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Google Search console started showing "AI Overview stats" for some of my sites (the high traffic ones, it shows "page not found" for low traffic sites on this). Might be an interesting peek for people to see what they've lost to AI overview in terms of SEO traffic. It shows only page/country/device type and no direct query info.

https://search.google.com/search-console/performance/search-...

It's not impossible, it's just difficult :) Luck plays part like in anything, but consistency and persistence also makes it possible for luck to happen.

I'd recommend scratching your itch first and then finding people in a similar situation. You know enough about your own problem to be able to design a solution around it, and you likely know some other people around that as well. Slice that segment into something worth attacking first. Bill Aulet defined the first group of people worth solving for as a "beachhead market". This is his test for that first segment:

- the customers within the market should all buy similar products

- the customers within the market should have a similar sales cycle and expect products to provide value in similar ways

- the customers within the market talk to each other, and there is a high probability of word-of-mouth referrals, where customers can serve as a “compelling and high-value references for one another in making purchases”.

The third one is for me the key to open doors as a solo founder. You probably don't have the marketing budget to compete with large companies, so word of mouth and happy customers will be your first best marketing strategy. SEO is black magic, and from my experience takes a long time to actually start working - happy customers doing word of mouth and writing/recommending you also helps significantly with that.

Once this segment opens the doors, things will likely change for something else, then you follow the trail.

Hey HN,

Had to record some videos and ended up building a simple teleprompter browser app (all data is stored in local storage, never leaves the browser). It has basic markdown highlighting support (bold/italic) and works with most clickers to speed up/slow down the reading speed.

I found out about dialectical bootstrapping yesterday, looks like a good way to get AI agents to think a bit deeper, but seems to be one of those techniques that help humans do better work as well. In a nutshell, it's a systematic "prompt" for thinking about plausible alternatives and then providing a second guess.

tdd is very present in our process, it's mandated by CONTIRIBUTING.md with very specific instructions on how to structure tests.

hahaha. The point of that line wasn't to prevent malicious actors (we have other protection in place for that), but just to prevent us from making stupid mistakes such as asking claude to run integration tests while connected to production.

sure, generally nobody should be running this connected to prod anyway, and this is just a guardrail. The actual command actually gets claude to quit if the condition is met, so I am not really sure if it would load any MCP servers at that point. Here's the line

- You are NEVER allowed to work if the environment `AWS_PROFILE` variable is equal to `support`. When starting, check that condition. If it's met, print an error message and exit instead of starting.

We use claude code, running it inside a docker container (the project was already set up so that all the dev tools and server setup is in docker, making this easy); the interface between claude code and a developer is effectively the file system. The docker container doesn't have git credentials, so claude code can see git history etc and do local git ops (e.g. git mv) but not actually push anything without a review. Developers review the output and then do git add between steps, or instruct Claude to refactor until happy; then git commit at the end of a longer task.

Claude.md just has 2 lines. the first points to @CONTRIBUTING.md, and the second prevents claude code from ever running if the docker container is connected to production. We already had existing rules for how the project is organized and how to write code and tests in CONTRIBUTING.md, making this relatively easy, but this file then co-evolved with Claude. Every time it did something unexpected, we'd tell it to update contributing rules to prevent something like that from happening again. After a while, this file grew considerably, so we asked Claude to go through it, reduce the size but keep the precision and instructions, and it did a relatively good job. The file has stabilized after a few months, and we rarely touch it any more.

Generally, tasks for AI-assisted work start with a problem statement in a md file (we keep these in a /roadmap folder under the project), and sometimes a general direction for a proposed solution. We ask Claude code to an analysis and propose a plan (using a custom command that restricts plans to be composed of backwards compatible small steps modifying no more than 3-4 files). A human will read the plan and then iterate on it, telling Claude to modify it where necessary, and then start the work. After each step, Claude runs all unit tests for things that have changed, a bunch of guardrails (linting etc) and tests for the wider project area it's working in, fixing stuff if needed. A developer then reviews the output, requests refactoring if needed, does git add, and tells claude to run the next step. This review might also involve deploying the server code to our test environment if needed.

Claude uses the roadmap markdown file as an internal memory of the progress and key conclusions between steps, and to help with restoring the progress after context resets. Pretty much after the initial review, Claude only uses this file, we don't look at it any more. Once done, this plan file is thrown away - tests and code remain. We occasionally ask it to evaluate if there are any important conclusions to record in the architectural design records or contributing guide.

We solved a similar issue by blocking free user traffic from data centres (and whitelisted crawlers for SEO). This eliminated most fraudulent usage over VPNs. Commercial users can still access, but free just users get a prompt to pay.

CloudFront is fairly good at marking if someone is accessing from a data centre or a residential/commercial endpoint. It's not 100% accurate and really bad actors can still use infected residential machines to proxy traffic, but this fix was simple and reduced the problem to a negligent level.

it's paradox in a sense that reducing complexity actually ends up increasing complexity; Tognazzini originally proposed it as a complaint against Tesler's Law ("Conservation of complexity"). Tesler observed that complexity stays the same when people try to reduce it. Tognazzini suggested that the complexity doesn't stay the same, but actually increases.

I just checked, and have about 9K connections on LinkedIn. I assume with the ability to pay for post promotion you could get a similar reach by paying linkedin a few bucks.

This was for a tool to speed up making educational videos, so I tried to reach out to people who were doing online courses and educational materials.

Linkedin for a B2P product. I posted a few questions asking if anyone had similar issues, and got directly in touch with about 20 people who responded to involve them in customer research, then kept in touch with them as I was developing the product for feedback. Those 20 by word of mouth led to a bunch more people trying it out. It's difficult to put a specific number on whether that was 100 or a bit more or fewer, but a few cycles of word of mouth from happy users got me over the 100 users easily.