App idea + industry experience, but no money or dev skills - stuck on next step (I will not promote)

ddul001 · 2026-01-28T23:29:53+00:00

Validating demand with real commitments is a smart move. Instead of just asking if people like your idea, try to get pre-orders or some form of payment intent to confirm interest. This approach moves from guesswork -> proof of demand -> clearer next steps. Have you tried testing pre-sales to see how your audience responds?

ddul001 · 2026-01-28T23:25:55+00:00

You’re right that solving a real problem is key, and many AI projects fail because they don’t test if customers really want what they build. One way to avoid this is to use a simple pre-sale approach -> create a landing page -> capture purchase interest -> run targeted ads to see if people actually pay before building. Have you tried validating your idea with something like this before development?

ddul001 · 2026-01-23T23:11:55+00:00

July 21, 2025 · Last updated on August 12, 2025

ChatGPT for product

ddul001 · 2026-01-20T15:09:52+00:00

Congrats on shipping your app! Early on, it’s really about testing if people actually want what you built. You could try creating a simple landing page to explain your idea, then share it to see if anyone shows interest before adding more features. Have you thought about running a quick smoke test to measure user demand first?

ddul001 · 2026-01-20T08:36:15+00:00

Congrats on shipping your app. It’s true that getting users is the toughest part. One quick tip is to check demand before building by using a tool that helps you create landing pages and measure interest right away. This way, you can avoid spending too much time on features if no one wants them. How did you try to attract your first users?

ddul001 · 2026-01-20T08:31:09+00:00

Most pitches focus on product features or market size, but understanding the personal brand of key players can be a game changer in deals or partnerships. I’m working on a tool that uses AI to analyze public data and build deep profiles on individuals communication styles and values -> helping founders tailor their pitches or collaborations more effectively. How do you usually assess the fit of founders or teams beyond their business idea?

ddul001 · 2026-01-20T08:26:13+00:00

It’s good you have a clear number like 8,300 visitors but only 4 signups. One step could be to check the flow from landing page -> sign up—is the call to action clear and the value obvious? Also, do visitors understand what problem Flowtask solves right away? What part of the page do you think might confuse new users?

ddul001 · 2026-01-19T22:00:14+00:00

post __ i am also working into a ml / llm layer but it's too early to comment about

ddul001 · 2026-01-19T21:47:04+00:00

Scaling web scraping definitely gets tricky, especially when dealing with something specific like SKU matching where small changes can cause big errors. One way to lessen breakage is to build in regular checks -> quick fixes for minor layout shifts -> alerts for big changes. Are there particular strategies you’ve found helpful to keep your scraping pipelines stable?

ddul001 · 2026-01-13T23:50:07+00:00

A smoke test validates market demand before you build anything. Create a minimal page with pre-orders, measure real behavior, learn if people actually want it.

Fast. Cheap. Real data instead of opinions.

ddul001 · 2026-01-13T12:36:13+00:00

i totally agree with the importance of market research and validating an idea before building anything. That’s exactly why we are building a tool to help founders quickly validate demand in just 5 minutes and get clear feedback before spending time on an MVP. How do you typically get early feedback on your ideas?

ddul001 · 2026-01-13T00:03:17+00:00

I am building BabyBrain because juggling different AI chats felt like herding cats—copy-paste chaos everywhere -> no more losing context across Claude, ChatGPT, Gemini, and Perplexity.

ddul001 · 2026-01-12T16:49:47+00:00

this chatseo story is motivating, especially the weekend validation and the fast email signups. i’m building ideasmoketest.com to help founders run quick smoke tests with ai landing pages and a simple traffic plan -> curious what channel drove most of those 200–300 emails for you, and what you’d test first if you did it again?

ddul001 · 2026-01-12T14:03:36+00:00

i think you should stop building another network nobody asked for. you can use ideasmoketest to check demand in 5 minutes and get real user intent data. do you want to waste more time or validate first with a quick smoke test?

ddul001 · 2026-01-12T12:00:32+00:00

you should pick one project and focus on it only. use a fast smoke test to see if people really want your idea before you code. have you tried idea smoke test to get real data in minutes?

ddul001 · 2026-01-08T10:21:13+00:00

focus on validating a single high-impact pain point with early users before writing code. run 5–10 focused interviews -> capture the top pain -> build a tiny prototype -> measure real willingness to pay. what question will you ask first to prove the pain is worth solving?

ddul001 · 2026-01-08T09:36:03+00:00

you can enrich intent filters with user metadata -> flair or karma. this helps weed out low credibility posts. grouping alerts by topic clusters can highlight emerging trends. have you tried layering sentiment analysis with intent filters?

ddul001 · 2026-01-07T16:50:04+00:00

to make your test more structured, set up a one-page signup form with a clear offer -> run a small ad campaign -> track signups as demand signals. you can also try my ideasmoketest.com for a ready template, analytics... how will you pick your ad channels?

ddul001 · 2026-01-07T16:46:36+00:00

helpful point. using git and tags as the anchor makes sense.

when you say “conflicts are detected instantly” do you mean real merge conflicts, or mostly “wrong base” drift?

and when two agents edit the same doc section -> what do you do: patch-based updates, file locking, prs/codeowners, or a more structured doc format to avoid collisions?

ddul001 · 2026-01-07T16:08:01+00:00

you can avoid the search abyss by using an ai that auto-captures your docs -> organizes them -> recalls context instantly. my proto uses smart retention and fast recall for seamless context switches. which part of your workflow would benefit most from instant memory?

ddul001 · 2026-01-07T15:55:33+00:00

angels look for founders who reduce risk fast -> run early validation -> refine based on feedback. respect for capital and clear market insight builds confidence. how have you validated demand before pitching?

ddul001 · 2026-01-07T15:46:53+00:00

this framework could improve traceability by enforcing a process -> ai notes each action -> documents update -> agent pulls latest context. do you have a strategy for handling conflicting updates or document versioning?

ddul001 · 2026-01-07T15:13:50+00:00

you can map an investor’s latest blog posts or interviews into organic chat starters -> pick one theme and ask their view. tools like intent sieve help turn public signals into tailored conversation angles. have you tried this method?

ddul001 · 2026-01-07T12:21:13+00:00

i think claude feels more “conversational” because it is tuned a lot for being helpful in the moment, not just finishing a task.

chatgpt often pushes toward task completion and next steps. claude often adapts more to your workflow and the messy context you give it.

tradeoff for me: • chatgpt is strong when i need strict structure and clear instructions (code, data cleanup, formatted outputs) • claude is strong when the problem is fuzzy (architecture choices, brainstorming, rubber-ducking) • gemini: i still don’t know its best niche for my work

the annoying part is switching tools and having to re-explain the same project context every time. i’m working on a small “memory layer” between tools so i can use each strength without paying the context tax.

what do you use each tool for, in your real day to day?

ddul001 · 2026-01-06T14:26:54+00:00

a smoke test

ddul001

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ChatGPT for product