Chapter 6 · Capstone: Build Your Harness · Lesson 6.5

Staying Current & Your Capstone

The field moves fast, so the durable skill is the ratchet mindset, not this month's tricks - here's how to keep it, and a capstone to prove it.

Chapter 0 · Sprint Zero
Chapter 1 · The ratchet & the practice loop
Chapter 2 · Spec-driven development in depth
Chapter 3 · Scaling & trusting the harness
Chapter 4 · Measuring & evolving the harness
Chapter 5 · Multi-agent & team harnesses
6.1 · Your starter harness
6.2 · One feature, end to end
6.3 · The first-week ratchet plan
6.4 · Adapt, don't copy
6.5 · Staying current & your capstone

Why "current" keeps moving

Here's the uncomfortable truth about a course on a fast-moving field: the exact setup you just learned will not be the state of the art for long. Three forces guarantee it. Models keep converging - the gap between them narrows every release (Lesson 0.1). The harness is disposable by design - a better model outgrows the scaffolding you built for the last one (Lesson 0.2). And the labs keep bundling the model and the harness together as a product - Harness-as-a-Service, where the loop and the plumbing come ready-made (Lesson 3.5, Cost, observability & HaaS). So memorising today's precise recipe is a losing game.

"The trick you learned this month is dead code next month; the ratchet mindset outlives every model."

What actually lasts

If the specifics expire, what's worth keeping? The way of thinking. Two ideas from this course don't age. The ratchet: every real failure earns a durable fix, and nothing goes in speculatively. And harness engineering: treating the scaffolding around the model as a first-class thing you deliberately tighten. Boiled down to a habit it's a short loop - measure, earn every line, enforce it, review it, and re-simplify on each model upgrade. That loop survives model churn because it never depended on any one model in the first place. Addy Osmani argues the whole discipline this way (Agent Harness Engineering), and Simon Willison's field guide (Agentic Engineering Patterns) is a living catalogue of the patterns the mindset produces.

Stay current

Follow the primary voices. Addy Osmani, Simon Willison, the My Experiments With AI substack, and the HumanLayer community. A handful of trusted sources beats chasing every hot take.
Watch your OWN eval set. When a new model lands, the honest signal isn't a benchmark tweet - it's what changed on your fixed set of real tasks. That tells you what to add and what to drop.
Re-simplify on every model upgrade. Rip out the scaffolding the new model no longer needs. A harness that only ever grows is one nobody is pruning.

The capstone challenge

You've done the parts. Now do the whole thing on something real. Over the next month, take one project from "prompt and hope" all the way to a measured, ratcheted, committed team harness - the full arc of this course, on your own work. The checklist:

Write the spec first - objective, scope, done-when - before any code.
Stand up a starter harness: a lean rules file and one or two sharp tools.
Run features through the loop and let it work.
Ratchet every failure into its cheapest durable home - a rule, a hook, or a reviewer.
Build a small eval set of real tasks so you can tell if a change actually helped.
Do review passes - a second agent, or a second model, over the same code.
Commit the harness to the repo so the team and every agent inherit it.
Prune the drift: cut unearned rules and stale scaffolding on the next model upgrade.

Check yourself

The durable skill worth keeping is -

Specifics expire - models converge and the harness is disposable. What lasts is the way of thinking: measure, earn every line, enforce, review, re-simplify. That outlives any single model.

On every model upgrade you should -

A better model outgrows old scaffolding. Rip out what it no longer needs - watch your own eval set to see what changed. A harness that only grows is one nobody is pruning.

Your capstone proves you can -

The capstone is the full loop on real work: spec first, starter harness, run features, ratchet failures, build an eval set, review, commit for the team, prune drift. Doing it end to end is the proof.

Your capstone (this month)

Two things, starting now:

Pick one real project and start the full-arc challenge above - spec first, then work the loop and ratchet as you go.
Join one community - the HumanLayer community, r/ChatGPTCoding, or Simon Willison's blog - and test your harness thinking on other people. Getting your earned rules critiqued is how they get sharper.

You've completed the course

One breath, the whole thing: the model is the commodity, the harness is your edge - and you learned to build it (Chapter 1: the ratchet), spec-drive it (Chapter 2: spec-driven development in depth), scale it safely (Chapter 3: sharp tools, sandboxes, cost and observability), measure it (Chapter 4: eval sets and golden tasks), work across agents & your team (Chapter 5: team harnesses and multi-agent orchestration), and make it yours (Chapter 6: your own starter harness, adapted not copied). Keep it lean, keep every line earned, treat it as disposable - and keep ratcheting. That's the whole job. Go build. It's been a pleasure teaching you.

Go deeper

Primary source (read this): Addy Osmani - Agent Harness Engineering. The essay this course is built around - return to it as the field moves.

Secondary: Simon Willison - Agentic Engineering Patterns. A living catalogue of current patterns, worth re-reading each time a new model lands.

Wisdom (test it on people): the HumanLayer community - the place to pressure-test what actually earns its keep in a harness, and what to prune.

I'm your teacher - and congratulations, you've finished the course. Want help scoping your capstone project down to something you can actually finish in a month, or a second pass on any lesson that still feels shaky? Ask me - that's exactly what I'm here for.

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