Show HN: Bind.ly – Persistent memory for AI across tools
by seongjaeryu | 2026-01-07 16:49:37+00:00
Hi HN,

I’m a product designer by background, not a traditional software engineer.

Over the last year, tools like Claude and ChatGPT completely changed how I work.
I started with small internal tools, and now I’m “vibe coding” multiple highly personalized apps.

As I iterated between Claude Code (implementation) and ChatGPT (ideation / thinking),
I kept running into the same problem.

To think clearly, I had to repeatedly re-explain:
- what the code currently does,
- what changed recently,
- and why certain decisions were made.

That re-summarization step became a real bottleneck.

So I built Bindly (bind.ly).

Bindly is a persistent knowledge layer that sits outside any single AI tool.
The key idea is simple:

AI doesn’t remember — it re-reads shared context from the same place every time.

The concrete workflow I use today

This is the workflow Bindly is built around:

1) Claude Code → Bindly
After coding or refactoring, I ask Claude Code to summarize what changed and why,
and store that context in Bindly.

2) ChatGPT → Ideation using Bindly
I then switch to ChatGPT and ideate based on that stored context —
architecture, tradeoffs, next steps.
Those ideation results are saved back into Bindly.

3) Claude Code → Reuse the ideation
Finally, I bring those ideation results back into Claude Code
to continue implementation.

Bindly becomes the shared memory that closes this loop,
without constantly restating everything.

To reduce both cognitive load and token usage,
Bindly applies lightweight diffs (inspired by Git) and progressive search,
so AIs only re-read what actually changed
or what’s relevant right now.

In short:

- Bindly doesn’t try to replace AI thinking.
- It stores what exists, what was decided, and why —
so any AI can continue from the same point.

Personally, this workflow already saves me a lot of cognitive overhead.
But I’m unsure whether this is just a personal productivity hack
or something others would actually pay for.

I’m curious whether others who bounce between multiple AI tools
run into the same problem.

Infrastructure uncertainty (and why I moved to Cloudflare)

I initially built the MVP on Fly.io.
It worked, and I don’t think Fly.io is a bad platform.
But as Bindly grew, I became uncomfortable with how opaque things felt —
volumes, persistence, failure modes.

Bindly is meant to be a knowledge layer.
If data is lost or hard to reason about,
that completely breaks the trust model.

For a tool whose purpose is “don’t lose context,”
that risk felt existential.

I realized I was spending more time worrying about infrastructure
than thinking about the product itself.

So I recently consolidated everything onto Cloudflare
(Pages, Workers, R2, Vectorize),
aiming to reduce operational uncertainty
and keep the system as boring and predictable as possible.

So far, it feels simpler and more transparent.
But as a non-engineer, I’m unsure
if this is a smart long-term decision or a local optimum.

What I’d really appreciate feedback on:

1) Does a shared “knowledge / memory layer” like this
feel useful beyond one person?

2) As a non-engineer, is consolidating on Cloudflare
a reasonable long-term choice?

Some extra context (optional):

I joined HN back in 2018 to apply to YC
and interviewed in Nov 2018 — didn’t make it in the final round.
This is my first time posting here in years.

Current ways I use Bindly:
- via Claude (web)
- via the ChatGPT app
- via MCP (so AIs can re-query stored knowledge)

If you have time to share thoughts —
even critical ones —
I’d be very grateful.

Happy New Year, and thanks for reading!