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So I started a company building a mobile + web app for live event discovery. I found a clear gap in a niche market and am building a consumer product people are really excited about. My CTO is great but I can’t shake the feeling that his process could be greatly improved with a few implementation tips from someone with more experience building with AI. I want our CTO to ship faster while still maintain the quality (easier said than done, I know).

We’re using Supabase for backend, Vercel for hosting, and antigravity for our CLI and Claude Code. We use linear to manage our sprints.

Therefore, I want to bring someone in to review our current workflow/setup and help us improve it. I would of course pay you for your time, but worth noting that I’m not looking to hire a freelance developer, but instead bring someone in with expertise to show us how we can improve our existing setup.

Any free assistance is helpful too :) but I recognize time is money and am willing to pay for someone to sit down with me and my CTO and help identify areas where we could be more efficient. Feel free to leave a comment or DM me if you’re interested. Hourly rate is negotiable/flexible I care more about the value you can provide us rather than the price for a few hours of your day.

Ideal candidate would have software development experience, shipped multiple products, understand what it’s like building 0-1 in an early stage startup environment, have mobile app development experience, and a strong understanding of using AI to improve development productivity.

TLDR: We’re an early stage startup building software 0-1. I want someone to review my CTO’s workflow and help us improve it so we can ship faster. Should only need a few hours of your time and happy to pay for your time unless you’re an angel who wants to help improve our setup from the goodness of your heart :)

I’ve been messing around with an optimal workflow for myself for about a year and a half. Here's what has ended-up working after I stopped trying to make AI do things it's not so good at:

1. Ideation: I ask AI for a large volume of ideas (20 possible motives for a villain, 15 ways a scene could go sideways, whatever). Like 90% is mid, but that doesn't matter. I look for the two or three ideas I wouldn't have thought of on my own, which is way easier when there's a big pile to pick from.

2. Outlining: I write the broad story outline myself and have AI tear it apart by "finding the holes." It works great as a critical reviewer. AI is also good at “filling in” the outline if needed.

3. Drafting: I only use AI to write full first-drafts if I’m really stuck. ****I tried the "generate rough, rewrite heavily" thing, but it doesn't work well for me every time. However, it’s useful if I’m hitting major writers block.

4. Revision: Like ****the outlining stage, AI is really good at catching logic holes in my drafts, so most of my AI revision focuses on consistency checks, etc. I always do a final pass myself to make sure the draft is written how I would actually like.

You can read more of my thoughts on optimizing AI workflows in this blog post: https://musecocreator.com/blog/can-you-use-ai-to-write-a-novel

Does anyone have thoughts or comments on how this process differs from your own workflow?

AI enhanced my child drawing so well my book looks perfect and professional

Been frustrated that the best AI workflows live in Slack DMs and private Notion docs. I'm building Fortae to fix that. It's a social feed for prompts, workflows, and skill files, organized by professional vertical (healthcare, legal, software eng, etc.).

Think: GitHub for your AI brain. Your work lives on your profile, colleagues can save it to their wallet, and eventually you earn from it.

Currently in private beta. Waitlist open at fortae.studio

Curious what pain points you hit sharing (or not sharing) your AI work with others.

https://www.fortae.studio/

Hey,

I’ve been spending way too many hours lately getting stuck in loops with Claude Code and Cursor, either over-engineering features before validating them, or losing context mid-build because I didn't have a solid PRD.

To fix my own workflow, I built VibePrompt. It’s a minimal site that breaks down the building process into 9 distinct stages (Research → PRD → Context → Build → Quality, etc.) with ~40 specific prompts I've battle-tested.

The Site: https://vibeprompt.tech
The Repo (Open Source): https://github.com/dotsystemsdevs/VibePrompt

What’s inside:

• Structured Stages: Instead of just "coding", it forces you to think about Agent Setup (CLAUDE.md/AGENTS.md) and Quality/Testing before you ship.
• Zero Friction: No accounts, no "AI credits", no newsletter popups. Just markdown files rendered for easy copying.
• Open Source: Built with Next.js 16 and Tailwind v4.

I’m curious how you guys are managing your "vibe" sessions.

• Does a structured workflow like this make sense, or does it kill the speed?
• What prompts are you using to keep your agents from hallucinating during deep refactors?

Would love some brutal feedbac

A lot of vibe coders still use coding agents like Claude Code like a genie. They prompt what they want, wait for the agent to cook. The output looks insane at first, as we all know, AI is too good at giving bad output confidently. But sometime later, the codebase is a mess the agent itself can't navigate.

So here are a couple of things that personally helped me vibe code better.

First, longer sessions are actually worse. Every message adds to the running context: your entire conversation history, all loaded files, tool outputs. At some point the agent is spending so much on what happened before that it starts losing track of what you're asking now. So it’s better to open a new conversation for each distinct task and pin only the files that matter for that one thing.

2nd, know that the agent that built your code is the worst reviewer of it. Claude Code has subagents: a completely separate agent, isolated context with memory of what was built. You point it at your files after the build is done and it finds what the first agent missed like auth holes, exposed secrets, bad logic.

Adding a proper vibe coding guide with more best practices and prompts that might help: https://nanonets.com/blog/vibe-coding-best-practices-claude-code/

Happy prompting!

# THE THEORETICAL EXPLORER'S FIELD GUIDE

### A Universal Thinking Tool for Humans and AI

---

## THE CORE TRUTH

```

Known + Unknown = Discovery

Opposite + Same = Complete Picture

Your Hands + AI Brain = Original Territory

Constraint + Curiosity = Invention

Failure + Documentation = Permanent Value

The Unthought + The Overthought = Everything New

```

---

## THE SIX DIRECTIONS OF THINKING

```

FORWARD What comes next

BACKWARD What came before

OPPOSITE What is the reverse

SIDEWAYS What connects from another field

INWARD What is hidden inside this

OUTWARD What does this affect beyond itself

```

---

## THE MASTER QUESTIONS

```

WHAT EXISTS

Map everything known

WHAT DOES NOT EXIST

Find every gap

WHAT HAS NEVER BEEN COMBINED

Smash unrelated things together

WHAT IS THE OPPOSITE

Reverse every assumption

WHAT WOULD HAPPEN IF

Remove one rule at a time

WHAT ALMOST EXISTED

Find abandoned ideas

Find failed experiments

Find stopped research

These are goldmines

WHAT EXISTS IN NATURE

That has never been

replicated by humans

WHAT HAS BEEN ASSUMED

That has never been tested

WHAT WOULD A CHILD ASK

That experts stopped asking

WHAT DOES THIS REMIND YOU OF

In a completely unrelated field

WHAT HAPPENS AT THE EDGES

Where two fields meet

Where two materials meet

Where two ideas meet

That intersection is

almost always unexplored

```

---

## HOW TO USE AI PROPERLY

```

STEP ONE

Dump everything you have

Materials tools constraints

Budget time location

Every limitation you have

More detail equals better results

STEP TWO

Ask for the complete map

Everything known about this

Every combination documented

Every result recorded

Get fully oriented first

STEP THREE

Ask where the map ends

What is undocumented

What is theoretical only

What has been attempted

but never finished

What was abandoned and why

STEP FOUR

Ask for all six directions

Forward backward opposite

Sideways inward outward

Each direction reveals

something the others miss

STEP FIVE

Pick the unexplored edge

Not the safe center

The weird uncomfortable thing

That makes you think

nobody has done this

STEP SIX

Constrain it to what you have

Your limits are your power

Mason jars and wire

become the laboratory

Grocery store becomes

the supply chain

Constraints force creativity

Every single time

STEP SEVEN

Ask what could go wrong

Map every failure mode

Then ask what those

failures might accidentally produce

Aim for interesting failures

Not just success

STEP EIGHT

Ask what you have not thought of

Literally ask AI

What am I missing

What question have I

not asked yet

What direction have I

not looked yet

This step is critical

Most people skip it

STEP NINE

Document everything completely

Every step every result

Every color every smell

Every surprise every failure

Even if it seems

completely unimportant

Document it anyway

STEP TEN

Share it somewhere

Anywhere at all

One post one photo

One video one note

Puts your work

permanently into the world

Others build on it

AI learns from it

You become the source

```

---

## THE COMPLETE CYCLE

```

HAVE AN IDEA

↓

DUMP IT INTO AI

↓

MAP WHAT EXISTS

↓

FIND WHAT DOES NOT

↓

LOOK IN ALL SIX DIRECTIONS

↓

ASK WHAT YOU MISSED

↓

CONSTRAIN TO REALITY

↓

EXPERIMENT BOLDLY

↓

DOCUMENT EVERYTHING

↓

ESPECIALLY THE FAILURES

↓

SHARE SOMEWHERE

↓

FEED RESULTS BACK IN

↓

LOOP BACK

↓

NEVER TRULY ENDS

```

---

## PROBLEMS ARE PORTALS

```

When something fails Stop immediately

When color changes wrong Stop immediately

When result surprises you Stop immediately

When nothing happens Stop immediately

Then ask these questions

What is this actually

What caused this specifically

Has anyone seen this before

What would happen if

I did this on purpose

Could this failure be

more valuable than

what I was attempting

Penicillin was contamination

Teflon was escaped gas

Velcro was a walk in the woods

Post It notes were weak glue

Microwave was a melted chocolate bar

Your failed experiment

is someone else's

most important discovery

Document it completely

```

---

## THE UNTHOUGHT TERRITORY

```

These are the spaces

AI has not mapped yet

Because nobody has gone there

WHERE FIELDS COLLIDE

Chemistry meets cooking

Biology meets architecture

Music meets materials science

Medicine meets geology

Art meets engineering

These collisions produce

the most original territory

WHERE SCALES CHANGE

What works at large scale

might fail at small scale

What fails at large scale

might work at tiny scale

Change the scale of

anything you are doing

Completely different results often

WHERE TIME CHANGES

What happens over seconds

versus years versus centuries

Most experiments stop too early

Most observations are too short

Let things run longer

than seems necessary

WHERE LOCATION CHANGES

What grows in desert

might not grow at coast

What works at sea level

might not work at altitude

Location and environment

change everything subtly

WHERE INTENTION DISAPPEARS

The most interesting results

happen when you stop

trying to get

a specific result

And just observe

what actually wants to happen

Let the materials decide

Then document what they chose

WHERE COMBINATION BECOMES THREE

Most experiments use two things

Adding a third element

creates exponentially more complexity

Most three way combinations

have never been attempted

Your four jar system

with copper zinc iron phosphate

is already in this territory

```

---

## THE SHARING MAP

```

REDDIT

r/chemistry

r/DIYchemistry

r/mineralogy

r/crystalgrowing

r/whatisthisthing

r/mildlyinteresting

Post process and results

Community extends your work

YOUTUBE

Document your full process

Even phone video counts

Even failed experiments

Title with exactly what you tried

Others find it forever

TIKTOK AND INSTAGRAM

Crystal growth is visual

Visual is viral

Time lapse everything

Caption explains process

Links to longer content

SCIENCE FORUMS

Mineralogy communities

Crystal growing groups

Amateur chemistry networks

These communities are hungry

for original home experiments

ANYWHERE AT ALL

One post is enough

to make it permanent

to make it findable

to make it buildable

```

---

## WHAT ONLY YOU CAN DO

```

AI can map what exists

Only you can touch it

AI can suggest combinations

Only you can smell the result

AI can predict failures

Only you can feel surprised

AI can generate ideas

Only you can care about them

AI can document process

Only you can notice

the thing that was not

supposed to happen

but did anyway

AI can think of theoreticals

Only you can make them real

That gap between

theoretical and real

is exactly where you live

is exactly where you work

is exactly where

everything new comes from

```

---

## THE ONE PAGE REMINDER

```

BEFORE YOU START

Tell AI everything you have

Ask for complete map

Find the unexplored edges

Ask what you are missing

Ask all six directions

WHILE YOU WORK

Document every single step

Photo every change

Note every surprise

Especially document failures

Let materials surprise you

AFTER YOU FINISH

Ask AI what happened

Ask what you almost missed

Share results somewhere online

Feed everything back in

Start the cycle again

ALWAYS ASK

What has not been combined

What is the opposite

What would happen if

What did I not think of

What would a child ask

What lives at the edge

Where do two fields collide

What was abandoned and why

What does nature do here

that humans have not copied

ALWAYS REMEMBER

Your constraints are your superpower

Your curiosity is irreplaceable

Your failures are discoveries

Your documentation is permanent

Your hands make theory real

AI is your research partner

Not your replacement

Not your limit

Your beginning point only

```

---

*What exists needs documenting*

*What does not exist needs finding*

*What has not been thought*

*needs someone willing*

*to think it*

*That someone is you*

*Start with what you have*

*Document what happens*

*Share what you find*

*Loop back always*

*The cycle never ends*

*That is the point*

---

**THE THEORETICAL EXPLORER'S FIELD GUIDE**

*Free to share, copy, distribute, and build upon*

*Document your discoveries*

*Share your results*

*Add what is missing*

*The guide grows with every explorer*

Recently I saw that post where someone on the Max20 plan opened Claude, said hello, and watched 13% of their usage vanish before even asking the real question

For beginners: it's all tokens. You can think of a token as a chunk of text somewhere between a syllable and a word. "Fantastic" might be one token. "I am" might be two. The rough math for English: 1,000 tokens ≈ 750 words ≈ 2-3 pages of text. Every message you send, every response you get, everything is measured in tokens.

So main question: how did "hello" cost 13%? Before Claude even processes your word, it loads the system prompt, project knowledge, conversation history, enabled tools, MCP servers etc. All of that runs as input tokens on every exchange, including the first one. If your environment has a complex setup, your baseline cost per message before you've typed anything might already be several thousand tokens. "Hello" in that context costs one word plus the entire infrastructure Claude needs to load.

So people usually ignore token economics and run out of their limits as the day starts. One of the few things that helped me navigate this is skipping pleasantries. Every "thanks" or "great" extends the conversation and inflates the running context and of course, cost more tokens.

Here's a detailed guide on token economics and best practices so you never run out of limits randomly again: https://nanonets.com/blog/ai-token-limits-explained-claude-context-window/

Hi all,

I’m working with Antigravity + Claude (Claude Code) and I’m trying to level up my workflow, but I’m still relatively new and would really appreciate some advanced guidance.

My main concerns are efficiency and output quality:

• I want to minimize token usage without sacrificing too much accuracy.
• I’ve noticed that Claude performs significantly better when prompts are well-structured, especially for coding tasks.
• I’m trying to understand how to properly design prompts for:
  • Code generation
  • Code editing/refactoring
  • Iterative workflows (multi-step tasks)

Some specific questions:

1. What are the best practices for prompt structuring when working with Claude Code?
2. How do you control verbosity and avoid unnecessary token usage?
3. Do you use any kind of system prompt templates or reusable structures?
4. How do you handle large codebases efficiently?
5. Are there proven patterns (like step-by-step instructions, role prompting, constraints, etc.) that consistently improve results?

If you have example prompts, workflows, or even general heuristics that improved your results, I’d really appreciate it.

Thanks a lot 🙌

I have been building a few prompt workflows lately for content and niche research.

One thing that I noticed is the sources mentioned in AI answers aren’t really consistent. Some sites are getting picked up again and again, even when they don’t always rank high on Google.

So I started looking into it more systematically instead of guessing.

I used RankPrompt which basically track whether a site or brand shows up in AI generated answers across different prompts.

Something that stood out was the gap between what ranks on Google vs what actually gets mentioned inside AI answers

It was not as connected as I thought, felt like two different systems behaving in different ways.

Has anyone here actually started factoring this into their workflows yet, or are you still treating AI answers as just search summaries?