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603 articles

Business DX2026-07-12
Using ChatGPT and Other AI Tools at Work — Data Risks and How to Set Company Rules
A neutral look at the real risks of using ChatGPT and similar AI tools at work, why outright bans can backfire, and five minimum rules for a practical internal policy.
AI経営中小企業DX社内ルール
Business DX2026-07-12
What Work to Delegate to AI (and What Not To) — The Real Test Is the Cost of Being Wrong
How to decide what to delegate to AI using a cost-of-error and ease-of-verification framework, with typical tasks to delegate, tasks to keep human-owned, and how to expand delegation gradually.
AI経営中小企業DX業務設計
Business DX2026-07-12
How to Find Subsidies for AI Adoption: Types of Programs and What to Check Before Applying
A neutral guide to subsidy programs SMBs can use for AI adoption in Japan: program types, what tends to qualify, a pre-application checklist, and why subsidy-first projects often fail.
AI経営中小企業DX補助金
Business DX2026-07-12
The Answer to 'We Don't Have AI Talent': Building a Structure Without a Dedicated Hire
A neutral guide for SMBs who feel they lack AI talent: common misconceptions, a comparison of team structures, and how to choose your first internal AI champion without hiring a specialist.
AI経営中小企業DXAI人材
Software Development2026-07-11
Command Code Deep Dive — the "taste-1" Model That Continuously Learns From Developer Accept / Reject / Edit Behavior, With 15+ LLM Providers Supported and a $1/Month Pro Entry Point Plus $10 in Free Credits A Terminal AI Coding Agent Claiming "Code 10× Faster, Reviews 2× Quicker, 5× Fewer Bugs"
Command Code is a terminal AI coding agent whose proprietary "taste-1" model combines LLMs with continuous reinforcement learning from developer behavior. Core differentiator: capture coding preferences from accept / reject / edit actions, producing output that increasingly matches your architectural patterns, naming conventions, and coding style. Key features: (1) continuous learning system — preferences captured from developer decisions, (2) multi-mode operation — interactive CLI, headless mode, sandbox environment, (3) built-in tools — file ops, shell commands, grep, extended thinking, (4) project-level skills + persistent memory across sessions, (5) team collaboration — npx taste push/pull share skill registries within a team, (6) design partnership mode — 17+ operational variants, (7) MCP server support. LLM coverage: 15+ providers including Anthropic / OpenAI / Google / DeepSeek / Qwen / MiniMax. Pricing: free tier for individuals, Pro from $1/month + $10 free credits (which stretches to $40-$100 depending on model), team plans with additional seats and shared skill registries. Install: npm i -g command-code. Claimed performance: "Code 10× faster. Reviews, 2× quicker. Bugs 5× fewer" — per-developer personalization breaking through the ceiling of generic output. Positioning: a direct competitor to Claude Code, Cursor, and Codex, but with "individual-personalization learning" as the differentiation axis.
Command Codetaste-1AI Coding Agent+3
Software Development2026-07-11
The "grill-me" Skill Deep Dive — Matt Pocock's 3-Line Agent Skill That Has AI Coding Agents Ask 18–24 Sequential Questions Until Full Alignment, Eliminating the "Plan → Build → Re-Plan" Inefficiency Loop A Read-Through of the Zenn Article (ryonakae), Best Paired With Opus 4.6 / Sonnet at Medium Effort
Matt Pocock's "grill-me" is an Agent Skill that fundamentally changes AI coding-agent behavior with just three lines of instruction (Zenn writeup by ryonakae). The core mechanic: the agent doesn't generate code immediately — instead, it asks sequential, thorough questions until full mutual understanding, presenting 2–5 options per question. The article's author reports 18–24 questions per session, progressively deepening understanding of project scope, dependencies, and design decisions. When the questioning ends, implementation proceeds frictionlessly from the established context. Problem solved: fundamentally eliminates the token-and-time waste of the traditional plan-mode loop ("plan → build → modify plan → rebuild"). Advantages: (1) no plan-modify-replan cycles, (2) full human–AI alignment before any code is written, (3) session history serves as natural implementation documentation. Recommended environment: Opus 4.6 or Sonnet at medium effort. Downside: the extended questioning phase causes real mental fatigue — the author's argument is that it prevents bigger problems downstream. Positioning: grill-me is a practical implementation of Anthropic Claude Skills, sitting alongside Command Code's Design Partnership Mode and Crit.md's HITL review as another example of the "HITL assistant, not full autonomy" family.
Agent Skillgrill-meMatt Pocock+3
Software Development2026-07-11
Mosaic (mosaic.inc) Deep Dive — Run Many Claude Code / Codex / OpenCode Sessions in Parallel From One Desktop, Plus SHARED CONTROL for Multiple People Live-Editing a Single Claude Code Session, With Git-Worktree-Isolated Workspaces That Never Collide — a New Option Alongside Conductor / Superset / Herdr in the Late-2026 Parallel-Agent Ops Stack
Mosaic (mosaic.inc) is a desktop tool that runs multiple AI coding agents (Claude Code / Codex / OpenCode) in parallel from a single UI, and on top of that offers "SHARED CONTROL" — a rare feature in 2026 that lets multiple people live-edit a single Claude Code session together. The core of SHARED CONTROL: spin up a session, a teammate joins the same terminal, and you both see each others cursors, prompts, and output in real time — genuinely shared control, not screen-share theater. The experience of Google Docs or VS Code Live Share, applied to a Claude Code session. Use cases (see the standing request in Anthropic issue #60082): pair programming, team debugging, onboarding, live review, and division of labor (Ali refactors the auth middleware while Shubham adds the rate-limit test — same session). Parallel-ops layer: each agent gets a Git-worktree-isolated workspace, and 5-10 agents can develop different branches / features concurrently with zero file collisions or state interference. Position: in the rapidly maturing late-2026 parallel-Claude-Code market, Mosaic competes with Conductor (YC, Mac-native), Superset (three ex-YC CTOs, 10+ concurrent), Herdr (terminal-native, Rust), and Product-Hunt entries like Claudy / Multi-Claude — its distinctive differentiation is real-time SHARED CONTROL. Target users: solo developers, startup CTOs, staff engineers, plus teams that want pair programming and live review with AI agents in the loop. Combined with Command Code taste-1 learning, the grill-me skill, and Crit.md HITL review, it forms a "parallel × personalized × thoroughly reviewed × real-time collaborative" late-2026 AI dev stack.
MosaicClaude CodeParallel Agents+4
Business DX2026-07-10
The Complete First-Time Guide to Ordering System Development: Costs, Choosing a Vendor, and Avoiding Failure
A complete guide to ordering system development for the first time, covering all eight stages from problem definition to vendor selection, quoting, contracts, and maintenance.
システム発注中小企業DX発注ガイド
Business DX2026-07-10
System Development Costs: Price Ranges by Scale and How Pricing Is Determined
A breakdown of typical system development costs by project scale and type, explaining how person-month pricing works, red flags in cheap quotes, and ways to control costs.
システム発注中小企業DX費用相場
Business DX2026-07-10
System Maintenance Cost Benchmarks — Understanding the "Percentage of Development Cost" Rule and What's Fair
System maintenance cost benchmarks: the reasoning behind the 'percentage of development cost' rule, annual ratio tables by system type, what to check in a breakdown, and the risks of running without a contract.
システム発注中小企業DX保守費用
Business DX2026-07-10
How to Read a System Development Quote — Line Items, Person-Month Rates, and Overhead Costs to Check
A neutral guide to reading a system development quote: typical structure, how to interpret person-month rates, watch-outs for "lump sum" items, and how to compare multiple vendor quotes.
システム発注中小企業DX見積書
Business DX2026-07-10
7 Ways to Reduce System Development Costs — Phased Development, MVPs, and Subsidies
A neutral guide to 7 practical ways to reduce system development costs, from scoping requirements to phased development, subsidies, and multi-vendor quotes.
システム発注中小企業DX費用相場
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