When you want an AI coding agent to get a layout right, the obvious move is to let it build the thing and look at the result. Build, eyeball, correct, rebuild. It feels productive. It is also the expensive way to iterate — because you are regenerating a full artifact every round to settle a disagreement that is really about the plan.
There is a cheaper path: have the agent show you its plan, annotate what's wrong, and let it generate the real thing only once. Here is the difference, with the math.
Where the tokens go
Agentic tools re-read and re-send a large context — your files, the conversation, tool output — on every turn, and that context is re-billed each turn. So total cost scales with two things: the number of turns a task takes, and the size of what gets generated on each of those turns. (For the longer version of this, see why AI coding agents burn tokens on visual bugs.)
Visual and layout work is brutal on both counts: it takes many turns to converge, and "build it so I can see it" regenerates a full artifact every single turn.
Two ways to validate a layout
Generate-to-validate (the default): the agent writes the real page, you render it, it's not quite right, you describe the fix, it regenerates. Repeat until the layout lands — typically several full builds.
Annotate-to-validate: the agent sketches its plan as a few labeled regions on the screen ("nav here, hero full-width, primary CTA, 3-up grid"). You correct the marks directly — which costs the agent nothing — it reads your feedback, and then builds the real thing once, correctly.
The model
Illustrative assumptions, stated plainly: a re-sent context of ~20,000 input tokens per turn; one full section generation at ~1,500 output tokens; a layout that takes ~4 build rounds to get right by eyeballing; a plan sketch at ~250 output tokens and a feedback read at ~500. Your numbers will differ — see the honest note below.
| Generate-to-validate | Annotate-to-validate | |
|---|---|---|
| How you check the plan | Build the real thing, look, correct | Agent sketches it, you correct the marks |
| Full code generations | ~4 | ~1 |
| Agent turns (context re-sent each) | ~7 | ~3 |
| Input tokens (context, re-billed per turn) | ~140k | ~60k |
| Output tokens | ~6k | ~2.3k |
| Total (illustrative) | ~146k | ~62k |
That is roughly 2.3x fewer tokens — and roughly half the turns, so it is faster too.
Why the gap is real
The savings are not a trick of the numbers. In generate-to-validate, the only way to see the plan is to build it, so you pay to regenerate a full artifact every round. In annotate-to-validate, you separate the cheap question (is the plan right?) from the expensive action (build it), and you only pay for the expensive part once.
And it compounds with size. Model a single section and the artifact is ~1,500 tokens. Model a whole page or a component tree and each regeneration is 5,000-10,000 output tokens — so generate-to-validate's repeated builds blow up while the plan sketch stays tiny. The bigger the thing you're iterating on, the more lopsided the comparison gets.
An honest note
This is a model, not a benchmark. Real context sizes, artifact sizes, and iteration counts vary widely, and a disciplined prompt can cut generate-to-validate's rounds. The point isn't the exact 2.3x — it's the direction: validating a lightweight plan before generating a heavy artifact removes your most expensive round-trips, and the advantage grows with artifact size and iteration count.
How to actually do it
You need a way for the agent to show its plan and for you to correct it visually. That is the bidirectional visual feedback loop Screentack is built for: over MCP, the agent draws its plan on your screen, you annotate feedback, and it reads your corrections before it writes code. The agent generates the real artifact once — the time it's actually right.
Stop paying to rebuild the wrong layout. Download Screentack — a free 7-day trial, then $29 once.