698],{},"branches"," (tone, audience assumptions, pacing that adapt per context). Example: \"Prioritize clarity over comprehensiveness\" is a root manifesting as conversational LinkedIn posts, researched newsletters, or detailed specs. Rebuilding branches per project wastes time; inheriting roots once eliminates context-switching costs, backed by research showing task-switching reduces productivity (cited PMC study). Readers sense this inconsistency online when AI defaults to averages without your encoded principles.",[17,3701,3703],{"id":3702},"build-a-root-file-in-20-minutes-for-instant-inheritance","Build a Root File in 20 Minutes for Instant Inheritance",[22,3705,3706],{},"Create a Markdown root file (300 words max) as the first layer in every Claude Project, skill, or agent. Paste it to load your universals: AI instantly knows how you reason, cutting clarifying questions and rephrasing. It saves calibration time, not tokens, by aligning AI to your defaults from the start. Distinctions:",[3708,3709,3710,3726],"ul",{},[3711,3712,3713,3716,3717,3721,3722,3725],"li",{},[42,3714,3715],{},"Vs. voice profile",": Root captures ",[3718,3719,3720],"em",{},"how you think"," (decisions before style); voice handles ",[3718,3723,3724],{},"how you write",".",[3711,3727,3728,3731],{},[42,3729,3730],{},"Vs. context document",": Root is prescriptive (\"how to decide ambiguities\"); context is descriptive (audience, goals).",[22,3733,3734],{},"To build: Pull writing from three different domains (e.g., newsletter + client email + product copy). Use the provided 4-phase prompt for extraction:",[3736,3737,3738,3744,3750,3756],"ol",{},[3711,3739,3740,3743],{},[42,3741,3742],{},"Pattern extraction"," (private): Spot recurring structures, commitments, aesthetics, reader outcomes.",[3711,3745,3746,3749],{},[42,3747,3748],{},"Interview"," (6 targeted questions): Confirm deliberate patterns, costs of commitments, non-negotiables.",[3711,3751,3752,3755],{},[42,3753,3754],{},"Pressure-test",": Verify each principle appears everywhere (with maintenance cost) vs. adaptive branches.",[3711,3757,3758,3761,3762],{},[42,3759,3760],{},"Output structure",":\n",[3708,3763,3764,3775,3781,3787,3793],{},[3711,3765,3766],{},[3767,3768,3770,3774],"h1",{"id":3769},"names-root-file",[3771,3772,3773],"span",{},"Name","'s Root File",[3711,3776,3777],{},[17,3778,3780],{"id":3779},"what-this-file-is-inheritance-explanation","What this file is (inheritance explanation)",[3711,3782,3783],{},[17,3784,3786],{"id":3785},"the-roots-max-5-name-declarative-principle-cost-success-indicator","The roots (max 5: name + declarative principle + cost + success indicator)",[3711,3788,3789],{},[17,3790,3792],{"id":3791},"what-changes-by-context-branches","What changes by context (branches)",[3711,3794,3795],{},[17,3796,3798],{"id":3797},"how-to-use-inherit-silently-flag-drifts","How to use (inherit silently, flag drifts)",[22,3800,3801],{},"Declarative only, no hedging; fits one screen.",[17,3803,3805],{"id":3804},"authors-four-roots-power-consistent-outputs","Author's Four Roots Power Consistent Outputs",[22,3807,3808],{},"Analyzing newsletter, notes, product copy, LinkedIn revealed these universals, now loaded in every project:",[3736,3810,3811,3817,3823,3829],{},[3711,3812,3813,3816],{},[42,3814,3815],{},"Strategy before execution",": Diagnose thinking problems first; costs speed but yields better workflows.",[3711,3818,3819,3822],{},[42,3820,3821],{},"Blueprints over fish",": Deliver frameworks that generate context-specific answers; trades quick fixes for adaptability.",[3711,3824,3825,3828],{},[42,3826,3827],{},"Intellectual respect as default",": Assume reader smarts, explain machinery; narrows audience but builds loyalty.",[3711,3830,3831,3834],{},[42,3832,3833],{},"Taste as non-negotiable filter",": Applies uniform bar, adapts expression; refuses mediocrity despite platform pressures.",[22,3836,3837],{},"Result: One-time write, zero re-explanation. Monday switches (newsletter → client → roadmap) pay tax once upfront. Extends prior work like Dexter Protocol (modular files), Cleopatra Treaty (AI partnership), Crossword Method (central constraints). Download ready prompt from RobotsOS.",{"title":62,"searchDepth":63,"depth":63,"links":3839},[3840,3841,3842],{"id":3687,"depth":63,"text":3688},{"id":3702,"depth":63,"text":3703},{"id":3804,"depth":63,"text":3805},[113],{"content_references":3845,"triage":3875},[3846,3849,3854,3857,3860,3863,3867,3872],{"type":75,"title":3847,"url":3848,"context":78},"TomTato","https:\u002F\u002Fblog.thompson-morgan.com\u002Ftomtato-harvest-potatoes-and-tomatoes-from-the-same-plant\u002F",{"type":75,"title":3850,"author":3851,"url":3852,"context":3853},"three Claude Projects for three thinking modes","Mia Kiraki","https:\u002F\u002Frobotsatemyhomework.substack.com\u002Fp\u002Fthree-claude-projects-thinking-modes","cited",{"type":75,"title":3855,"author":3851,"url":3856,"context":3853},"Dexter Protocol","https:\u002F\u002Frobotsatemyhomework.substack.com\u002Fp\u002Fcontext-engineering-guide",{"type":75,"title":3858,"author":3851,"url":3859,"context":3853},"The Cleopatra Treaty","https:\u002F\u002Frobotsatemyhomework.substack.com\u002Fp\u002Fbehavioral-engineering-ai-partnership",{"type":75,"title":3861,"author":3851,"url":3862,"context":78},"Crossword Method","https:\u002F\u002Frobotsatemyhomework.substack.com\u002Fp\u002Fi-created-a-crossword-to-redesign",{"type":3864,"title":3865,"url":3866,"context":3853},"paper","Context-switching is expensive","https:\u002F\u002Fpmc.ncbi.nlm.nih.gov\u002Farticles\u002FPMC10140903\u002F",{"type":3868,"title":3869,"url":3870,"context":3871},"tool","Voice Profile Builder","https:\u002F\u002Frobotsatemyhomework.com\u002Frobotsos\u002Fskills\u002Fvoice-profile-builder","recommended",{"type":3868,"title":3873,"url":3874,"context":3871},"RobotsOS","https:\u002F\u002Frobotsatemyhomework.com\u002Frobotsos\u002Fplaybooks\u002Froot-file-builder",{"relevance":81,"novelty":3876,"quality":81,"actionability":81,"composite":3877,"reasoning":3878},3,3.8,"Category: AI & LLMs. The article provides a practical framework for creating a 'root file' to streamline AI interactions, addressing the pain point of context-switching for multi-domain creators. It offers a specific method for building this file, which can be directly applied to enhance productivity in AI projects.","\u002Fsummaries\u002F7db846cc30c3f06d-root-file-unifies-ai-thinking-across-contexts-summary","2026-04-29 12:28:23","2026-05-03 17:01:23",{"title":3677,"description":62},{"loc":3879},"7db846cc30c3f06d","Robots Ate My Homework","article","https:\u002F\u002Frobotsatemyhomework.substack.com\u002Fp\u002Fai-root-file-context-switching","summaries\u002F7db846cc30c3f06d-root-file-unifies-ai-thinking-across-contexts-summary",[96,97,98],"Capture your core cognitive principles in a single .md root file (\u003C300 words) and paste it into every AI project to eliminate the 'identity tax' of rebuilding your thinking for each domain, ensuring consistent reasoning from newsletters to product specs.",[98],"3OGktm_VwIh_V9k4hYtu-N04EIv1G7u4FblGoqoenE8",{"id":3894,"title":3895,"ai":3896,"body":3901,"categories":3941,"created_at":69,"date_modified":69,"description":3942,"extension":70,"faq":69,"featured":71,"kicker_label":69,"meta":3943,"navigation":84,"path":3944,"published_at":3945,"question":69,"scraped_at":3946,"seo":3947,"sitemap":3948,"source_id":3949,"source_name":3950,"source_type":92,"source_url":3951,"stem":3952,"tags":3953,"thumbnail_url":69,"tldr":3954,"tweet":69,"unknown_tags":3955,"__hash__":3956},"summaries\u002Fsummaries\u002F74b1199b70221af9-wispr-flow-4-6x-faster-claude-code-via-dictation-summary.md","Wispr Flow: 4-6x Faster Claude Code via Dictation",{"provider":7,"model":8,"input_tokens":3897,"output_tokens":3898,"processing_time_ms":3899,"cost_usd":3900},5510,1328,14122,0.00129875,{"type":14,"value":3902,"toc":3936},[3903,3907,3910,3913,3917,3920,3923,3927,3930,3933],[17,3904,3906],{"id":3905},"dictation-delivers-detailed-prompts-for-first-try-claude-code-success","Dictation Delivers Detailed Prompts for First-Try Claude Code Success",[22,3908,3909],{},"Replace typing's 20-25 words per minute with Wispr Flow's 150 wpm dictation to craft nuanced prompts that capture full intent without simplification. For a login page, dictate: \"Build with email\u002Fpassword fields, validation errors below each, forgot password modal, Google\u002FGitHub OAuth buttons, Tailwind-responsive design, and submit loading states.\" This 15-second speech yields a complete component on Claude Code's first generation, avoiding 20 minutes of lazy-prompt follow-ups. Detailed input reduces iteration because Claude builds exactly what's specified—email validation, modals, OAuth, responsiveness—in one shot, saving output time too.",[22,3911,3912],{},"Follow-ups benefit equally: Dictate corrections like \"Button mismatches design system—use Tailwind primary blue, add 10% darker hover, fix form field vertical padding\" in 10 seconds for instant multi-change application, versus fragmented typed instructions.",[17,3914,3916],{"id":3915},"claudemd-and-documentation-accelerate-via-natural-speech","CLAUDE.md and Documentation Accelerate via Natural Speech",[22,3918,3919],{},"Document projects comprehensively by dictating CLAUDE.md files, which sub-agents inherit for codebase awareness. Speak: \"Next.js app router, TypeScript everywhere, app\u002Fapi routes, Prisma\u002FPostgreSQL DB, Tailwind custom config, Vitest in tests folder, default server components.\" Finish in minutes what typing skips due to tedium, including forgotten details like conventions and deployment. Strong CLAUDE.md prevents agents from flying blind, ensuring consistent outputs across tasks, teams, and parallel execution.",[22,3921,3922],{},"Extend to commit messages\u002FPRs: Dictate \"Refactored auth middleware for JWT\u002Fsession support, added login rate limiting, updated Vitest for OAuth flow\" in 5 seconds per commit. Over dozens daily, this scales savings without sacrificing clarity for teams or open source.",[17,3924,3926],{"id":3925},"developer-features-minimize-editing-and-adapt-to-coding-contexts","Developer Features Minimize Editing and Adapt to Coding Contexts",[22,3928,3929],{},"Wispr Flow activates via hotkey in terminals, VS Code, browsers, Slack—any typing app—with real-time transcription stripping filler (ums), adding punctuation\u002Fformatting. Post-use, it learns vocab: Prisma, Vitest, TypeScript, Supabase spell correctly after days, unlike generic tools.",[22,3931,3932],{},"Whisper mode captures speech in coffee shops\u002Fshared offices without disturbance. Mid-sentence fixes (\"add POST endpoint—actually PUT\") output only finals, eliminating backspace. Cross-device Mac sync maintains consistent hotkeys\u002Fsettings.",[22,3934,3935],{},"Free tier: 2,000 words\u002Fweek suffices for trials; Pro unlimited via promo (AICodeKING link) adds one free month. No integrations needed—install and dictate instantly, making typed AI coding obsolete for prompt-heavy flows.",{"title":62,"searchDepth":63,"depth":63,"links":3937},[3938,3939,3940],{"id":3905,"depth":63,"text":3906},{"id":3915,"depth":63,"text":3916},{"id":3925,"depth":63,"text":3926},[107],"Download Wispr Flow by using my link with promo code AICODEKING for an extra month of Wispr Flow Pro today: https:\u002F\u002Fref.wisprflow.ai\u002FAICodeKing\n\nThanks to Wispr Flow for sponsoring! I've been using Wispr Flow, a voice-to-text tool that actually cleans up what I say as I speak, and it is a game-changer and much faster and smarter than native or built-in voice input! \n\nIn this video, I'll be telling you about Wispr Flow, an AI-powered speech-to-text tool, and how it can massively speed up your Claude Code workflow by letting you dictate detailed prompts instead of typing them out.\n\n--\nKey Takeaways:\n\n🎙️ Wispr Flow turns your speech into clean, polished text in any app, including your terminal, VS Code, Slack, and browser.\n⚡ Dictating at 150 words per minute is 4 to 6 times faster than typing, leading to a massive overall speed boost.\n📝 Better prompts from voice dictation means Claude Code gets it right on the first try, reducing back-and-forth.\n🧠 Wispr Flow learns your technical vocabulary, correctly spelling terms like Prisma, Vitest, and TypeScript.\n🤫 It even works when you whisper, making it perfect for shared offices or coffee shops.\n📄 Writing CLAUDE.md files and documentation becomes effortless when you can just talk through your project.\n✅ Wispr Flow handles mid-sentence corrections naturally, only outputting your final intended version.",{},"\u002Fsummaries\u002F74b1199b70221af9-wispr-flow-4-6x-faster-claude-code-via-dictation-summary","2026-03-12 08:58:34","2026-04-04 23:37:15",{"title":3895,"description":3942},{"loc":3944},"74b1199b70221af9","AICodeKing","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=oIRkmf89URo","summaries\u002F74b1199b70221af9-wispr-flow-4-6x-faster-claude-code-via-dictation-summary",[97,96,98],"Dictate detailed Claude Code prompts at 150 wpm with Wispr Flow—4-6x faster than typing 20-25 wpm—delivering precise first-try results that cut follow-ups and compound to 20x workflow speed.",[98],"0RWbnEk9D0aH-132G8Otx5rAEGOXc6FjI445aFFn44M",{"id":3958,"title":3959,"ai":3960,"body":3965,"categories":4025,"created_at":69,"date_modified":69,"description":62,"extension":70,"faq":69,"featured":71,"kicker_label":69,"meta":4026,"navigation":84,"path":4042,"published_at":4043,"question":69,"scraped_at":4044,"seo":4045,"sitemap":4046,"source_id":4047,"source_name":4048,"source_type":3886,"source_url":4049,"stem":4050,"tags":4051,"thumbnail_url":69,"tldr":4053,"tweet":4054,"unknown_tags":4055,"__hash__":4056},"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":3961,"output_tokens":3962,"processing_time_ms":3963,"cost_usd":3964},6221,1949,39048,0.0021962,{"type":14,"value":3966,"toc":4019},[3967,3971,3991,3995,3998,4002,4012,4016],[17,3968,3970],{"id":3969},"replace-dumb-loops-with-llm-judged-persistence","Replace Dumb Loops with LLM-Judged Persistence",[22,3972,3973,3974,3978,3979,3982,3983,3986,3987,3990],{},"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 ",[3975,3976,3977],"code",{},"\u002Ffeatures enable goal",", then ",[3975,3980,3981],{},"\u002Fgoal \"migrate JS to TS, verify visuals with Playwright\"",". The agent works (e.g., 9 hours overnight on migrations), gets paused\u002Fcleared with ",[3975,3984,3985],{},"\u002Fgoal pause"," or ",[3975,3988,3989],{},"\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.",[17,3992,3994],{"id":3993},"craft-prompts-with-quantifiable-done-and-alignment","Craft Prompts with Quantifiable 'Done' and Alignment",[22,3996,3997],{},"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.",[17,3999,4001],{"id":4000},"tools-and-extensions-for-reliable-execution","Tools and Extensions for Reliable Execution",[22,4003,4004,4007,4008,4011],{},[3975,4005,4006],{},"npx goal-buddy"," generates goal.md (describes request\u002Fconstraints\u002Fstops) + state.yaml (tracks tasks)—",[3975,4009,4010],{},"\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.",[17,4013,4015],{"id":4014},"missions-for-weekmonth-horizons","Missions for Week+\u002FMonth+ Horizons",[22,4017,4018],{},"\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":62,"searchDepth":63,"depth":63,"links":4020},[4021,4022,4023,4024],{"id":3969,"depth":63,"text":3970},{"id":3993,"depth":63,"text":3994},{"id":4000,"depth":63,"text":4001},{"id":4014,"depth":63,"text":4015},[],{"content_references":4027,"triage":4040},[4028,4031,4034,4038],{"type":3868,"title":4029,"url":4030,"context":78},"Crewlet","http:\u002F\u002Fcrewlet.io\u002F",{"type":3868,"title":4032,"url":4033,"context":78},"Superdesign","http:\u002F\u002Fsuperdesign.dev\u002F",{"type":4035,"title":4036,"url":4037,"context":3871},"event","\u002Fgoal & codex best practices workshop","https:\u002F\u002Fwww.aibuilderclub.com\u002F",{"type":3868,"title":4039,"context":78},"goal-buddy",{"relevance":80,"novelty":81,"quality":81,"actionability":80,"composite":82,"reasoning":4041},"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":3959,"description":62},{"loc":4042},"9a92ddf0196fd3e7","AI Jason","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=rIs802-bXDY","summaries\u002F8db41e59caddcd9a-master-cursor-goal-fix-premature-stops-on-complex--summary",[4052,96,97,98],"agents","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).",[98],"dOGtGYhoEEetAYG0f3aNAHdOqGdyRQKixW_ALYePucc",{"id":4058,"title":4059,"ai":4060,"body":4065,"categories":4371,"created_at":69,"date_modified":69,"description":62,"extension":70,"faq":69,"featured":71,"kicker_label":69,"meta":4372,"navigation":84,"path":4391,"published_at":4392,"question":69,"scraped_at":4393,"seo":4394,"sitemap":4395,"source_id":4396,"source_name":4397,"source_type":3886,"source_url":4398,"stem":4399,"tags":4400,"thumbnail_url":69,"tldr":4401,"tweet":69,"unknown_tags":4402,"__hash__":4403},"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":4061,"output_tokens":4062,"processing_time_ms":4063,"cost_usd":4064},8619,2616,40938,0.0030093,{"type":14,"value":4066,"toc":4364},[4067,4071,4078,4084,4090,4096,4100,4111,4117,4146,4152,4158,4163,4167,4174,4179,4196,4201,4215,4225,4235,4240,4244,4251,4256,4282,4292,4314,4320,4325,4329],[17,4068,4070],{"id":4069},"access-and-manage-all-customizations-from-one-ui","Access and Manage All Customizations from One UI",[22,4072,4073,4074,4077],{},"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 ",[3975,4075,4076],{},"\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).",[22,4079,4080,4083],{},[42,4081,4082],{},"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.",[22,4085,4086,4089],{},[42,4087,4088],{},"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.",[22,4091,4092,4095],{},[42,4093,4094],{},"Quote",": \"Customization changes that. It lets you define behavior once, reuse it everywhere, and get consistent outputs.\"",[17,4097,4099],{"id":4098},"enforce-rules-and-styles-with-custom-instructions","Enforce Rules and Styles with Custom Instructions",[22,4101,4102,4103,4106,4107,4110],{},"Custom instructions are Markdown files acting as a \"rule book\" for Copilot, applied automatically to matching file types (defined in ",[3975,4104,4105],{},"apply_to"," metadata). Structure: metadata (description, glob patterns like ",[3975,4108,4109],{},"**\u002F*.js","), then bullet-point rules.",[22,4112,4113,4116],{},[42,4114,4115],{},"Steps to create",":",[3736,4118,4119,4125,4140,4143],{},[3711,4120,4121,4122,4124],{},"In Chat: ",[3975,4123,4076],{}," + description (e.g., \"Ensure UI meets WCAG standards, confirm in chat\").",[3711,4126,4127,4128,4131,4132,4135,4136,4139],{},"Copilot generates ",[3975,4129,4130],{},".instructions.md"," (user: ",[3975,4133,4134],{},"~\u002F.vscode-customizations\u002F","; workspace: ",[3975,4137,4138],{},".vscode-customizations\u002F",").",[3711,4141,4142],{},"Review\u002Fedit in UI: Add confirmation phrases like \"Confirmation: Applied WCAG standards.\"",[3711,4144,4145],{},"Test: Ask Copilot to edit code (e.g., \"Refactor this script\" or \"Make UI 80s arcade style\")—it analyzes, applies rules, and confirms.",[22,4147,4148,4151],{},[42,4149,4150],{},"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.",[22,4153,4154,4157],{},[42,4155,4156],{},"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.",[22,4159,4160,4162],{},[42,4161,4094],{},": \"Imagine every developer in the repo having Copilot follow the same coding conventions... This saves a lot of time.\"",[17,4164,4166],{"id":4165},"specialize-agents-with-skills-and-custom-agents","Specialize Agents with Skills and Custom Agents",[22,4168,4169,4170,4173],{},"Agent skills are folders (",[3975,4171,4172],{},"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.",[22,4175,4176,4116],{},[42,4177,4178],{},"Build a skill",[3736,4180,4181,4187,4193],{},[3711,4182,4183,4186],{},[3975,4184,4185],{},"\u002Fcreate skill"," + task (e.g., \"Update README on feature add, confirm in chat\").",[3711,4188,4189,4190,4192],{},"Copilot creates folder with ",[3975,4191,4172],{}," (description, related skills, rules like \"Extract feature from convo, append to README features section\").",[3711,4194,4195],{},"Test: Add feature (e.g., \"Add dark\u002Flight jingle\")—skill auto-updates README.",[22,4197,4198,4116],{},[42,4199,4200],{},"Build custom agent",[3736,4202,4203,4206,4212],{},[3711,4204,4205],{},"Ask Copilot for prompt: \"Suggest custom agent for arcade calculator.\"",[3711,4207,4208,4211],{},[3975,4209,4210],{},"\u002Fcreate agent"," + persona (e.g., \"Arcade App Builder: Knows retro aesthetics, sound effects, HTML\u002FJS\u002FCSS stack\").",[3711,4213,4214],{},"Select from Chat dropdown (@agentname); it uses codebase knowledge for tasks like \"Build tip calculator.\"",[22,4216,4217,4220,4221,4224],{},[42,4218,4219],{},"Example",": Security agent reviews JS for vulns (categorizes low\u002Fmedium\u002Fhigh); Arcade agent clones styles\u002Fsounds to new app. ",[42,4222,4223],{},"Trade-off",": Domain-focused (great for projects) but overkill for one-offs.",[22,4226,4227,4230,4231,4234],{},[42,4228,4229],{},"Mistake to avoid",": Not scoping (user vs. workspace)—use workspace for teams. ",[42,4232,4233],{},"Quality",": Clear description, minimal tools, architecture awareness.",[22,4236,4237,4239],{},[42,4238,4094],{},": \"Custom agents enable you to configure the AI to adopt different personas tailored to specific development roles and tasks.\"",[17,4241,4243],{"id":4242},"automate-repetitive-tasks-with-hooks-and-prompt-files","Automate Repetitive Tasks with Hooks and Prompt Files",[22,4245,4246,4247,4250],{},"Hooks run shell commands at agent lifecycle events (e.g., ",[3975,4248,4249],{},"post_tool_use","). Prompt files are reusable templates.",[22,4252,4253,4116],{},[42,4254,4255],{},"Create hook",[3736,4257,4258,4261,4279],{},[3711,4259,4260],{},"UI > Generate hook + spec (e.g., \"Run Prettier on post_tool_use\").",[3711,4262,4263,4264,4267,4268,4271,4272,4275,4276,4139],{},"Edits ",[3975,4265,4266],{},".vscode-customizations\u002Fhooks\u002Fprettier.hook.json",": Define ",[3975,4269,4270],{},"events"," (array), ",[3975,4273,4274],{},"command"," (e.g., ",[3975,4277,4278],{},"npx prettier --write .",[3711,4280,4281],{},"Reload VS Code; test: Edit README—hook auto-formats.",[22,4283,4284,4287,4288,4291],{},[42,4285,4286],{},"Prompt files",": ",[3975,4289,4290],{},"\u002Fcreate prompt"," for templates (e.g., code review); reference in skills.",[22,4293,4294,4297,4298,4287,4301,4304,4305,4304,4308,4310,4311,4313],{},[42,4295,4296],{},"Principle",": Automate validation (security, formatting) without manual invocation. ",[42,4299,4300],{},"Events",[3975,4302,4303],{},"start_session",", ",[3975,4306,4307],{},"user_prompt_submit",[3975,4309,4249],{},". ",[42,4312,4223],{},": Shell reliance—test commands; no timeout for long runs.",[22,4315,4316,4319],{},[42,4317,4318],{},"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.",[22,4321,4322,4324],{},[42,4323,4094],{},": \"Hooks enable you to execute custom shell commands at life cycle points during agent sessions... automate workflows, enforce security policies.\"",[17,4326,4328],{"id":4327},"key-takeaways","Key Takeaways",[3708,4330,4331,4334,4340,4343,4349,4352,4355,4358,4361],{},[3711,4332,4333],{},"Open Customization UI via gear or \"chat customizations\" to manage everything in one place.",[3711,4335,4336,4337,4339],{},"Start with custom instructions for persistent rules: ",[3975,4338,4076],{}," + glob patterns + confirmations.",[3711,4341,4342],{},"Use agent skills for tasks (e.g., README updates) and custom agents for personas—select via @dropdown.",[3711,4344,4345,4346,4348],{},"Automate with hooks on lifecycle events like ",[3975,4347,4249],{}," for formatters; reload to activate.",[3711,4350,4351],{},"Generate via Copilot slash commands to skip manual writing; always review\u002Fedit.",[3711,4353,4354],{},"Scope user\u002Fworkspace for personal\u002Fteam use; test on real edits\u002Frefactors.",[3711,4356,4357],{},"Check Awesome Copilot repo for community examples.",[3711,4359,4360],{},"Avoid repetition: Customizations turn Copilot into a context-aware system.",[3711,4362,4363],{},"For apps: Chain features—instructions for compliance, agents for domain logic, hooks for polish.",{"title":62,"searchDepth":63,"depth":63,"links":4365},[4366,4367,4368,4369,4370],{"id":4069,"depth":63,"text":4070},{"id":4098,"depth":63,"text":4099},{"id":4165,"depth":63,"text":4166},{"id":4242,"depth":63,"text":4243},{"id":4327,"depth":63,"text":4328},[113],{"content_references":4373,"triage":4389},[4374,4377,4380,4383,4386],{"type":75,"title":4375,"url":4376,"context":78},"VS Code Customization Overview","https:\u002F\u002Faka.ms\u002FVSCL-Cust-Overview",{"type":75,"title":4378,"url":4379,"context":3871},"Awesome Copilot","https:\u002F\u002Faka.ms\u002FAwesomeGC",{"type":75,"title":4381,"url":4382,"context":78},"VS Code Learn Playlist","https:\u002F\u002Faka.ms\u002Fvsc-learn",{"type":3868,"title":4384,"url":4385,"context":78},"Custom Instructions Docs","https:\u002F\u002Faka.ms\u002Fcustom-instructions",{"type":3868,"title":4387,"url":4388,"context":78},"Custom Agent Skills","https:\u002F\u002Faka.ms\u002Fcustom-agent-skills",{"relevance":80,"novelty":81,"quality":81,"actionability":80,"composite":82,"reasoning":4390},"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.","\u002Fsummaries\u002F8e760cba47215e0d-customize-vs-code-copilot-agents-for-repeatable-wo-summary","2026-05-06 14:00:14","2026-05-06 16:10:56",{"title":4059,"description":62},{"loc":4391},"ab488a3c329a1bb7","Visual Studio Code","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=9PUt81AjfmA","summaries\u002F8e760cba47215e0d-customize-vs-code-copilot-agents-for-repeatable-wo-summary",[4052,96,97,98],"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 extensions.",[98],"W1zwbe6XmkDedssnAbVlY_GoLAd41WfXB9VHvOaL2LU"]