Loop Engineering
Playbook
Turn one-off AI help into workflows that act, check, retry, and stop before they create damage.
The loop is not the hard part.
Prompt engineering taught us to ask. Context engineering taught us what to feed the model. Loop engineering is the next rung.
A loop is simple: goal, context, action, check, retry. The real work is deciding what counts as done before the agent starts moving.
If you corrected the same AI behavior three times, stop improving the prompt and build the loop around it.
This is the spark for the guide: move from one-off prompting to agents that can act, check, and stop.
Get the practical loop map
Use-case chooser, loop shapes, verifier ladder, human gates, templates, examples, and the 7-day build track.
What You Get
The Verifier Ladder
The Learning Path
One loop, many jobs
Who This Is For
The Parts Most People Skip
Loops are easy. Choosing the right loop is the hard part.
Closed before open
Start with fixed paths, clear triggers, and pass/fail checks. Open exploration comes later. Patch the smallest failed section or diff because full rewrites create drift.
Operator minutes
Track supervision time, not only model cost. A cheap model call with 20 minutes of steering is still expensive.
Human checkpoints
Relationship, money, legal, auth, and brand decisions need approval gates, not blind autonomy.
Built From Real Loops
Content validator
Draft, scan for banned phrases, score quality, revise until the threshold clears.
Research cleaner
Find sources, reject dead links, keep claims only when evidence is present.
Sales follow-up gate
Read the conversation, draft the next message, check tone and facts, wait for approval.
Code proof contract
Tests, build, and reviewer verdicts decide whether a change ships.
Pair This With the Right Resource
Loop engineering is the control layer. These resources cover the adjacent pieces: context, cadence, first agents, and real system examples.
Context Engineering Guide
Use this before a loop. It shows how to give agents durable instructions, memory, tools, and context so each run starts from the right place.
Open guideAI Work Cycle Skill
Use this as the operating cadence inside a loop: Plan, Work, Review, Triage, Learn. It is the reusable loop pattern in skill form.
Get skillFor scheduled briefing loops that read calendar, email, pipeline, and priorities.
For turning one loop into a working agent with a clear job and tools.
For executive loops: decisions, metrics, meetings, follow-ups, and weekly reviews.
For seeing how memory, agents, and routing fit together in the full system.
Iwo Szapar
- Co-founded the AI Maturity Index with Harvard researchers. Acquired by ISG in 2026.
- Led training and change management projects at Microsoft, ING Bank, Walmart.
- Up-skilled 25,000+ professionals through Remote-how Academy.
Get the Playbook
Free guide for choosing, designing, and controlling AI loops that prove their work.
Loop Engineering Fits Inside a Second Brain
The playbook teaches the loop. Second Brain 2.0 gives that loop memory, agents, tools, and a place to store the lessons each run produces.
The complete Claude Code system. 30+ agents, memory that compounds, pre-configured MCPs.
DIY $197 / Kickstart $597 / DWY $2,497
See PackagesA companion skill for Plan, Work, Review, Triage, and Learn. Use it with this playbook.
Get the Skill