last night, I had a half-finished workflow and no energy to keep going. so I started ralph, closed my laptop, and went to bed. this morning, 6 updates. everything working.
I didn't write a single line.
what ralph actually is
ralph is an AI that builds software while you're away. named after the simpsons character known for naive, relentless persistence.
you give it a list of small tasks. it picks one, builds it, checks if it works, saves it. picks the next one. repeats until done.
while you sleep. while you eat dinner. while you do anything else.
why normal AI coding breaks
most people open an AI coding tool with an idea and no plan.
45 minutes later they're fixing the same bug for the third time. the AI forgot what you were building. you're frustrated and nothing shipped.
this happens because tasks are too big.
one feature has 20 pieces. the AI tries to remember all of them at once. it can't. it gets confused. it makes stuff up. you end up babysitting.
ralph fixes this by breaking work into pieces small enough that the AI finishes each one before it forgets what it's doing. no confusion. no asking you for help every 5 minutes.
the insight that makes it work
engineering teams have worked this way for decades.
sticky notes on a board. pull one, complete it, put it back. grab the next one.
ralph is the AI version of that workflow.
you're not telling the AI how to build each piece step by step. you're describing what the finished product should do.
you become the product designer. the AI becomes the engineering team.
how it actually works
you write a description of what you want the feature to do. what should happen when someone clicks this button? what should the screen look like?
that description gets broken into small tasks. each one simple enough for the AI to finish in one shot.
ralph works through the list. picks a task. builds it. checks if it works. if it passes, saves the work and moves on. if it fails, logs what went wrong.
next round starts fresh. reads what happened last time. learns from mistakes. keeps going.
you set a limit. 10 rounds, 14 rounds, 20 rounds. it runs until everything works or hits your limit.
each round starts with a clean slate. no confusion carrying over from earlier work.
the workflow
step 1: describe what you want
open your AI coding tool. start talking.
"i want users to filter tasks by priority. high, medium, low. a dropdown with all options. selecting one filters the list."
talk for 2-3 minutes. describe everything you want. then tell the AI to turn your rambling into a formal list of requirements.
step 2: break it into tasks
each task needs a clear way to check if it worked. pass or fail. yes or no.
good: "add a priority column that defaults to medium." "dropdown shows options: all, high, medium, low."
bad: "make it good." "make it pretty."
the AI needs to know when it's done without asking you.
step 3: run ralph
start it from your computer. it loops through tasks automatically.
grabs one. builds it. tests it. saves if it works. grabs the next one.
repeat until done.
why this beats everything else
fresh start every round. each task begins clean. no accumulated confusion from earlier work.
clear success criteria. the AI knows if it worked without asking you. pass or fail. binary.
compounding knowledge. every round logs what it learned. next round reads those logs. same mistakes don't repeat.
the key insight
spend your time on the description.
vague description = garbage output. tasks too big = failures. unclear success criteria = AI doesn't know when to stop.
an hour on requirements saves 10 hours of fixing.
the description is your contract with ralph. get it right and the rest is automatic.
what it costs
typical ralph run: 10 rounds. roughly $30 total.
one builder used ralph to deliver, review, and test an entire app for under $300. would have cost $50,000 to hire someone.
during a startup hackathon, a team used it to ship six different projects overnight.
someone built an entire programming language from scratch using ralph. took under 3 months.
what to expect
ralph is not magic. you still review what it built. you still test it yourself. you still fix edge cases.
typical result: ralph gets 90% there. you spend an hour fixing the last 10%.
the win is turning a full day of focused work into an hour of cleanup. and running it while you sleep.
two ways to run it
AFK ralph: set it running overnight. wake up to finished features. good for straightforward tasks with clear requirements.
hands-on ralph: run one round at a time. review each update. steer when needed. good for complex features where you want more control.
even hands-on, it's faster than normal AI prompting. the structure keeps you focused on what needs to happen, not how to make it happen.
why this makes you untouchable
right now, most builders spend 6-8 hours writing code for every feature. you spend 1 hour on requirements and wake up to finished work.
that's not a small edge. that's 5x output with the same hours.
compound that over 3 months. while everyone else is still debugging manually, you've shipped 10 projects. built a portfolio. landed clients. stacked skills they haven't even started learning.
the gap between "knows ralph" and "doesn't know ralph" will be massive. and it's closing fast.
getting started
ralph is free and open source: github.com/snark-tank/ralph
tell your AI tool to set it up. it will download the files, explain the workflow, help you configure.
first time: 30 minutes to understand. second time: 10 minutes to start.
the window
3 months from now this will be in every youtube tutorial and paid course.
right now most people don't know it exists. the ones who do are shipping 10x more than everyone around them. and nobody understands how.
that gap closes fast.
I put together a complete ralph starter kit: the scripts, templates, example files, and the exact prompts I use to generate task lists.
like, repost, and reply "RALPH" and I'll send it to you (must be following so I can DM).
