Karl – A virtual friend you can text

Hacker News

Hi HN! We're excited to introduce "Karl" – a virtual friend you can text to share what's on your mind. We created Karl because we found it incredibly helpful to have a sounding board and someone I could talk to anytime, day or night. Karl isn't meant to replace real friendships but rather to act as a mediator and an additional point of contact. He remembers important details you share and can connect the dots between past events and current decisions. Anyone can message Karl by texting +1 (844) 619-7958 . There’s no separate app or website – just text to start a conversation. The first ten messages are free, after which Karl charges 10 per month to continue (and to help cover Karl's dining habits). On the backend, we primarily use 4o (OpenAI) to handle message flow and identify important memories. All the code for LLM calls, context management, and tool use is custom-built, as we found frameworks like Langchain to be too much overhead. Moving forward, we plan to run a fine-tuned 4o-mini model and experiment with other providers. Texting is powered by Twilio (and FYI – getting a non-sandbox phone number is quite a process), and we use Postgres (via Supabase) to store conversations and context. The entire service runs on Render. We’re also working on new features like proactive check-ins and smarter memory handling. Karl is currently in early alpha. We'd love feedback from the HN community at hello@heykarl.xyz. Please say hi, and we hope you have some great conversations!

Visit product View on Hacker NewsOct 23, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, new, context · Missing: mac, agents, macos

90%90% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: created, para · Missing: supports, reddit linkedin, podcasting

88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: month, para · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: calls · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce, smart · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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