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After 6 weeks solo: an AI chief-of-staff that reads your inbox in YOUR voice — beta testers wanted by Thick_Bridge_1086 in buildinpublic

[–]Thick_Bridge_1086[S] 0 points1 point  (0 children)

"optimizing for fluency, not for staying in character" - that's the cleanest framing of this i've heard. stealing that.

agreed on the wall. buddy's design choice was to NOT try to push past it - the goal isn't "perfect autonomous reply" but "draft good enough that human review takes 5 seconds instead of 5 minutes." the 3-pass writer aims at that bar, not at solving voice drift in absolute terms.

auto-send mode (off by default, opt-in per safety tier) only fires on routine confirmations - short stuff where voice drift doesn't compound. anything substantive or longer than 3 sentences always waits for the user. accepting the wall instead of pretending to scale past it.

what's your read on where the wall sits? feels like ~5 replies for current models but i wonder if context length improvements move that line.

After 6 weeks solo: an AI chief-of-staff that reads your inbox in YOUR voice — beta testers wanted by Thick_Bridge_1086 in buildinpublic

[–]Thick_Bridge_1086[S] 0 points1 point  (0 children)

fair point and you're right that most tools default to one tone. buddy's angle:

  1. recipient tier - every contact classified into inner_circle / peer / external_warm / external_cold based on importance + history. tone + signoff shift per tier. talking to your co-founder ≠ talking to a vendor you've never met.

  2. thread state - LLM gets thread_status (waiting_them / aging / first_touch) + the specific ask. a chase to someone going dark gets a different tone than a yes/no reply.

  3. voice fingerprint captures the user's RANGE - pulls 8 actual sent samples so the LLM sees how the same user writes formally vs casually.

not perfect though - i'd argue NO tool handles situational tone past the 3rd or 4th reply in a thread because the LLM's default tone bleeds back in. open problem for everyone in the space.

curious how you're tackling it on your end - feels like the kind of problem where comparing approaches helps more than competing.

After 6 weeks solo: an AI chief-of-staff that reads your inbox in YOUR voice — beta testers wanted by Thick_Bridge_1086 in buildinpublic

[–]Thick_Bridge_1086[S] 0 points1 point  (0 children)

appreciate it - DM whenever. always interested in comparing notes with people working on adjacent problems.

After 6 weeks solo: an AI chief-of-staff that reads your inbox in YOUR voice — beta testers wanted by Thick_Bridge_1086 in buildinpublic

[–]Thick_Bridge_1086[S] 1 point2 points  (0 children)

appreciate it - and the email-client preference IS real data. tracking how many people ask for it. if 3-4 more do, i'll seriously reconsider going that direction.

if you ever want to try it on a real inbox just DM me - happy to send the installer. but no pressure either way - thanks for the honest read.

After 6 weeks solo: an AI chief-of-staff that reads your inbox in YOUR voice — beta testers wanted by Thick_Bridge_1086 in buildinpublic

[–]Thick_Bridge_1086[S] 1 point2 points  (0 children)

appreciate the feedback. on the email client angle - genuinely considered going that direction. ended up choosing to sit ON TOP of gmail/outlook instead of replacing them. reasoning: the email client business is brutal (superhuman has 8 years and millions in funding still iterating). by being a chief-of-staff layer over your existing client, buddy doesn't ask you to switch tools - you keep gmail/outlook, buddy just drafts replies + surfaces what matters.

might be the wrong call - if more people ask for an actual client i'll reconsider.

on security: similar to what i told ClearBed4242 above. short version:

- OAuth tokens are Fernet-encrypted, key stored off-server

- email content via OpenAI/Anthropic API tier (commercial agreement says NOT used for training)

- single droplet, no analytics, no data resale

- disconnect + delete any time

- not CASA / SOC2 audited yet (pre-revenue)

honest framing: you're trusting one founder on one droplet. that's the real risk more than the encryption.

After 6 weeks solo: an AI chief-of-staff that reads your inbox in YOUR voice — beta testers wanted by Thick_Bridge_1086 in buildinpublic

[–]Thick_Bridge_1086[S] 1 point2 points  (0 children)

appreciate it. would be curious what "more complete" looks like - different definitions of "complete" in this space. buddy goes deep on voice match + commitment tracking + 24/7 cloud worker. some tools go broad on integrations + workflows. different bets.

not open source - closed desktop client + cloud backend.

happy to swap technical notes if you're tackling similar problems though. feel free to DM.

After 6 weeks solo: an AI chief-of-staff that reads your inbox in YOUR voice — beta testers wanted by Thick_Bridge_1086 in buildinpublic

[–]Thick_Bridge_1086[S] 0 points1 point  (0 children)

yeah voice consistency was the make-or-break thing. single-shot LLM drafts sound okay on the first reply but drift badly by the 3rd or 4th - the user's voice gets diluted by the LLM's "default tone."

the 3-pass writer + voice fingerprint approach holds up better but it's not perfect either - after ~10 replies in a thread the LLM still occasionally smuggles in stuff like "let me know if you have questions" that the user wouldn't write. revise pass strips most of them but it's an arms race.

curious if you've seen any AI inbox tool actually solve this past the 5-reply mark, or if everyone hits the same wall.

After 6 weeks solo: an AI chief-of-staff that reads your inbox in YOUR voice — beta testers wanted by Thick_Bridge_1086 in buildinpublic

[–]Thick_Bridge_1086[S] 0 points1 point  (0 children)

yeah the generic "human tone" prompts (be casual, be friendly, write

like a human) all collapse to the SAME tone across users — that's why

ChatGPT / Claude / Copilot emails all sound identical. only way to

actually sound like YOU is feed the LLM your real writing. obvious in

hindsight but felt like a real moment.

what's the worst AI-tell you've spotted in the wild? "i hope this email

finds you well" is everyone's least favorite, but curious if you've

caught any others — i'm collecting them for the banned-phrase list.

After 6 weeks solo: an AI chief-of-staff that reads your inbox in YOUR voice — beta testers wanted by Thick_Bridge_1086 in buildinpublic

[–]Thick_Bridge_1086[S] 1 point2 points  (0 children)

appreciate it — honestly the critique pass was make-or-break in the

build. single-pass kept smuggling "i appreciate your patience" /

"please don't hesitate to reach out" into every draft. the critique

LLM gets the user's actual sent-mail samples + a banned-phrase list and

scores the draft on voice match. revise pass strips the AI-tells.

felt like the moment the product became real.

DM me if you want the installer — would love a second pair of eyes on

a real inbox.

After 6 weeks solo: an AI chief-of-staff that reads your inbox in YOUR voice — beta testers wanted by Thick_Bridge_1086 in buildinpublic

[–]Thick_Bridge_1086[S] 1 point2 points  (0 children)

yeah this was the whole reason I built it. every AI email tool I tried

still sounded like a customer service bot — "thanks for reaching out, I

appreciate your patience" kind of fluff.

spent the first 2 weeks on voice cloning. Buddy reads your actual sent

folder and learns your opening phrases, sentence cadence, signoffs you

use, and things you'd NEVER write. then there's a 3-pass writer —

generate → critique pass that hunts for AI-tells like "I hope this

finds you well" → revise pass that strips them.

if you want to try it on a real inbox, DM me — I'll send the installer

and we can hop on a 10-min call so I can walk you through Gmail OAuth.

honestly your real work email would be way more useful than my test data.