| "I want to build something with AI but not sure where to start" | /ai-do | Describe your problem, get routed to the right skill with a ready-to-use prompt |
| "I'm starting a new AI feature" / "DSPy quickstart" | /ai-kickoff | Scaffold a complete AI project with the right structure |
| "I need to auto-sort/tag/categorize content" / "classification results are inconsistent" | /ai-sorting | Build AI that sorts tickets, tags emails, detects sentiment |
| "I need to search docs and answer questions" / "retrieval returns irrelevant results" / "RAG pipeline tutorial" | /ai-searching-docs | Build AI-powered knowledge base, help center, or doc Q&A |
| "I need AI to answer questions about our database" / "chat with your Postgres" | /ai-querying-databases | Text-to-SQL: plain English questions over Postgres, MySQL, Snowflake |
| "I need to condense long content into summaries" | /ai-summarizing | Summarize meetings, articles, threads — with length control |
| "I need to pull structured data from messy text" / "the emails are messy and lack structure" | /ai-parsing-data | Parse invoices, extract entities, convert text to JSON |
| "I need AI to take actions and call APIs" / "LLM function calling" | /ai-taking-actions | Build AI that calls APIs, uses tools, and completes tasks |
| "I need AI to write articles, reports, or copy" | /ai-writing-content | Generate blog posts, product descriptions, newsletters |
| "My AI fails on hard problems that need planning" / "LLM can't do multi-step logic" | /ai-reasoning | Add multi-step reasoning, Self-Discovery, chain-of-thought |
| "My task needs multiple AI steps" / "LangChain LCEL alternative" | /ai-building-pipelines | Chain classify, retrieve, generate, verify into one pipeline |
| "I need to verify AI output before users see it" / "LLMs invent data points" | /ai-checking-outputs | Add guardrails, fact-checking, safety filters, and quality gates |
| "My AI makes stuff up / hallucinates" / "LLM makes up facts" | /ai-stopping-hallucinations | Ground AI in facts with citations, verification, and source checking |
| "My AI doesn't follow our rules" / "LLM JSON output is unreliable" | /ai-following-rules | Enforce content policies, format rules, and business constraints |
| "My AI gives wrong answers" / "I spent hours tweaking prompts" | /ai-improving-accuracy | Measure quality, then systematically improve it |
| "My AI gives different answers every time" / "same prompt, different results every run" | /ai-making-consistent | Lock down outputs so they're predictable and reliable |
| "My AI is too expensive" / "LLM API costs too high" / "GPT-4 costs too much" | /ai-cutting-costs | Reduce API costs with smart routing, caching, fine-tuning |
| "Let's fine-tune on our data" / "prompt optimization hit a ceiling" | /ai-fine-tuning | Train models on your data for max quality or cost savings |
| "Can we switch to a different model?" / "prompt broke after model update" | /ai-switching-models | Switch providers, compare models, re-optimize automatically |
| "We don't have enough training data" / "no labeled data, need to bootstrap" | /ai-generating-data | Generate synthetic examples, fill data gaps, bootstrap from scratch |
| "How do I put my AI behind an API?" / "deploy LLM as API" / "productionize my AI" | /ai-serving-apis | Wrap your AI in FastAPI endpoints for production serving |
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