Guides
Long-form playbooks from real engagements. No fluff, no vendor takes.
The AI Sprint Playbook
How we ship a working AI system in a two-week sprint — Day 5 demo, Day 10 ship — and what we ask of you to make it possible.
The AI Readiness Checklist
Twelve things to true up before you spend a dollar on an AI project — from data hygiene to executive sponsorship.
RAG vs Fine-Tuning: A Practical Decision Guide
Pick the right architecture for the right problem — without ending up with both, neither, or the wrong one.
Evals That Actually Catch Regressions
Most AI eval suites are theater. Here is how to build ones that block bad releases and reward the right wins.
How to Choose an LLM in 2026
A no-vendor-loyalty guide to picking between Claude, GPT, Gemini, Llama, and the open-source pack.
Cutting Your AI Bill in Half Without Losing Quality
Real tactics — model routing, caching, batching, and prompt surgery — that ship 50%+ cost savings.
The AI Sprint Brief Template
The one-page brief we fill in with every client before writing a line of code. Use it to scope your project, brief a vendor, or build the internal case.
AI Workflow Audit: 12 Questions Before You Build
Run this 12-question audit on any workflow before committing to a build. Each "no" is a risk. Three or more means fix the gap first.
50 AI Prompts for Business Teams
50 copy-paste prompts for email, meetings, analysis, content, and proposals. Tested on ChatGPT, Claude, and Gemini.
The Blog
Shorter posts on what is and isn't working in production AI.
AI Glossary
Plain-English definitions for the terms that matter.
AI Agent
A model that takes actions in a loop until a goal is met, not just one reply.
RAG (Retrieval-Augmented Generation)
Look up relevant documents first, then ask the model to answer using them.
Embeddings
Numerical representations of text so a computer can measure meaning by distance.
Vector Database
A database optimized for storing embeddings and finding the nearest matches fast.
Context Window
How much text (in tokens) you can feed the model in one request.
Tokens
The chunks of text models count and bill by — usually 3-4 characters each.
Prompt Library
Battle-tested prompts we actually use with clients.
Turn a meeting transcript into a structured summary
For: ops, EAs, founders. Output: TL;DR, decisions, action items with owners, open questions.
Write a cold outbound email that doesn't sound like spam
For: sales, founders. Output: a 5-sentence email a real person would actually reply to.
Generate a PR description from a diff
For: engineers. Output: clean PR description with summary, test notes, and risk callouts.
Rewrite anything shorter without losing meaning
For: writers, marketers. Output: 30-50% shorter, same point.
Draft a job description from a few bullet points
For: HR, founders. Output: a JD that attracts the right people, not 800 wrong people.
Extract structured data from unstructured text
For: developers, ops. Output: clean JSON ready to insert into a database.
AI Comparisons
Honest head-to-heads. Pick the right tool, not the loudest one.
Claude vs ChatGPT (2025)
Both are excellent. They are excellent at different things.
Gemini vs ChatGPT (2025)
Gemini wins on context length and price. ChatGPT wins almost everywhere else.
RAG vs Fine-Tuning
Use RAG to teach a model new facts. Use fine-tuning to teach it new behavior.
OpenAI API vs Anthropic API
OpenAI has the bigger toolbox. Anthropic has the more reliable model.
Self-Hosted LLM vs API
Almost nobody should self-host. The few that should, know it.
LangChain vs LlamaIndex (2025)
LangChain for general agent pipelines. LlamaIndex for anything document and retrieval heavy.
Pinecone vs Weaviate
Pinecone is the fastest zero-ops option. Weaviate gives you more control and hybrid search out of the box.
OpenAI API vs Azure OpenAI
Same models, very different enterprise posture. Azure if you need compliance, OpenAI if you need speed.
Cursor vs GitHub Copilot (2025)
Cursor is the better AI coding IDE. Copilot is the better AI coding plugin if you want to stay in your editor.
AI Agents vs Chatbots
Chatbots answer questions. Agents take actions. The distinction matters enormously for what you build.
OpenAI o3 vs Claude Opus 4
Both are frontier reasoning models. o3 edges ahead on hard math and code. Opus 4 edges ahead on writing and long-context analysis.
GPT-4o vs Claude Sonnet 4
These are the two primary workhorses. GPT-4o for breadth and multimodal. Claude Sonnet for writing and long-context.
LangChain vs LangGraph
LangChain for simple linear pipelines. LangGraph for stateful, multi-step, multi-agent workflows.
Vector Database Comparison: Pinecone vs Weaviate vs Qdrant vs pgvector
Managed is faster to ship. Self-hosted is cheaper at scale and gives you compliance control.
ChatGPT vs Gemini (2025)
ChatGPT is more reliable and has a better ecosystem. Gemini is cheaper with a much larger context window.