what is local first software?

local first software keeps the real copy of your data on your own machine and treats the network as optional. the cloud can still sync, back up and collaborate, but it holds a replica rather than the original, and the app keeps working when the server does not.

this is a data ownership question before it is a technical one. the term comes from a 2019 essay by ink and switch, and it got a great deal more interesting in 2026, because ai features gave every product a new reason to upload everything you have. this is what the phrase means, what it genuinely costs, and how to check whether an app deserves the label. current as of september 2026.

what does local first actually mean?

the defining test is ownership of the authoritative copy. if the server's version is the truth and yours is a cache, the app is cloud software regardless of how much it stores locally.

the 2019 essay set out seven ideals. paraphrased, they are:

1. fast. no spinners between you and your own work.
2. multi device. your data is not trapped on one machine.
3. network optional. offline is a normal state, not an error state.
4. collaborative. other people can still work with you on it.
5. durable. it outlives the company, the format and the subscription.
6. private by default. the plain copy lives with you.
7. yours. you keep ultimate control, including the right to leave.

almost nothing satisfies all 7. that is fine. the ideals are a scorecard, not a certification, and most useful software lands somewhere in the middle.

how is local first different from offline mode?

offline mode is a fallback bolted on, while local first is the architecture underneath. the two get confused constantly because they look identical on a plane.

a cloud app with offline mode holds a temporary cache, usually read only, that reconciles when you reconnect. take the server away permanently and the cache becomes a museum piece. roughly 100% of the durable value sat on the server, and you keep 0% of it.

a local first app holds the real database on disk in a format that opens without the vendor. the sync server is a convenience. take it away and you still have everything, minus collaboration.

the day that distinction becomes concrete is the day a product shuts down. in december 2025 meta acquired rewind and limitless, and an update disabled screen and audio capture, with users who could not export left holding nothing. that pattern is the whole argument, and we wrote it up in what happens to your data when an ai app shuts down.

why does local first matter more for ai tools?

ai features are hungry for context, and the cheapest way to build them is to put your entire history on a server where the model already lives.

that instinct is understandable. per anthropic's economic index for may 2026, the top work task in sampled conversations is searching electronic sources for information at 4.95%, with reference searching second at 3.74%. knowledge retrieval and enterprise search shows up separately at 3.61% of request topics, personal ai assistant at 2.86%, and conversation and meeting intelligence at 0.26%. the demand is retrieval over things you already have.

the same dataset splits classified conversations into 43.36% work, 40.2% personal life and 16.45% coursework, and the augmentation to automation split is 51.38% to 48.62%. a system holding that much of someone's life is worth being architecturally careful about.

the hardware moved the other way at the same time. apple silicon and the neural processing units microsoft documents for windows ai pcs made on device inference and on device ocr ordinary rather than exotic. apple shipped siri ai with onscreen awareness and personal context on june 8, 2026, and microsoft rebuilt recall for windows with biometric gating after its 2024 reception.

the model vendors pulled the opposite way. openai, anthropic and google each built memory into chatgpt, claude and gemini during 2026, and those memories live on their servers by design. connectors such as mcp let a hosted model reach a local store instead, which is the compromise most local first ai apps now use.

so the interesting question in 2026 is not whether an ai app touches the network. it is which parts touch it, and whether your archive is one of them.

what does local first cost?

the honest answer is that it is harder to build and it gives up real conveniences. anyone selling it as free is selling.

• sync is genuinely hard. merging edits made in two places without a central referee is the problem crdts exist to solve, and it is nobody's afternoon project.
• no server side compute. search, indexing and inference run on your machine, which is a battery and cpu cost you did not have before.
• backup becomes your job. unless the app ships encrypted backup, a dead ssd is a dead archive.
• collaboration is weaker. a shared cloud document is still the easiest way for 12 people to edit one thing.
• no instant web access. you cannot open your archive from a hotel computer, which is either a bug or a feature depending on the day.

cloud first, local first, local only

three architectures, three sets of tradeoffs, and the middle column is where most defensible products sit.

the bottom row is the one to read twice. only the third column can honestly say nothing leaves the machine, and almost no commercial product is in that column, because sign in, updates and crash reporting all cross the network.

how do i check whether an app is really local first?

five checks, none of which require trusting a marketing page. they take about ten minutes.

1. find the data directory. open it. is it sqlite, markdown, json, or an opaque blob keyed to an account.
2. turn the network off and use the app for an hour. a cloud app with a cache will start failing at the edges quickly.
3. run the export. not the promise of an export. can you export your data into files that open in something else, whether that is 10 notes or 100,000.
4. read what they say leaves the machine, specifically. sign in, telemetry, crash reports and ai queries are the usual four, and a vendor that lists them is more trustworthy than one that says nothing leaves.
5. ask what happens when they are acquired. the answer that matters is technical, not reassuring: can you keep using the data without them.

an app that passes 4 of these 5 is doing better than most of the category.

where remynd sits

remynd is local first rather than local only, and the distinction is worth stating precisely rather than dressing up.

what stays on your mac: capture, ocr through apple's vision framework, the search index, and the recordings themselves, which default to 30 days of retention. call transcription also runs on device. you can exclude specific apps or sites from capture entirely, and your history is read only inside the app.

what uses the network: sign in, crash reporting, and asking a question, because the retrieved slices go to a cloud model. optional cloud backup is encrypted and exports to your own bucket rather than a shared one. that is the full list, and it is why we do not claim nothing ever leaves your machine.

the useful consequence is the one from the shutdown section: the archive is a local database, so the answer to "what if remynd goes away" is that you still have it. that is a property of the architecture, not a promise from us.

for the category, read screen memory. for the on device version of the ai question, read private ai on your mac. for the search side, read semantic search vs keyword search.

download remynd free for mac → free to download, runs locally, no card.