مهندسی پیشرفته ایجنت‌ها : راهنمای عملی برای توسعه‌دهندگان حرفه‌ای

عنوان دوره : Maven – Hardcore Agentic Engineering for builders who ship

سطح : متوسط

زمان کل دوره : 17 ساعت و 59 دقیقه

تعداد فايل ها : 9

سال آموزش : 2026

فایل تمرینی : دارد: ZIP (1)

مربی دوره : Greg Ceccarelli

نرم افزار : –

زیرنویس انگلیسی : ندارد

Maven – Hardcore Agentic Engineering for builders who ship

Driving agents effectively is the engineering skill that matters most right now.

What you’ll do
Build a real agentic harness in 3 weeks from an initial loop to a verified deterministic gate
Brief the goal, steer the run, verify the result: in class, then on your own repo each week. You’ll ship on Demo Day.
Why this matters

Everyone worries AI makes engineers worse. After two years building entirely with agents, we’ve found the opposite: a high-ceiling skill is forming: driving agents to produce work, then engineering the proof it’s correct.

The split isn’t who uses AI; everyone does. It’s engineering your mindset, process, and harness versus letting agents ship slop.

Agentic Engineering where the unit of review is a goal, not a diff is a brand-new practice.

The courses that do exist teach the easy part: idea to prototype in minutes.
The hard part: making an agent’s code correct, yours to understand, and safe to ship over months is what almost no one can teach, because few have done it for real.
We have, entirely by driving agents (what we build at SpecStory, used by 200K+ engineers). And you’ll learn it live in a build room we made: Stoa, not Zoom.

What you’ll learn
Build an agentic harness end-to-end, hands on, and walk away able to brief the goal, steer the run, and verify on your own repo confidently.

Engineer a brief an agent can run unattended via Goals

Author a capped goal + bounded rider with named checks before any code, so “done” is a check that passes or fails not a feeling.

Compile plain-English “done” into runnable checks the harness runs each turn and compare with model judges.

Build and reuse a custom Agent Skill so Goal Engineering is one repeatable command and judge when a full goal+rider is overkill

Verify against what the agent can’t internally assess with calibrated distrust.

Re-derive an agent’s “it passed” from what it didn’t write with the running binary, the real exit code, the actual bytes.

Stand up a separate gate holding a secret the agent can’t read, and watch it refuse a forged “accepted” marker.

Drive an agent to find a real bug in a read-only, zero-edit turn, so you judge its reasoning before you trust the fix.

Steer the run live: be the operator, not a tokenmaxxer of slop.

Kill a wrong run at the first bad move with one asserted fact, instead of debugging a path it already ran down.

Redirect a stuck agent by pointing it at working code and a full SHA range, not by re-explaining yourself in prose.

Read your interrupt rate from your session histories, and feel a runaway coming before it costs you hundreds in tokens.

Engineer the context your next solo agent (or team’s agent) runs on

Write a hand-off doc a stateless agent ships from every claim pinned to a file:line or a re-runnable command.

Send a 20-read investigation to a side-agent that returns only a summary, keeping your main window out of the 40% “dumb zone.”

Keep an AS-BUILT map per subsystem and durable state in files, not chat, so a crash or fresh context window loses nothing.

Learn how to orchestrate agents for specific outcomes.

Develop judgement to distinguish between what Claude or Codex is best at, what effort to use, when to use a goal, workflow or agent team.

Fan out across git worktrees in look-don’t-touch lanes that can’t collide and know when parallel agents add intent and cognitive debt.

Apply a semantic rebase. Delete and regenerate a tangled branch from a clean base, lessons kept, instead of patching the mess.