Agentic Workflows — Mastery1 / 8
The Agentic Workflow Mindset
Most developers treat AI like a smarter autocomplete. The ones who pull ahead treat it like a teammate that acts. Here is the mental model.
Most developers treat AI like a smarter autocomplete. The ones who pull ahead treat it like a teammate that acts on the repository, runs the tests, and reports back.
Assistance vs. agency
Autocomplete and chat are assistance: you stay the hands, the AI suggests. An agentic workflow gives the model agency inside guardrails you set — it reads files, runs commands, edits code, and verifies results, pausing only when it hits something irreversible or ambiguous.
The shift is not "better prompts." It is moving the work from a chat tab into your terminal and repo, where the agent has the same context and tools you do.
The four habits
- Give it the project, not a paragraph. Point the agent at the codebase and a
CLAUDE.mdof conventions. Context beats cleverness. - Let it run, then review. Approve a tool allow-list once; stop babysitting every step. Review the diff, not the keystrokes.
- Make rules deterministic. Anything that must always happen (format, lint, secret-scan) belongs in a hook, not a polite request.
- Delegate the deep dives. Spin a subagent for a focused, context-heavy task so your main thread stays sharp.
What this series covers
Over the next articles we wire up the daily-driver setup: MCP servers to connect your tools, hooks to enforce your rules, custom slash commands to package team workflows, and subagents to parallelize. By the end you will chain them into pipelines that take a ticket to a reviewed branch with you in the loop only where it counts.
The rest is mechanics — and mechanics are exactly what the next seven articles are about.
Series — Agentic Workflows — Mastery
- Part 01The Agentic Workflow Mindset — you are hereMost developers treat AI like a smarter autocomplete. The ones who pull ahead treat it like a teammate that acts. Here is the mental model.
- Part 02MCP Servers 101 — Give Your Agent Real ToolsThe Model Context Protocol is how your agent stops guessing and starts querying your database, your issues, your browser. Here is the mental model and the first connection.
- Part 03Build Your First Custom MCP ServerOff-the-shelf servers cover GitHub and Postgres. The high-leverage one is the server only you can write — the bridge to your own system.
- Part 04Hooks — Make the Agent Obey Your RulesA prompt asks the model to remember. A hook makes it happen — deterministically, every time, outside the model's control.
- Part 05Custom Slash Commands as Team WorkflowsA custom slash command is a reusable prompt you commit to the repo — so the whole team runs the same high-quality instruction instead of re-typing it.
- Part 06Subagents — Delegating Work That ScalesOne giant context gets slow and vague. Subagents let the main agent hand focused work to specialists with their own context and tools — and run them in parallel.
- Part 07The Daily-Driver Setup — Settings, Permissions, Status LineThe difference between fighting the agent and flowing with it is twenty minutes of configuration you do once. Here is the setup.
- Part 08Multi-Tool Pipelines — Ticket to Reviewed BranchThe payoff: chain MCP, hooks, commands and subagents into one flow that takes a ticket to a reviewed branch — with you in the loop only where it counts.