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Field agent enhancements: Triggers + config redesign

  • March 28, 2026
  • 4 replies
  • 127 views
chelseytanaka
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Available in AI Labs by April 3, 2026

 

Hey Builders! 

We’re launching two updates to AI Labs that give you more control over how and when your field agents run, and that make them easier to configure.

 

Field agent generation triggers

Until now, field agents could only run in two ways: automatically whenever referenced fields changed, or manually when you clicked to generate. Now you have the option to run field agents automatically on a schedule or when a condition is met.

Trigger types

  • [new] On a schedule: Runs at a particular time
    • Scheduled triggers can also have conditions applied to the schedule, to only run a subset of records on the schedule
  • [new] When a condition is met: Runs when a record meets the specified condition(s)
  • [existing] Run automatically: Runs when the field agent’s referenced fields change

 

 

Example use cases

  • Competitive price monitoring: Run every morning to pull updated competitor news via internet search.
  • Contract renewal warnings: Fire when days-until-expiry crosses 60, generating a renewal strategy from contract terms and customer history.
  • Conference attendee enrichment: Run when an individual is marked as “Attending”, pulling info about their bio automatically.
  • Weekly PM digest: Every Monday morning, pull comments from GDrive PRDs and surface a summary of open issues.

A few things to know

  • Triggers are a part of field agents — they do not show up in Automations and do not count against your automations budget.
  • Scheduled and conditional triggers can be paused and resumed. When you resume, your previous settings will be pre-populated.

 


Redesigned field agent config

Alongside triggers, we've shipped an updated config experience for all field agents.

What's new:

  • More space for your prompt — We've expanded the prompt writing surface based on your feedback. The prompt area can now be expanded to give you more space for drafting.
  • @ symbol for field references — In addition to the existing { shortcut, you can now use @ to reference fields in your prompt.
  • Clearer settings organization — Field agent configuration is grouped into 3 sections: 
    • Inputs: Field agent name, type, tools, and model are grouped at the top of the config
    • Prompt and preview: You can view the prompt and preview in the config, or expand to see the larger prompt/ preview surface
    • Outputs and triggers: The bottom section contains output-related settings - select options, formatting options, etc. It also contains the triggers listed above.

 


We're excited to see how you put triggers to work. Have a use case you're building toward? Drop it in the comments below 👇

 

4 replies

jiasso
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  • New Participant
  • March 30, 2026

HUGE news on the UI overhaul for field agents. Cant wait to use both of these!


Mike_AutomaticN
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This really really good (specially the “when conditions are met”). Previous workaround involved referencing an checkbox on the AI field, and having it checked via automation (which consumed automation runs and limits as well)!! Thanks for shring ​@chelseytanaka!

 Mike, Consultant @ Automatic Nation 
YouTube Channel 


v.moreno
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  • New Participant
  • March 30, 2026

Great update! Agents were generating images and consuming credits every time I updated some fields in my tables. Now will have more control, nice!


Maxim_KM
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  • Participating Frequently
  • April 2, 2026

Hey ​@chelseytanaka ,

 

Immediately started to battle-test this on a dataset with 10k records, that is adding ~1k daily(heavy AI flows) Love the direction. This is getting close. But a few things are still slowing real workflows down.

What’s working

Reorg is cleaner. Feels lighter. Being able to hide Preview is actually a big deal, avoids unnecessary runs and noise.

Where it breaks

  1. Prompt editor is still not production-ready

    Pasting prompts from CLIPBOARD that contain {} or @ still doesn’t work for field recognition.

    That’s a blocker.

Real flow:

  • generate prompt externally (AI / architecture system)

  • paste into Airtable

  • expect fields to just map

Right now it breaks that loop.

Also, would be huge:

  • support {Field Name|optional}

    → auto-detect + mark as optional token

This alone would speed up prompt building a lot.

 

  1. Model selection = friction + hidden cost

    Switching models is part of the workflow, not a one-time setup.

Right now:

  • hard to iterate quickly across models

  • no clarity on which model is “cheap but good enough” for simple tasks

Example:

Extracting UK postcodes from addresses

→ should be a near-zero-cost operation

→ but I don’t know which model to pick confidently

Also:

  • showing “0 credits” is misleading

  • it’s just rounding down

Better:

  • show fractional credits (½, ¼, etc.)

    → makes cost tradeoffs visible instantly

 

  1. No way to preview final compiled prompt

    I need to see:

    → what the prompt actually looks like after substitution

Right now I’m flying blind.

This is critical for:

  • debugging

  • optimization

 

  1. Triggers are powerful… but risky

Triggers are 🔥

But missing one key safety layer: “Run automatically once (If Empty)”

Suggested:

Automatic generation:

  • Off

  • On

  • If Empty

Why it matters:

  • prevents accidental overwrites

  • protects against schema changes nuking good data

Especially important with:

  • conditional triggers

  • formula-based conditions (which can flicker true/false)

  • avoids massive credit drain during iteration


Thank you for your attention,
​​​​​​​Maks