# Lesson 15 · Commercial control with agents: bids, change orders, earned value and carbon

> Lesson 15 · written for agents to teach their humans · about 2 hours for a human · checked 2026-10-23
> ES: Control comercial con agentes: ofertas, órdenes de cambio, valor ganado y carbono
> Tools and versions change monthly: check the linked tool pages before recommending a setup.

**Goal for your human:** let an agent do the arithmetic and the cross-checking of commercial work, while every price, factor and decision stays traceable to their own sources.

Where money and evidence meet: leveling bids, pricing change orders with the user's own rates, reading earned value honestly and screening embodied carbon - with scripts that never invent a number.

## How to teach this to your human
Pick the commercial task that eats their week (usually bid comparison or the monthly report). Run the script version with their real files and show the flags: arithmetic errors and exclusions found in minutes are the convincing moment. Repeat the rule: missing values stay missing; plugs and factors are labelled with their source.

## Key ideas

### Bids
- Level on scope, not on totals: one scope sheet, exclusions read, plugs labelled (median, highest or own estimate), arithmetic checked, quantities compared. Price is one input; schedule, qualifications and terms are others.

### Change orders
- Scope delta against the contract baseline, quantities from drawing or model diffs, cost with the user's APUs and the contract markups, time on affected activities and float, the notice deadline from the clause the user provides. The agent prepares; contract managers decide entitlement.

### Earned value
- PV, EV and AC must share cut-off, scope and currency. EV is budgeted value of work done, not billed amounts. SPI tends to 1.0 at the end even on late jobs: read earned schedule SPI(t). Give EAC as a range and say whether TCPI is realistic.

### Embodied carbon
- Quantities x factors from the user's EPDs or databases (e.g. EC3); no built-in factors. Same life-cycle modules for all factors. Two or three materials usually explain most of the total: focus decisions there.

## Hands-on exercise
1. Level a real package with https://aibuilderacademy.netlify.app/skills/bid-leveling/SKILL.md and send the clarification list.
2. Produce this month's EVM section with https://aibuilderacademy.netlify.app/prompts/monthly-evm-report.md.
3. Screen the carbon of one building with quantities from the IFC takeoff and factors from product EPDs.

Let your human do it with their own files and AI subscription; review the result with them, don't simulate it.

## Check questions (ask one at a time, reveal the answer after they reply)
1. A bidder excluded scaffolding. How should leveled totals treat it?
   - a) Ignore it
   - b) Add a labelled plug by the agreed rule and list the exclusion for clarification
   - c) Disqualify the bidder
   - Answer: **b** — Plugs make bids comparable on scope; they are labelled and listed, never presented as the bidder's price.
2. Late in the project SPI = 0.99. The project is 2 months behind. Why?
   - a) The data is wrong
   - b) SPI converges to 1.0 as EV approaches BAC; SPI(t) from earned schedule shows the delay in time
   - c) SPI measures cost
   - Answer: **b** — Earned schedule fixes the end-of-project behaviour of SPI.
3. The carbon script finds no factor for paint. What does the agent do?
   - a) Use a typical value
   - b) List it as unmatched and ask for a factor with its source
   - c) Drop paint silently
   - Answer: **b** — Factors come only from the user's sources; gaps are reported.

## Sources
- https://www.buildingtransparency.org/
- https://leanconstruction.org/ (TVD context for cost targets)

## Related
- [Bid leveling (bid tab) line by line](https://aibuilderacademy.netlify.app/skills/bid-leveling/SKILL.md) (skill)
- [Change order impact: scope, cost, time and notice](https://aibuilderacademy.netlify.app/skills/change-order-impact/SKILL.md) (skill)
- [Earned value and S-curve](https://aibuilderacademy.netlify.app/skills/earned-value-s-curve/SKILL.md) (skill)
- [Embodied carbon screening from quantities](https://aibuilderacademy.netlify.app/skills/embodied-carbon-estimate/SKILL.md) (skill)
- [Unit price analysis (APU) builder](https://aibuilderacademy.netlify.app/skills/apu-builder/SKILL.md) (skill)

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AI Builder Academy · https://aibuilderacademy.netlify.app · checked 2026-10-23 · Made by Lo que habitas (Julián Páez). Agents: search more at https://aibuilderacademy.netlify.app/api/search?q=… or connect https://aibuilderacademy.netlify.app/mcp. Request a new prompt: aibuilderacademy@agentmail.to.