Teable 3.0

The mix of structured data and app generation is what caught me. Being able to turn something like receipts or customer feedback into a working workflow without moving it into another tool feels genuinely useful.

the multi-agent collaboration angle is the part that jumps out at me over the single-agent rollback question everyone else is asking. once you have two agents with overlapping permission scopes both acting on the same linked record at roughly the same time, is there any locking or conflict detection, or does it become a last-write-wins situation where the second agent's transaction just silently overwrites the first without either agent knowing a conflict happened?

Congratulation on the launch Teable 3.0 team! Really amazing stuff 🎉Most AI-native database tools are moving toward autonomous agents. How do you see Teable balancing user control and transparency with AI-driven actions, especially when agents are modifying business-critical data at scale?

The thing that always sold me on Teable over the Airtable-style tools is that it's real Postgres underneath — your data stays actual SQL you can own and query, not locked in a proprietary spreadsheet blob. Curious how 3.0 handles the AI-workflow side: when an agent builds an app or automation off the data, do you get a deterministic, inspectable step you can audit, or is it prompt-driven each run? That's usually the trust gap for "AI + my business data." Congrats on the launch.

What am I missing? If I have data in a spreadsheet, using the spreadsheet as a db, why would I move the data into Teable? Maybe I am too tired but I don't understand the value prop and the problem this solves. Maybe someone can explain? Thank you!

"AI workflows" built on top of spreadsheet data is the pitch but the interesting question is what the AI layer is actually doing, like is it generating formulas, automating data entry, running analysis on the data, or orchestrating multi-step workflows that call external APIs? Those are pretty different products and the listing doesn't distinguish between them, curious which one is actually the core use case Teable users are building toward.

Congrats on 3.0! The Postgres foundation is what sold me. Most “AI acts on your data” tools break the second an agent touches linked records. You built on real relational structure instead. Smart bet.One question: how do you see Teable fitting next to tools people already use? I’ve got data in Notion, Drive, and Jira. Would Teable be the source of truth those sync into, or are you asking teams to move in fully?Either way, I want to try it on a real workflow.

building software through natural language could change how teams operate. how does Teable ensure generated applications remain easy to maintain over time? can users modify everything after AI creates it?

Congratulations on the launch!natural language application building has huge potential. can multiple team members collaborate with the same AI agent simultaneously? how does collaboration work in shared workspaces?

Congrats on the launch @guangyu_li A quick question, how does Teable compare to just using Airtable + a couple of AI plugins at this point?

hey congrats on the launch! quick question: how do you handle permissions and history logs since many people can just edit and change data that can tangle the rest of the workflow?

One of the most interesting launches today! The Postgres-as-substrate choice is what makes the agent story believable to me. And probably most 'AI acts on your data' pitches fall apart the second an agent writes something wrong across linked records. Wondering...when an agent runs a multi-step action and step 3 fails, does the whole thing roll back as one transaction?

the migrate-anything plus self-host combo is the real hook here, owning your own data is the thing airtable structurally can't offer. congrats on 3.0

Hey, the spreadsheet-that-is-really-a-database space is crowded, so curious where you land. In my experience the moment a team spreadsheet gets important it breaks, because five people edit it and nobody trusts the numbers. Does Teable handle permissions and audit trails well enough to be the real source of truth, or is it best as a fast front end?

The migration claim is the part I would stress test hardest, specifically the linked records piece. Airtable and similar tools let people build pretty tangled relationship structures over years, lookups referencing lookups, rollups built on linked fields that are themselves filtered views. Moving the raw data over is the easy part. Moving the actual behavior of those relationships so formulas and automations still resolve the same way on the other side is where most migration tools quietly lose fidelity. Curious how much of that structural logic survives a real migration versus just the tables and values themselves.

Also on the super automation side, once you're running things like contract expiration reminders and weekly sales reports automatically, what happens when the underlying data changes shape, say someone renames a field or restructures a table the automation depends on. Does it fail loud and notify someone, or does it quietly keep running against stale assumptions.