It's 4pm. You've got 12 patient messages waiting and a full schedule.
You don't want anyone sitting there just to hear back.
@tabflows reads the thread, pulls the patient's context, and drafts the reply. You review and send. Inbox cleared before you leave, because you care.
We just released Draft Assist in Tabflows.
One click and the assist read's the patient's conversation and medical history, and practice internal information to draft an accurate reply ready for review, tweak and send.
@0xsachi Give the same task to both models. Compare the output. Repeat depending on the complexity of the task. Personally, I am using @conductor_build. You can know even let the models evaluate their output.
Introducing 30 days of AI.
For the next 30 weekdays, I’m going to share one observation per day from the frontlines of AI.
I have the privilege of co-running an enterprise AI transformation firm, where I experience the edges of this technology, see the biggest challenges the biggest companies are facing, and have deep relationships with companies on the frontier (Anthropic, OpenAI, Lovable, Cursor, Perplexity, Vercel).
I get to live in the future for free, and I want to bring that future to those trying to disrupt themselves before they get disrupted.
There’s just two rules:
1) Each observation is actionable & understandable to the non-technical leader.
2) I can’t miss a day.
Post 1 coming soon.
Your patient's full story shouldn't be scattered across five different systems ‼️
Here is a quick look at the Patient view we built at Tabflows. The place that pulls together everything that matters about a patient, no matter which system it lives in.
Have a good weekend ☀️
My advice to founders in 2026: spend tokens, not headcount.
Record everything. Make your company queryable. Build self-improving loops.
Before long, AI won’t just help you operate your company. It will make it self improving.
Don't think AI adoption, think AI transformation.
This is the biggest shift in how startups get built since cloud computing.