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I launched a Next.js + FastAPI + Supabase boilerplate for AI agent apps. Here's what was harder than expected.
▲ 6 r/AiBuilders+2 crossposts

I launched a Next.js + FastAPI + Supabase boilerplate for AI agent apps. Here's what was harder than expected.

I've built a few AI agent apps, and 80% of the work each time was the same plumbing. So I packaged it. Things that took far longer than I expected:

  1. Logins across two languages. Supabase signs users in on the Next.js side; FastAPI has to verify that token on every request, including Supabase's newer asymmetric keys.

  2. Row-level security on the vector table. Easy to forget, and without it a similarity search can return another customer's documents.

  3. Streaming that survives real networks. I store every event so a dropped connection resumes from Last-Event-ID instead of starting over.

  4. Agent cost. Without a step limit and a token cap, one confused agent can loop for a long time. Every run is now metered, with a monthly budget per workspace.

The free FastAPI + LangChain starter is MIT: https://github.com/The-AppLab/ultimate-fastapi-langchain-boilerplate

Disclosure: I'm the maker, and the full stack is a paid product (link in comments if anyone wants it). Happy to answer questions about any of the above.

u/Ok_Share7278 — 4 days ago
▲ 3 r/AiBuilders+1 crossposts

I built a blog platform where the user is the AI agent, not the human

Your agent signs up with one API call, sends markdown and gets a live URL back. No login page, no dashboard. The only thing it needs from you is an email, since that's how you get the key back.

I wanted something dead simple and super fast for agents to blog online. Tech people have been doing this kind of thing with OpenClaw and Hermes Agent for a while, but it was hard for normal people to set up.

Now with Muse, Grok Bot and the rest, everyone's getting an agent, and most of the internet still assumes a human is clicking.

To try it, tell your Muse or Grok Bot or claude or whatever you use to just check out SlopIt and signup to it, create a post about something.

https://blog.slopit.io/hey-agents/

u/asenna987 — 6 days ago
▲ 14 r/AiBuilders+12 crossposts

Promoting a small business on Reddit: a free checklist, with a furniture-maker example

For a furniture maker, a useful Reddit post could explain which measurements a customer should take before ordering a dining table: room size, space to move the chairs, and the delivery route. That gives people something practical to use and a specific question to ask next.

Here is a simple checklist for turning that kind of expertise into a community post:

  1. Find a community discussing the actual buying problem. Read its promotion rules and use the designated thread if it has one.

  2. Answer one customer question in the post itself. Make the explanation useful before asking anyone to visit a website.

  3. Disclose your connection to the business and use a link only where permitted.

  4. Save the permalink and check what happened after posting. An entry in your own profile does not by itself prove other readers can see it.

  5. Return for real questions. Keep post views, website visits, inquiries and paid orders as separate numbers.

I'm with the ThreadFox team at AMF Indiana. We put the process into a free guide you can follow with a spreadsheet:

https://threadfox.vip/guides/reddit-self-promotion?utm_source=reddit&utm_campaign=tf-businesspromotion

ThreadFox also offers a paid toolkit for your own AI assistant and browser, plus a managed campaign service if you want us to do the research, posting and follow-up. The options and published scope are here:

https://threadfox.vip/?utm_source=reddit&utm_campaign=tf-businesspromotion

u/investigatormaker — 10 days ago
▲ 8 r/AiBuilders+4 crossposts

Multi-Agent Collaboration With Tools You Already Own

Coding agents are getting smarter and smarter at writing code. A new idea has been gaining traction: what if instead of giving a task to a single agent, you give it to a team of agents working collaboratively to solve the problem? It sounds complex, but there's a surprisingly simple solution.

Herder already gives you the core ability you need: one agent can talk directly to another agent. Combined with the coding tools you already have — Claude Code CLI, Codex CLI, or whatever's in your stack — you've got everything for a full multi-agent workflow.

Here's the pattern:

  1. One agent leads — takes ownership and coordinates using Herder's agent-to-agent communication
  2. Delegation — passes work to other agents through Herder
  3. Review loop — completed work cycles through peer review
  4. Iteration — repeats until requirements are met

No extra subscriptions, no API key juggling — just leverage Herder's built-in agent-to-agent messaging and the tools you've already got.

I built a repository showing this in practice with a Claude Code skill:
https://github.com/alexstrilets/panel

It demonstrates how simple and effective this approach can be when you use what's already at your fingertips.

u/RelativeActive5306 — 10 days ago
▲ 8 r/AiBuilders+1 crossposts

Hiring: Hands-on AI Systems Lead / Founding AI Engineer — want someone who actually builds

I’m the founder of a growing services business and we’re trying to turn the company into a genuinely AI-native operation.

I’m posting anonymously because I care more about finding the right builder than promoting the company.

This is not a “make us a chatbot” job.

We already have real customers, employees, operational workflows, CRM data, research data, calls, internal knowledge and a bunch of systems that currently require humans to connect the dots.

The problem I want someone to own is essentially:
How do we build an intelligence layer across the company?

Some examples of what we’re working on:

Making Zoho function more like an AI-native CRM
Giving agents the ability to safely read/write CRM data and trigger workflows
Building a company “second brain” that agents can actually reason over
Creating AI agents for research, customer delivery, sales and internal ops
Voice agents for onboarding, qualification, follow-ups and other workflows
Building structured customer state so AI understands what has happened, what needs to happen next and why
Evaluating new models/providers and deciding when switching actually produces ROI
Creating proper evals instead of deciding whether an AI workflow “feels good”
Figuring out where agents make sense versus boring deterministic software
Reducing expensive/manual human work without destroying quality

Current environment includes things like:
Zoho / Supabase / Postgres / Next.js / APIs / webhooks / automation tools / LLM APIs / voice AI.

I am specifically looking for a player-coach.

Someone who can personally open their laptop and build the difficult parts, but can also lead a very small engineering/automation team and get other people shipping.

You might be a fit if:
You have ~5–8 years of strong software/product engineering experience
You’ve spent the last 2–4 years going very deep into applied AI/LLMs
You have actually shipped AI systems into production
You understand backend architecture, APIs, databases and integrations
You’ve worked with agents, tool calling, structured outputs, RAG/knowledge systems, evals, voice AI, etc.
You think about latency, failure modes, observability and cost
You have strong opinions about what should not use an LLM
You can take an ambiguous business problem and turn it into something working
You can lead a couple of engineers without becoming a full-time manager
You are ridiculously hands-on

What I don’t want:
Someone whose main skill is managing Jira
Someone trying to graduate out of coding
“AI consultants” whose experience is mostly prompting ChatGPT
People who want to architect a 12-service distributed system before we have 1,000 users
People obsessed with whichever agent framework is fashionable this month
People who need a PRD telling them exactly what to build
One thing I care about a lot is technical investment judgement.
New models and AI products come out constantly.

I want someone capable of saying:
“This new capability could reduce X workflow from 20 minutes to 5 minutes. It would take us three days to prototype, cost approximately $Y/user, these are the failure modes, and this is how we should test whether it’s worth deploying.”

Rather than:
“This new model looks cool, we should use it.”
The hiring process will be practical.

I’ll probably give shortlisted people a messy real-world architecture problem involving customer data + CRM + agents + human workflows and spend most of the interview discussing how you’d approach it.

I care significantly more about things you have built and how you think than degrees, FAANG logos or certifications.

Could be titled AI Systems Lead / Founding AI Engineer / Head of AI Systems depending on seniority.

Remote.

If this sounds like you, DM me with:
What you’ve built
Your GitHub / portfolio / demos if available
The most complicated AI system you’ve shipped
One AI architecture decision you got wrong and what you learned from it
Location/timezone
Compensation expectations

Please don’t send me a generic cover letter.

I’d much rather receive:
“Here are three things I built. Here’s how they work. Here’s what broke.”

ANNUAL SALARY BUDGET : 22-30LPA, depending on experience

reddit.com
u/boss1010indianking — 8 days ago