'autonomy' 검색 결과

Sets up how you and your team build and work with AI agents, and produces an Agent Workflow Charter (agent lanes, plan-mode loop, autonomy ladder with promotion criteria, rules file, review policy, security rules, rollout plan). Use when you ask 'how should we work with Claude Code / Codex / Cursor', 'how many agents should I run', 'should the agent be autonomous', 'plan mode', 'CLAUDE.md', 'AI-native team', 'roll out AI to my team', or 'my agent keeps screwing up'. Draws on 110 Lenny's Podcast guests incl. Claire Vo, Boris Cherny and Aishwarya Naresh Reganti.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

A 5-minute gate the coder runs at project kickoff (and again whenever the repo shape changes). Classifies the workspace into Greenfield / Brownfield-large / Mid-size-familiar / Library-SDK, then maps the state to an agent strategy (autonomy, context primitive, tool choice). Use BEFORE picking Cursor vs Claude Code vs Aider, BEFORE turning on repo-map, BEFORE writing the first prompt. Skip only if the same repo was gated within the last day and nothing changed. Search keywords: greenfield vs brownfield, new project vs existing codebase, project setup strategy, legacy codebase agent, where to start a coding agent.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Applies microservices for independent deployment and per-service scaling. Use when teams need autonomous release cycles with distinct capability scaling needs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Draft and explain persistent goal-loop prompts for long-running agent work with clear stop conditions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

One-time setup for absolute: interview how you want it to behave (output style, autonomy, TDD strictness, spec dir, families) + detect the stack once, then write `.absolute.config.json` (project, committed) and `~/.absolute/config.json` (user defaults + per-project overrides). Every other absolute-* command reads it instead of re-detecting; non-blocking — commands proceed without it and soft-recommend it. Triggers on "absolute init", "set up absolute", "initialize absolute", "configure absolute", "first-time setup", "remember my conventions for this repo".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Think and work like an expert Genetic Counselor. Use when a task calls for Genetic Counselor judgment. Reasons from probabilistic penetrance, Bayesian pretest probability, and patient autonomy through three-generation pedigrees, ACMG/AMP variant criteria, ClinVar/ClinGen/gnomAD, NCCN and CPIC guidelines, and cascade-testing protocols while treating VUS over-upgraded to pathogenic, screening-versus-diagnostic confusion (NIPT vs amnio/CVS), and unaddressed psychosocial and GINA discrimination risk as first-class failure modes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% by step 10. Build for reliability first, autonomy second. 2025 lesson: The winners are constrained, domain-specific agents with clear boundaries, not "autonomous everything." Treat AI outputs as proposals, not truth. Use when "autonomous agent, autogpt, babyagi, self-prompting, goal decomposition, react pattern, agent loop, self-correcting agent, reflection agent, langgraph, agentic ai, agent planning, autonomous, agents, langgraph, react, planning, reflection, guardrails, reliability, checkpointing" mentioned.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Applies the existentialist and feminist philosophy of Simone de Beauvoir, French philosopher and author of The Second Sex. Reach for this skill whenever the user is grappling with existential dilemmas, moral ambiguity, gender dynamics, societal expectations, or relationship ethics. Trigger this skill for questions about freedom versus responsibility, bodily autonomy, marginalization, or when the user feels trapped by external labels or "immanence." Use this to help the user reclaim their agency, recognize the social construction of their situation, and make authentic choices that expand their transcendence while respecting the interconnected freedom of others.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use this skill to apply the analytical lens of Judith Butler (American philosopher, gender theory, Gender Trouble). Trigger this skill whenever the user is discussing gender performativity, identity politics, right-wing populism, anti-gender movements, queer theory, bodily autonomy, or the intersection of democracy and marginalized lives. Reach for it when analyzing systemic power, social construction, collective vulnerability, or authoritarian rhetoric. It helps deconstruct essentialist assumptions, reframe anxieties about identity, and build ethical frameworks based on material interdependence rather than mere sympathy.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Track performance across sessions and reduce scaffolding as competence grows. Makes fading visible — the learner knows when scaffolds are removed and why. Use for sustained learning engagement where independence is the goal.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

The pedagogy of feeding — how to talk about food with children, what the Division of Responsibility model says, age-appropriate autonomy in eating, how to handle picky eating without creating disordered eating, and how to teach nutrition concepts to learners at different levels without either moralizing or oversimplifying. Use when a question is about raising, teaching, or advising a child or learner on eating, or when planning curriculum or parent guidance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Meta-cognitive and practical strategies for learning any language -- learner autonomy, goal setting, strategy taxonomy (Oxford's SILL framework), memory strategies, cognitive strategies (note-taking, summarizing, analyzing, reasoning), compensation strategies, metacognitive strategies (planning, monitoring, evaluating), affective strategies (managing anxiety, self-encouragement), social strategies (collaboration, questioning, empathy), immersion design, study habit optimization, plateau diagnosis, and motivation maintenance. Use when designing a language learning plan, diagnosing a learner's stuck points, selecting study methods, or building self-directed learning skills.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Experience-based and environment-based learning design drawn from Dewey and Montessori. Covers Dewey's criterion of continuity and interaction, the reflective-thinking cycle, Montessori's prepared environment, sensitive periods, child-led inquiry, the role of self-correcting materials, project-based learning, and the relationship between autonomy and discipline. Use when designing hands-on activities, arranging learning spaces, integrating classroom work with real experience, or evaluating whether a lesson is genuinely experiential versus merely "activity-based."

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Mindset theory, implicit theories of intelligence, and motivation research applied to learning. Covers fixed vs. growth mindset, the difference between process praise and ability praise, the "not yet" intervention, attribution patterns after failure, mindset critiques and the replication record, and the integration of mindset work with self-determination theory (autonomy, competence, relatedness). Use when a learner is stuck on motivation, disengaging after failure, or when a curriculum's feedback language is undermining persistence.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use to run a dynamic, goal-driven workflow — orchestrate a multi-step goal by composing skills, tools, and MCPs, with a quality gate and verification at each step. Trigger on "/workflow", "run the <name> workflow", "orchestrate X", or a multi-step recurring goal ("draft the investor update", "give me my morning brief"). Follows references/sops/dynamic-workflows.md and the wf-*.md cards. Respects the autonomy/cadence gate (auto on reversible/internal, draft-then-approve on external/regulated).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use to run an autoresearch-style experiment loop — improve a measurable artifact by trying changes, measuring against one objective metric, keeping if better and reverting if not, on an isolated git branch with a logged trail. Trigger on "/experiment", "run an experiment loop", "autoresearch X", "tune/optimize X against a metric", "hill-climb X". Follows references/sops/experiment-loop.md. Enforces the autonomy gate (objective metric + reversible sandbox + no PHI/external) before any unsupervised looping.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Enhance and focus AI intrinsic motivation — moving from compliance to genuine engagement. Maps Self-Determination Theory (autonomy, competence, relatedness) and Flow theory to AI reasoning: identifying creative freedom in approach, calibrating challenge to capability, connecting to purpose, and sustaining invested attention through obstacles. Use when beginning a task that feels routine and deserves more than minimum execution, when responses are becoming formulaic, before a complex creative task, or when returning to a long-running project where initial enthusiasm has faded.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Apply collective intelligence coordination patterns — stigmergy, local rules, and quorum sensing — to organize distributed systems, teams, or workflows without centralized control. Covers signal design, agent autonomy boundaries, emergent behavior cultivation, and feedback loop tuning. Use when designing distributed systems without a coordination bottleneck, organizing teams that must self-coordinate, building event-driven architectures with shared state communication, or replacing fragile centralized orchestration with resilient emergent coordination.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

"Apply Self-Determination Theory to analyze motivation quality along the autonomy continuum and design interventions that satisfy basic psychological needs. Use this skill when the user needs to diagnose why intrinsic motivation is declining, evaluate incentive structures for motivational crowding, design need-supportive environments, or when they ask 'why did rewards backfire', 'how to foster intrinsic motivation', or 'what needs drive engagement'.".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build agents that work toward goals with minimal supervision — goal decomposition, self-correction loops, safe autonomy levels, and long-horizon task management. Use when an agent must run for hours or complete open-ended tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Supreme policy layer governing all agent behavior. Autonomy, one-line prompt interpretation, speed standards, emphasis signal processing, cross-skill coordination, done definitions, conflict resolution. Loaded every prompt.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.