Tag

Cost Reduction

Articles about "Cost Reduction"

3 articles

Should You Cancel Your Expensive SaaS and Build It Yourself? Seven Tests for the AI Era

For IT heads, corporate planning teams, and CFOs who opened a SaaS renewal quote and thought "we could build this for less," here are seven tests for deciding whether to cancel a SaaS you already pay for and build a replacement in-house: price increases and currency exposure, per-seat pricing growth, how slowly the data and features change, legal and accounting complexity, the number of integrations, who will maintain it, and the cancellation and migration terms. It does not hide the evidence on the other side, including public guidance that favors SaaS and research showing AI-assisted development can be less stable. The first article in a five-part series.

2026-09-29Ryuta Hamamoto

WARP

Five-Year SaaS TCO | How Price Hikes and a Weak Yen Move the Build-vs-Buy Break-Even

When a SaaS renewal quote makes you think building it yourself would be cheaper, the number to put in the approval request is a five-year total, not the annual fee next to a development estimate. Using the actual track record of vendor price increases and the weak yen, and the lifecycle-cost principle in Japan's Digital Agency guideline DS-310, this article works through a model case of a Japanese company (300 users, $60 a month, ¥160 to the dollar, all our own assumptions) with maintenance, security, and people included, and tables the variables that move the break-even point.

2026-09-29Ryuta Hamamoto

ZEROCK

Five Ways to Cut AI Coding Agent Costs While Keeping Data In-Country

Coding agents such as Claude Code, Codex and Grok Build have grown heavy, and token bills are becoming a board-level topic. Using only what official documentation confirms, this piece lays out five ways to bring the cost down: switching the model an agent talks to, open-source agents such as OpenCode and Hermes Agent, open-weight models from China, NVIDIA, Google and others, domestic serverless inference such as Sakura's AI Engine, and on-prem operation on hardware such as DGX Spark or Mac Studio. It explains the pitfalls of each and, for newcomers, the idea of an AI gateway that cuts cost while keeping data in-country.

2026-09-12Ryuta Hamamoto

3 articles

WARP

Should You Cancel Your Expensive SaaS and Build It Yourself? Seven Tests for the AI Era

For IT heads, corporate planning teams, and CFOs who opened a SaaS renewal quote and thought "we could build this for less," here are seven tests for deciding whether to cancel a SaaS you already pay for and build a replacement in-house: price increases and currency exposure, per-seat pricing growth, how slowly the data and features change, legal and accounting complexity, the number of integrations, who will maintain it, and the cancellation and migration terms. It does not hide the evidence on the other side, including public guidance that favors SaaS and research showing AI-assisted development can be less stable. The first article in a five-part series.

2026-09-29Ryuta Hamamoto

WARP

Five-Year SaaS TCO | How Price Hikes and a Weak Yen Move the Build-vs-Buy Break-Even

When a SaaS renewal quote makes you think building it yourself would be cheaper, the number to put in the approval request is a five-year total, not the annual fee next to a development estimate. Using the actual track record of vendor price increases and the weak yen, and the lifecycle-cost principle in Japan's Digital Agency guideline DS-310, this article works through a model case of a Japanese company (300 users, $60 a month, ¥160 to the dollar, all our own assumptions) with maintenance, security, and people included, and tables the variables that move the break-even point.

2026-09-29Ryuta Hamamoto

ZEROCK

Five Ways to Cut AI Coding Agent Costs While Keeping Data In-Country

Coding agents such as Claude Code, Codex and Grok Build have grown heavy, and token bills are becoming a board-level topic. Using only what official documentation confirms, this piece lays out five ways to bring the cost down: switching the model an agent talks to, open-source agents such as OpenCode and Hermes Agent, open-weight models from China, NVIDIA, Google and others, domestic serverless inference such as Sakura's AI Engine, and on-prem operation on hardware such as DGX Spark or Mac Studio. It explains the pitfalls of each and, for newcomers, the idea of an AI gateway that cuts cost while keeping data in-country.

2026-09-12Ryuta Hamamoto