Longer reads on choosing and deploying AI tools
Comparisons, deployment guides and the occasional opinion — including the parts that only apply when the company is in Japan.
Why AI rollouts fail in Japanese companies — four structural reasons
It is almost never the tool. Four organisational patterns that kill AI adoption inside Japanese companies, and what the ones that succeed do differently.
Enterprise AI rollout checklist — SOC 2, ISO 27001, DPAs and personal data
The questions to answer before a company-wide AI deployment: certification, data processing agreements, identity, audit logs, personal data handling, and what changes if the entity is in Japan.
Japanese-developed LLMs for business — ELYZA, Sakana AI, NTT tsuzumi and PLaMo
When a domestically developed Japanese LLM is the right answer, when it is not, and what the four main options actually offer a company deploying in Japan.
AI coding tools compared — Cursor, Copilot, Claude Code, Windsurf and Codeium
What the five main AI coding tools cost, what you actually get at each tier, and which one survives a team rollout rather than just an individual trial.
The best AI meeting note tools in 2026 — and whether you need Copilot for it
Seven meeting transcription tools compared on accuracy, speaker identification, CRM integration and privacy — including when the bot joining the call is itself the problem.
Cursor vs Windsurf — two VS Code forks, five dollars apart
Both are AI-native editors built on VS Code at nearly the same price. What actually separates Composer from Cascade, and which one to pick.
Claude Code vs Cursor — terminal agent or AI-native editor?
Two different shapes of the same idea. When a terminal agent beats an editor, when it does not, and why plenty of developers pay for both.
ChatGPT Enterprise vs Azure OpenAI — product or platform?
One gives your company a finished assistant. The other gives your engineers an API in your own cloud. The choice is about who does the building.
A shadow AI policy that works — permit it safely instead of banning it
Blanket bans push AI usage underground, where you cannot see it. A policy template that sets boundaries people will actually follow.
When not to use AI coding tools — five situations where they cost you time
AI coding assistants are a clear win most of the time. These are the cases where reaching for one makes the work slower, riskier, or both.
ChatGPT Plus vs Claude Pro — which $20 subscription should you buy?
Same price, different strengths. A straight answer by what you actually do all day, and when the right answer is both.
ChatGPT vs Gemini — has Google caught up?
Gemini's argument is not raw capability, it is where the model sits. What that is worth, and when it decides the choice.
Perplexity vs ChatGPT Search — which one for research you have to defend?
Both search and cite. The difference shows up when someone asks where a claim came from and you need the answer to hold.
GitHub Copilot vs Codeium — paid standard against the free option
Codeium is genuinely free for individuals and Copilot is $10. What that $10 buys, and when it is worth paying.
DALL·E 3 vs Midjourney vs Imagen — three image models, three jobs
Art quality, prompt adherence and ecosystem integration pull in different directions. Which to reach for by what you are making.
Midjourney vs Stable Diffusion — which is actually cheaper?
Free weights are not a free tool. What self-hosting Stable Diffusion really costs against a Midjourney subscription, and when each one wins.
Notion AI vs ChatGPT — why most teams end up with both
One can see your documents, the other can do almost everything else. The comparison is about context, not capability.
AI translation compared — DeepL, GPT, Claude and Gemini for Japanese
Dedicated translation engines against general LLMs, judged on business documents in and out of Japanese — and what each one gets wrong.
What an AI agent actually is — Devin, Cursor Agent and Claude Code in practice
The word covers everything from a chatbot with a tool to a system that opens pull requests. A working definition, and where the current tools actually sit.
Eight criteria for choosing an AI vendor — and how to run a proof of concept
What to weight when selecting an AI vendor, and a PoC structure that produces a decision instead of an opinion.
Calculating AI ROI — what a twelve-month payback actually requires
A model for estimating return on an AI deployment that survives a finance review, and the three assumptions that usually break it.
ChatGPT Enterprise vs Team — which one does your company actually need?
Team is $25 per seat and starts today. Enterprise is quoted and takes a procurement cycle. What the gap buys, and when you need it.
A workflow for AI pair programming — delegate, discuss, do it yourself
A three-tier model for deciding what to hand to the AI, what to think through with it, and what to write without it.
A one-person content pipeline — article, images and video with AI
How to produce article, visuals and a short video for one piece of content without a team, and which steps are still worth doing by hand.
Ten things Notion AI is actually good at — from meeting notes to OKRs
Concrete uses that justify the per-seat cost, and the ones where a general assistant does it better.
Putting AI into customer support — from ticket summaries to automated replies
A staged implementation that improves support without the failure mode everyone has experienced as a customer.
Claude Projects, properly — keeping team context in one place
How to set up Projects so the context actually helps, and the structure that makes them useful to a team rather than one person.
Business prompts that hold up — marketing, sales and HR
Prompt patterns that produce usable output in a work context, and the structure that makes them repeatable.
Using v0 with an existing design system
v0 generates shadcn/ui by default. How to get output that matches a design system you already have, and when to stop fighting it.
Figma AI vs Galileo — inside your file, or a file you import?
Both generate UI for designers rather than engineers. The difference is whether the AI lives in Figma or hands you something to bring into it.
Custom GPTs vs Claude Projects vs Gemini Gems — keeping context for a team
Three ways to stop re-explaining your situation at the start of every conversation, compared on sharing, file handling and depth.
Is prompt engineering over? What replaces it
Models got better at inferring intent, which killed the trick-based version of prompting. What survived is more valuable and harder to fake.
Seven design skills AI is absorbing, and five that got more valuable
An honest split for designers: what the tools now do adequately, and where human judgement became worth more rather than less.
An icon design workflow with AI in it
Where generation helps in icon work and where it actively hurts, with a loop that produces a consistent set rather than twenty unrelated images.
GitHub Copilot Workspace vs Cursor — issue-driven or editor-driven?
Two approaches to AI development: start from a GitHub issue and produce a pull request, or stay in the editor and move faster inside it.
Suno vs Udio — AI music for video, podcasts and ads
Two services at the same price producing full songs from a prompt. How they differ, and what the ongoing litigation means for commercial use.
AI OCR for invoice processing — choosing a service in Japan
What to evaluate when automating invoice handling: Japanese document accuracy, the accounting integration, and the retention rules you have to satisfy.
Sourcegraph Cody vs GitHub Copilot Enterprise — AI for a large codebase
Two enterprise coding assistants with different theories of context. Which one fits depends on how many repositories your engineers work across.
Perplexity Pro vs ChatGPT Plus search — paying twice for research?
If you already pay for ChatGPT, is a second $20 for Perplexity justified? It depends on one thing.
Security for LLM applications — the OWASP Top 10 in practice
The risks that actually appear when you build on an LLM API, and the controls that address them without theatre.
Choosing a flagship API — how to compare frontier models without the benchmarks
Model names change every few months. A durable way to choose between frontier APIs for a production workload, and the costs the pricing page does not show.
An RFP template for a generative AI deployment
The questions worth asking vendors, in the order they matter, with the ones that quietly disqualify marked.
Adobe Firefly vs Midjourney — which is safer for client work?
Licensing, training data and indemnification compared, for anyone whose generated images end up in paid work.
ElevenLabs vs CoeFont — synthetic Japanese speech compared
An international standard against a Japanese specialist. Which produces better Japanese narration, and which is easier to license for commercial use here.
Sora vs Kling vs Runway — generated video compared
Three video models with different strengths in length, motion quality and commercial availability — and the compliance question one of them raises.
Canva AI vs Adobe Express — design tools for people who are not designers
Two tools aimed at marketers and solo creators. What each one is genuinely good at, and which fits an existing Adobe workflow.
Jasper vs Writesonic vs Copy.ai — which writing tool, if any?
Three marketing writing platforms at very different prices, and the honest case for using a general LLM instead.
Azure AI Search vs Bedrock Knowledge Bases — choosing a RAG foundation
Two managed retrieval services from the two clouds most enterprises already use. What differs, and what decides it in practice.
Ollama vs LM Studio — running models locally, CLI or GUI
Two ways to run open models on your own machine. Which fits depends almost entirely on whether you want a command line or a window.
LangChain vs LlamaIndex — and whether you need either
Two frameworks for building LLM applications, compared on what they are actually for — plus the case for using neither.
Our Japanese edition has 50 articles. We are translating them one at a time — the full archive is available in Japanese.