2022
Flo Crivello says Lindy was started in 2022, which he now considers too early because agent tooling did not yet exist.
“We started this this company in 2022. And so it was it was in hindsight way too early.”
Topic
Lindy
21 facts from 2 episodes, in date order. These are what speakers said on the shows, each linked to the moment it was said. They aren't independently verified.
2025
Evan Ratliff built his AI agents on an AI assistant platform that the transcript renders as 'Lindi'.
“And so I used a platform, which is basically an AI assistant. It at the time it was more of an AI assistant platform, although you can do a ton of things with it, called Lindi.”
2026
Lindy launched Lindy Teammate, an AI employee that works inside a company's Slack and accumulates the team's shared context.
“I think, like, what we are releasing today is called Lindy teammate. It is an AI employee that lives in your slack, connects to all of your tools, accumulates your entire team's context.”
2026
Lindy's memory agent runs roughly every fifteen minutes in the background to update shared and personal memory, rather than once a day.
“it runs every something like fifteen minutes, like why why would you need to sleep every twenty four hours?”
2026
Flo Crivello says Lindy's initial hydration of a twenty-person team's tools and Slack history consumes about three to five million tokens.
“For a team of twenty, that's gonna tend to consume 5 million tokens at most, you know, three to 5 million tokens”
2026
Flo Crivello says the main bottleneck when Lindy crawls a company's Slack history is the Slack API rather than the language models.
“And actually, here, surprisingly, the bottleneck is not even the LLMs, it's the Slack API.”
2026
Flo Crivello says Lindy's current prompt cache rate is 85%, which he considers lower than it should be.
“Our current cache rate is at 85%, which is is lower than it should be, frankly.”
2026
Flo Crivello says a drop in Lindy's cache rate from 85% to 65% roughly doubles its token costs.
“now your cache rate dips from 85% to 65%. And the gap between both, it sounds small, but actually it's a lot of two times the price”
2026
Flo Crivello says Lindy Teammate has put Lindy back into negative gross margin because users give it more complex tasks than the earlier assistant.
“With Lindy teammate, we're back at it and back into, frankly, negative gross margin territory.”
2026
Flo Crivello says Lindy's error rate fell eightfold within the first week of its self-improvement loop going live.
“it went down by eight times the error rate.”
2026
Lindy organizes nested context buckets in a tree where each node holds a hundred children, instead of the two used in a standard red-black tree.
“We went for a it's called a century tree. It's literally just each node's got a hundred nodes.”
2026
Lindy backs its agent file system with Git to handle conflicts when multiple memory sub-agents edit files, and to keep a history of changes.
“The answer to that is Git, which by the way, also gives you history for free, which is which is awesome.”
2026
Flo Crivello says Lindy works with Mesa, a vendor selling an agent-native file system backed by Git.
“We've been working with a Mesa, M E S A, they sell like uh an agent native file system that that's backed by Git”
2026
Flo Crivello says Lindy uses E2B for its agent sandboxes.
“So we've we've gotten with the E two B for that.”
2026
Flo Crivello says Lindy's internal pull requests per week, and lines per pull request, each tripled over three months.
“Our number of P Rs internally has, like P Rs per week has tripled over the last three months”
2026
Flo Crivello says Lindy's headcount has been flat while he estimates its productivity has tripled over a couple of months.
“The team is actually, I think headcount has been flat now for a while, and we've again, like I said, we've actually tripled our productivity over a couple of months.”
2026
Flo Crivello says Lindy's payroll still exceeds its internal AI inference spend, but he expects the two to cross within three to six months.
“So payroll is still greater, but the the lines are gonna cross three to six months from now.”
2026
Lindy has its agents include the weekday with dates and uses a simple regular-expression validator to catch the one-day date errors Flo says Claude models made.
“Okay, if you do that, then you can have a deterministic validator that checks whether the date of the week matches the the day, the data was submitted. And that's just a regular expression.”
2026
Flo Crivello says Lindy's default model is currently DeepSeek for everything, though the company is reconsidering because Teammate needs more compute.
“Everything is DeepSeek right now. We are in the middle of reconsidering it”
2026
Flo Crivello says re-optimizing Lindy's prompts with its GEPA-based loop costs about $10,000 each time a major new model is released.
“So it's like about like $10,000 every time like a new major model comes out.”
2026
Flo Crivello says that with unlimited resources he would train a LoRA, a small fine-tuned adapter, for each user as a way of storing memory in model weights.
“I think eventually, with infinite resources, what I would like to do is I would like to do a LoRA per user, because LoRAs are actually pretty cheap to train.”
Episodes