agentic

DE//AGENT currently lists 11 resources under agentic: 8 tutorials, 2 references, 1 pattern. Everything below is derived from the live registry — counts, capabilities, verification state and security posture come from the curated records, never from marketing copy.

Documented learning objectives across these resources:

• Separate agent read/recommend from write/execute — via Keep an agent read-only until a human approves
• Encode the safety policy as hooks — via Keep an agent read-only until a human approves
• Keep a human gate on anything irreversible — via Keep an agent read-only until a human approves
• Name the four parts of an agent — model, tools, loop, guardrails — via What makes an agent — model, tools, loop, guardrails
• Identify each part in a real registry agent — via What makes an agent — model, tools, loop, guardrails
• Say where DE agents fit — review, triage and planning under guardrails — via What makes an agent — model, tools, loop, guardrails
• Explain where hooks run — on tool-call and pre-run events, outside the model — via Hooks — deterministic gates around an agent
• Match each safety hook to the failure it prevents — via Hooks — deterministic gates around an agent

16 more objectives live on the individual resource pages.

These resources map to stage: Agentic Data Engineering (11). Follow the four-phase roadmap to place this topic inside a progression instead of learning it in isolation.

Every entry, its shape and its trust state — sorted by the registry's composite score. This table is the honest version of a marketing comparison: no sponsored placements, no unverifiable claims.

How scores are computed: source quality score.

Highest composite score first:

1. Agent-in-the-Loop Review score 35.75 — intermediate
2. Keep an agent read-only until a human approves score 34.15 — beginner
3. What makes an agent — model, tools, loop, guardrails score 34.15 — beginner

Scores rank provenance, completeness and trust — read how verification works before adopting anything.

Start here if you're new: Keep an agent read-only until a human approves, What makes an agent — model, tools, loop, guardrails.

Reach for these with production experience: Capstone — the guarded agent checklist, Production gotchas — untrusted content, destructive actions, permission scope, When an agent does the wrong thing — contain, audit, postmortem.

Known limits: A purely local sandbox with no real data (Agent-in-the-Loop Review)

• Agent-in-the-Loop Review — Coding agents can do real data-engineering work, but can also ship a schema change or drop a table. details
• Keep an agent read-only until a human approves — Coding agents can do real data-engineering work, but can also ship a schema change or drop a table. Walk the Agent-in-the-Loop Review pattern: separate read/recommend from write/ex… details
• What makes an agent — model, tools, loop, guardrails — Build the map before touching anything: an agent is a model that reasons, tools that act, a loop that iterates, and guardrails that bound it. Meet a real data-engineering agent fro… details
• Hooks — deterministic gates around an agent — The model can be talked into anything; a hook is code on the tool path. Walk the four safety hooks every data repo should know — destructive-SQL guard, prod write confirmation, sec… details

Adjacent topics: tutorial (8 shared), guardrails (4 shared), review (3 shared), security (3 shared), skills (2 shared), format (2 shared).

Study path: the roadmap places this topic in a progression · the scoring model explains the numbers · the trust rule catalog shows every security check these entries passed through.