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If you are a technical founder, you do not need a non-technical cofounder.

Day 12 of building autolead.trythis.app Today I implemented post fetching using the Snoowrap SDK. For each subreddit, I fetch up to 100 posts from the “new” section, stopping once I hit a post older than what I previously scraped. This runs every 10 minutes. To avoid

Day 13 of building autolead.trythis.app Today I didn't code, but instead, I researched how to match subreddit posts with a user’s website content. The pipeline I’m considering: Use a cheap (or free) vector-based semantic match. Embed both the Reddit post and the website

I wish Prisma Postgres gets support for vector datatype! Otherwise I have to keep using queryRawUnsafe, which I hate doing.

Taking a break from coding now and then is as important as making progress everyday! Your mind needs time to pause, reflect, think, play, and rest.

Day 15 of building autolead.trythis.app Started building the post matching pipeline! Step 1: fetch Reddit posts that match the topics of a user’s website. - Both website + post embeddings are already in Postgres - Run a SELECT query (per subreddit) ordering by cosine

Just tried out Anthropic Claude code today. Using that for making larger changes + cursor for tab completion or small changes is IMO the optimal vibe coding experience.

Cloning llama 3.1, 8B takes forever on Azure 😴😴😴😴

Finally got QLORA fine tuning of Llama 8B working!! Wohooo! 🙌🙌. Will open source my script and pipeline fully. It’s a project to fine tune the LLM to reply as me on my email threads.

Day 16 of building autolead.trythis.app Did competitor analysis today: - Signed up for 20 alternative websites - Went through their flows, noting issues and good ideas - This helped me rethink some of my planned flows and clarified how Reddit integrations can work

Day 17 of building autolead.trythis.app Today I integrated Google Gemini App and langfuse.com observability into the stack. Integrating Langfuse with Gemini wasn’t straightforward (unlike their integration with OpenAI SDK), but after a lot of Googling, I got it working (code

Day 18 of building autolead.trythis.app Didn't have much time today but made a small improvement: added a DB cache for LLM prompts to save on AI costs. Flow: - DB table: prompt (varchar(100)), model, response - Store key as {prompt.slice(0, 10)}{sha256(prompt)} so

Day 19 of building autolead.trythis.app Today I optimized a GPT prompt. This prompt takes a Reddit post, the user’s website summary, the matching score, and user feedback, then generates additional criteria to improve the main matching prompt. Process: - Wrote the

Day 20 of building autolead.trythis.app Today I added a new onboarding step. When a user enters their website URL, the system generates a summary of their product and shows it to them. They can edit it if needed. Once confirmed, I use the summary to find relevant

Spending at least 30 mins walking everyday is one of the best life hacks I know. It refreshes your mind, keeps you healthy, gives you time to reflect, you can spend it hearing a podcast, and you feel so energised after!

Just finished reading the book: man’s search for meaning. A few points that struck me the most: - the meaning of life is personal and can be found in wanting to achieve a goal, loving someone, of suffering. - humans are capable of enduring almost any suffering as long as they

Day 21 of building AutoLead Added a new piece to the Reddit post matching pipeline. The pipeline now takes a user_id: - Fetches all subreddits the user is watching - For each subreddit: - Finds recent posts - Runs the matching logic on each post - Saves the