Built an AI cofounder that remembers my startup's context between sessions

The pushback angle raises a useful distinction: an idea I'm exploring isn't a decision I've made. If I say 'maybe we should target agencies,' I'd want Pythe to keep that as a hypothesis, not silently update my ICP. Does it ask for confirmation before a conversation changes the roadmap's underlying assumptions?

The re-explaining-your-own-company problem is real. I keep a pinned doc I paste into new sessions just to avoid repeating ICP and positioning every time. One thing I'd want to know before trusting a memory layer: when positioning shifts (and it does every few weeks early on), does Pythe version the old context or just overwrite it? Stale memory feels worse than none.

The re-explaining problem resonates, but stale context worries me too. With DictaFlow, I've found that people need to see and edit useful context easily. If they can't, they stop trusting it and find ways around it. Version history and a clear "what this remembers" view would make the promise much easier to trust.

The "30% off for life" offer is the part I would kill before launch. You are permanently repricing your most engaged early cohort at a number you set before you knew what the product was worth, and those are exactly the accounts you will want to raise prices on later. Give the first 50 a few free months or a founding-member badge instead, both cost you less and neither one puts a permanent ceiling on the account.

Most "AI memory" demos are a bigger context window with better marketing.

What actually sticks is a tiny pipeline, not a model feature: decide what's worth keeping, park it somewhere, retrieve it later, and have a rule for when to stop keeping it. Skip that last part and you just accumulate sludge until the agent gets worse.

I tore the word "memory" into the five mechanisms people mash together, then wrote a ~90-line version that does the job:

https://medium.com/data-science-collective/i-built-the-thing-that-lets-ai-remember-you-it-took-90-lines-c301a96cdfac?sk=f87978834c801da16d80c4799b467edc

Curious how you're handling the forget side. That's the bit most demos skip.

Nice post!

The “push back like a cofounder” part is what caught my attention. Remembering context is useful, but having the AI actually tell you when an idea probably isn’t worth building seems much more valuable. Have you found that founders prefer the pushback, or do they mostly use it for brainstorming?

This sounds like a general-purpose memory layer. I'm wondering how it differs from other memory layer applications out there.

I've actually been following a lot of memory layer apps, but I haven't really found any practical use cases yet because I can just have AI read my website directly. Plus, tools like Codex or Claude already have built-in memory that remembers these things.

The only real difference would be whether there is a way to flexibly switch between different software. For example, once I've built up enough memory in one tool, can I just switch directly to another?

This hits home — I got tired of re-explaining my own company to every AI tool too. Respect for shipping Pythe and taking the feedback loop on the chin; the "push back like a cofounder" angle is genuinely the strongest part, and context is what makes that pushback relevant. Curious what context you persist — positioning doc, ICP notes, competitor matrix? I solve the same problem from the other direction: plain-text CLAUDE and SKILL instruction files that travel with the repo, so any agent reads the same context every session. Packaged 76+ of those workflows into $7 packs.

The 'remembers between sessions' pitch is the right one to lead with, that reset-to-zero problem with every AI tool is real and something I've felt myself. One thing I'd push on: 'ships via MCP/REST so it sits inside Claude, ChatGPT, Cursor or Lovable' is a strong technical differentiator, but it's buried after the roadmap pitch, that integration point is probably the actual reason someone switches from just re-explaining context every time, I'd lead with that rather than the staged roadmap feature.

The persistent context and staged roadmap approach sounds genuinely useful, especially for founders who are tired of repeating the same company details every session. MCP/REST support is also a nice touch. I’d be interested to see how well the context retention works as a startup evolves.

The memory solves a real annoyance, but I’m curious whether founders actually make different decisions because Pythe remembers the context, or whether it mainly saves them from re-explaining the same things each session.

Addendum since a few people asked what actually makes this different: the memory part is just plumbing. The main thing Pythe does is generate the staged roadmap and push back like a cofounder would ("this isn't worth building yet, do X first") - the fact that it retains context between sessions is what lets it do that well, not the feature itself. Should have led with that.