Hello Agentic Coding
AI coding was phase one. Agentic coding is phase two. Engineering was never about writing code — it is about building systems of leverage. The goal: become a commander of compute who builds systems that build systems.
Core Thesis
Phase One — AI Coding
Using LLMs to autocomplete, generate, or assist with code. The developer still types, still reviews line by line, still owns the cursor. This phase is over as the primary competitive edge.
Phase Two — Agentic Coding
You plan, review, and architect closed-loop structures. LMs in agent architectures do the coding. Your hands and mind are no longer the best tools for writing code — they are the best tools for commanding compute.
Tactic #1 — Stop Coding
The Rule
Do not type a single line of code throughout TAC. Your hands and mind are no longer the best tools for writing code. LMs in agent architectures are superior coders. Your new role is planning, reviewing, and building closed-loop structures.
Daily Actions
- →Resist the urge to type code manually — catch yourself before you start.
- →Go all in on agentic coding tools as your primary execution layer.
- →Write prompts and review output instead of coding directly.
- →Communicate to agents what you want built — spec first, then review.
The Core Four
Upgrade the classic AI coding trio (Context, Model, Prompt) by adding Tools as a first-class variable. Reliable tool execution unlocks long-running agentic workflows.
What the agent knows. CLAUDE.md, memory, prior output, file ownership.
Which LM executes. Capability ceiling for reasoning, tool-calling, context window.
The spec. Precision here multiplies output quality across the entire thread.
What the agent can do. File I/O, bash, web fetch, MCP servers, APIs.
Primary Tool: Claude Code
Long-Running Workflows & Thread Types
The atomic unit of agentic engineering is a thread: Prompt → Tool Calls → Review. Progress is measured in tool calls per unit of your attention, not lines of code. Seven thread types cover the full spectrum from single cycles to 26-hour autonomous runs.
Four improvement levers
Programmable Agentic Coding & The Compute Advantage
Compute Advantage Equation
(Compute Scaling × Autonomy) / (Time + Effort + Money)Higher ratio = bigger competitive edge. Every tool, workflow, and architecture decision should be evaluated through this lens. Small compute increases produce exponential output — doubling x from 10 to 20 multiplies effective value ~22,000x.
The Year of Trust — Top 2% Roadmap
Success in agentic coding scales directly with how much you trust your agents. More trust → more delegation → faster iteration → compounding advantage. The bottleneck is not model capability — it is your willingness to delegate.
Progression
10 Strategic Bets
The Paradox
"To become irreplaceable, replace yourself."
Delegate every task you can to an agent. What remains — judgment, architecture, taste, trust calibration — is the work only you can do. That residual is your competitive moat.