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The future of survey programming
is already shipping.

Insights runs on surveys. Surveys run on code — until now, hand-authored by specialists, measured in days. Fieldbase SP writes that code the engine was built to run, inside the editor the team already uses, with every change in a thread the operation can audit. A 60-question tracker, drafted in minutes.

Fieldbase SP · project-aware · per-project thread
① Spec upload

Drop the brief.
Get the survey.

A client doc arrives in the morning. By lunch, a working draft is on a reviewer's screen — not next week.

  • Word, PDF, or transcript — in. Fieldbase SP parses the structure, keeps the sections, keeps the ordering.
  • Full survey — out. Screeners, routing, quota wiring, options, scripts. All linted before you see it.
  • Level 3 complexity · 60 q · ~6 min. A survey a specialist would quote for 24 hours, drafted while you refill a coffee.
W
brand-tracker-Q3.docx
Client brief · 42 pages · 1.2 MB
Programming complexity
Level 3 of 4 · routing + loops
By hand ~24 hours
240× faster
✦ Fieldbase SP
✦
survey.yaml
Fieldbase SP draft · 944 lines · pid-00067
60 questions
  • 8 screeners
  • 42 main · 10 demo
  • 1 lookup
  • routing + loops
With AI ~6 min · 0 lint errors
FIELDBASE · in-editor
DE "Screen out under-18s at S2."
✦ S2 · Age screen-out 1 line · lint 0 errors
− if S2.value >= 65:
+ if S2.value < 18 or S2.value >= 65:
the usual way: open ChatGPT → paste survey → ask → paste back → hope
② Change-request with review

Describe the change.
The AI writes it.
You accept, refine, or skip.

Every other AI you've used lives in another tab. You copy, paste, hope. Fieldbase SP edits the project in place — and nothing lands without a human click.

  • Ask inside the editor. Scope with @, qid, or a line number. No copy-paste tab-dance.
  • Review the diff. Lint-checked before you see it. Accept, Refine, or Reject with one click.
  • Lands in place. No stitching, no "did it get the quota cell too?" — the editor is where change happens.
③ Project thread

Every change,
in one audit thread.

The team sees everything. Scoped to one project. Scroll back weeks. Ask the AI itself what changed last Thursday — it answers from the log.

  • Persistent, per-project. Not a personal chat window. Each project has its own thread, bound to its own file.
  • Shared with the whole team. Every ask, every proposal, every Accept, Refine, Reject, revert — logged where everyone can see it.
  • Ask the thread itself. "Summary of changes this week?" The AI answers from its own log — the audit trail nobody has to maintain.
✦
AI · project thread
pid-00052 · Brand Tracker Q3 2026
JO
PR
SA
DE
— TUE 16 SEP —
PR
Priya10:40
Add a gender question after S1.
✦
AI10:40
Added S1b · Gender.
S1b · Gender Applied by Priya
SA
Sarah14:22
Add a MaxDiff on the 8 brand attributes.
✦
AI14:22
Proposed QMaxDiff.
QMaxDiff · Trade-off Reverted by Sarah
— THU 18 SEP —
DE
Dev09:12
Rename S1 to COUNTRY.
✦
AI09:12
Renamed S1 → COUNTRY. Updated 13 refs across pipes, scripts, quotas.
S1 → COUNTRY · cascade Applied by Dev
JO
Jojust now
Summary of what changed this week?
✦
AIjust now
3 asks across 2 days:
  • ✓ S1b Gender added (Priya, Tue)
  • ✗ QMaxDiff proposed, reverted (Sarah, Tue)
  • ✓ S1 → COUNTRY renamed, 13 refs updated (Dev, Thu)
Net: +11 lines, 0 new lint errors.

Still a human decision

The AI never writes directly to the survey. Every proposal is a reviewable diff with Accept, Refine, or Reject. Metering is opt-in; a team can leave AI assist switched off and nothing else in the editor changes. What ships is the research team's call — the AI just takes the slow part out of the middle.