Watershed
AI / ML EngineerComplexAug 6, 2026

Constrain climate narratives to source-grounded statements

A fluent disclosure narrative can be harder to trust than to produce.

Teams often balance useful coverage against the cost of verifying every consequential statement.

A polished paragraph isn’t helpful if I have to reopen every source to trust it.

Ehsan Saad · Director of Sustainability Reporting

Leads climate disclosure preparation for a public company facing legal, finance, and assurance review.

What pulls against what

  • drafting speed vs. disclosure defensibility
  • coverage vs. abstention
  • fluent language vs. source entailment
  • product launch commitment vs. legal risk
  • automation assistance vs. human accountability

What is at stake

The release can save substantial drafting time, but unsupported statements may create disclosure risk. The model must be useful only where its evidence can be verified

Why Watershed

For Watershed, disclosure workflows often require speed and traceability to coexist under close scrutiny.

Written for

responsible AI engineerLLM evaluation specialisthigh-stakes ML systems builder

This is the setup. The work is inside.

Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.