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Covering the AI stack

  • Claude
  • GPT-5
  • Gemini
  • Cursor
  • Perplexity
  • ElevenLabs
  • Pinecone
  • Qdrant
  • MCP
  • LangGraph
  • Replicate
  • Whisper
  • n8n
  • Zapier

Editor's picks

Topic clusters

Curated paths through the site, organized around the four most common goals.

Build with AI

From idea to shipped

Workflows, agent loops, and the concepts you need to actually ship.

Code with AI

3x your shipping speed

Pick the right model, set up the right tool, ship faster.

Understand the foundations

The concepts that power everything

First-principles primers that age well.

Pick the right model

Stop guessing — start matching

Opinionated head-to-heads, updated when the leaderboard shifts.

Get the AI job

Interview prep that mirrors real loops

Role maps, Q&A with model answers, follow-ups, and a 4-week prep path.

What's new

Recently updated

The latest entries across the library — see what we're refreshing this week.

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Including case studies from teams shipping AI in production.

Featured guides

Start here

Hand-picked tool guides and concept primers — the fastest path to getting useful.

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Build something real

Workflows ready to ship this week

End-to-end blueprints. Architecture, prompts, costs — everything you need to ship.

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Tool stacks

Curated bundles for how you build

Opinionated tool picks by profile — solo dev, automation engineer, RAG on a budget, local privacy.

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Comparison

Pick the right model for the job

Honest, opinionated head-to-heads. No model hype, no model bias.

All comparisons

Featured comparison

Best AI Coding IDE

Cursor vs Windsurf vs Claude Code vs Aider vs Continue vs Copilot. Which AI-native editor is best for what kind of work?

CursorWindsurfClaude CodeAiderContinueCopilot

Verdict

Cursor or Windsurf for most engineers. Claude Code as the terminal companion. Aider/Continue for power users who want full control.

Read the full comparison
DimensionCursorWindsurfClaudeAiderContinueCopilot
Multi-file agentBestBestBestStrongLimitedSolid
Tab autocompleteBestStrongN/A (CLI)N/A (CLI)StrongBest
Model choiceStrong (multi)Strong (multi)Claude onlyBest (any)Best (any)GPT only
Open sourceNoNoNoYesYesNo
Pricing$20/mo Pro$15/mo Pro$20+/moBYO APIBYO API$10/mo

Prompt library

Prompts you can use today

Copy, paste, run. Tested across Claude, GPT, and Gemini.

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Productivity

After-Action Review

Run a structured retrospective on a project, launch, or incident.

Run an after-action review on the event below.

Event: {{describe what happened}}
Goal: {{what we set out to achieve}}
Result: {{what actually happened}}
Timeline: {{rough sequence of events}}

Output:

• What was supposed to happen — restate the plan clearly

• What actually happened — restate the outcome, with key moments

• Why it diverged — root causes, not just symptoms (use "but why?" 3 times)

• What worked well — what to keep doing

• What didn't — what to stop or change

• What we learned — surprises, misconceptions corrected

• Action items — concrete changes for next time, with owners

Rules:

• Blameless tone — we're learning, not assigning fault

• Be specific — generic learnings ("we should communicate better") are useless

• Push back on conventional explanations — challenge assumed causes

• End with: "What would we do differently if we ran this again tomorrow?"
RetroReviewLearning

Coding

Agent Tool Spec Generator

Design a clean function/tool spec for an LLM agent.

Design a function specification for an AI agent.

What the function should do: {{description}}

Output a JSON Schema-style specification:
{
"name": "verb_noun" (snake_case, narrow),
"description": "What it does + when to call it + return shape (1-3 sentences)",
"input_schema": {
"type": "object",
"properties": {
"field": {
"type": "string|number|boolean|object|array",
"description": "What this field is, valid values, defaults",
"enum": ["..."] (if applicable)
}
},
"required": ["..."]
}
}

Then list:

• Failure modes — what could go wrong; what error messages should be returned

• Idempotency — is the function safe to retry?

• Side effects — what changes in the world when this runs?

• Suggested guardrails — confirmation prompts, rate limits, scope restrictions

Rules:

• Narrow scope — one verb, one noun

• Strong typing — no "any" types

• Self-describing — model should be able to use it correctly first try
AgentTool UseSpec

Coding

Generate Unit Test Cases

Generate edge-case-aware unit tests from a function signature.

Generate unit tests for the function below.

Cover:

• Happy path (with realistic input)

• Boundary cases (empty, single element, maximum size)

• Invalid input (null, wrong type, malformed)

• Edge cases specific to this domain (think hard — what would a senior reviewer flag as untested?)

Use {{test framework}}. Each test gets a descriptive name. Group by category.

Function:
"""
{{paste function}}
"""
TestingCoding

Learning paths

From beginner to building

Multi-week roadmaps for each direction AI can take you.

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  1. Path · 01Advanced

    AI Agent Builder Roadmap

    The path from 'I built a chatbot' to 'I built an agent that runs unsupervised.' For builders, not lurkers.

    10–12 weeks · 6 stagesStart
  2. Path · 02Intermediate

    AI Automation Engineer Roadmap

    Become the person who turns manual workflows into AI-powered automations. Highly hireable, instantly useful.

    8–10 weeks · 5 stagesStart
  3. Path · 03Beginner

    AI Beginner Roadmap

    Zero to genuinely capable. The path I'd give my smart non-technical friend who wants to actually use AI well.

    4–6 weeks · 5 stagesStart
  4. Path · 04Intermediate

    AI Coding Roadmap

    Become 3x more effective with AI in your daily coding loop. Aimed at working engineers.

    4–6 weeks · 5 stagesStart
  5. Path · 05Beginner

    AI Creator Roadmap

    For writers, YouTubers, podcasters, and indie creators. Use AI to do more, better, faster — without becoming AI slop.

    6–8 weeks · 6 stagesStart
  6. Path · 06Intermediate

    AI Engineer Interview Prep Roadmap

    Four-week plan to go from 'I know the basics' to 'ready for AI Engineer onsite loops at competitive companies.' Daily-deliverable structure.

    4 weeks · 4 stagesStart
  7. Path · 07Intermediate

    AI Product Manager Roadmap

    Ship AI features users trust — without pretending to be an ML engineer. An 8-week path for PMs who need to spec, evaluate, and launch AI products in 2026.

    6–8 weeks · 8 stagesStart
  8. Path · 08Advanced

    MLOps / LLMOps Engineer Roadmap

    Take LLM features from prototype to production — evals, observability, deployment, guardrails, and cost control. A 10-week path for engineers owning AI in prod.

    8–10 weeks · 10 stagesStart

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