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Sep 3 10 tweets 2 min read Read on X
everything you need to build reliable AI systems:
most people want an AI that can operate autonomously

they want it to make every decision, handle entire workflows, and figure everything out without guidance

the result is different outputs every time with little consistency
when an AI makes all decisions, you get random results

ask Cursor to "build a customer service chatbot" 10 times and you'll get 10 completely different solutions

but with automating business tasks you need predictability
the right way: map out how YOU do the task manually first

write it like training instructions for a dipshit intern

every decision point, every step in order
here's an example with cold email reply management:

step 1: reply comes in you read it

step 2: categorize response type (interested / not interested / wrong person / bad timing)

step 3: if interested - ask for their availability

step 4: check if their suggested time matches your calendar

if available - send calendar invite

if not available - follow up with open times
notice there are multiple decision points here:

first categorization: what type of response?

second categorization: does timing work?

each decision has clear options and next steps
now here's where AI fits in:

don't ask an AI to design this entire process as everyone has their own unique processes

but you can ask it to make specific choices at each decision point
for cold email reply management that’s going to be:

"what type of response is this:

> interested
> not interested
> wrong person
> bad timing?
"
then route to your predetermined next action based on the category
for the second decision point:

"does their suggested Tuesday 2pm conflict with my calendar? yes or no?"

if yes - send alternative times template

if no - send calendar invite
to recap this framework for building reliable AI systems:

> map out your manual process step by step
> identify each decision point in the workflow
> turn decisions into clear categories for AI to choose from
> let AI categorize and route, not create

all you’re doing is designing the process and the AI helps route everything

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More from @tyler_agg

Sep 3
how to give an AI agent memory to make it smarter over time:
most AI system treats every conversation like it's meeting you for the first time

for example a customer first complains about a broken chair, then the AI responds like it's a new issue

but the same customer complains about another broken chair 2 months later

but in most cases an AI system still treats it like a new convo and acts like it's never happened before
what an AI with memory would do:

"Hello David, following up on your previous case from August where you experienced issues with an ergonomic chair, I sincerely apologize this is happening again. We appreciate your continued trust since 2023..."

it references past interactions and treats customers like actual humans
Read 14 tweets
Sep 1
here's everything you need to become an AI developer as a complete beginner (step-by-step):
most people jump straight to AI tools without learning the fundamentals

they think "I'll just use ChatGPT API and build something cool"

but building AI tools is 90% traditional software engineering and 10% AI

learn to code first and it’ll make building AI apps 100x easier
step 1: learn Python basics

> for loops
> lists
> classes
> objects
> if/else statements

you need one programming language to understand how coding works

Python is a great choice if you want to get into AI
Read 10 tweets
Aug 29
how to build an internal chatbot that answers your team's SOPs and FAQs (the exact roadmap):
every growing company has this problem:

your team constantly asks the same questions about processes, SOPs, and company policies

you end up answering "where's our onboarding doc?" or "what's our refund policy?" 20x a week
most chatbot solutions look scary and technical

they require embedding, vector databases, maintaining all this data, etc

but there's a much simpler way that works just as well using tools you already have
Read 11 tweets
Aug 28
here's everything you need to make money with AI (the only 2 paths that actually work):
there are only two ways to make money with AI

most people get confused because they see all the time on twitter about how people are making six figures with this automation or using this tool and shit like that

but when you strip away all the noise, it comes down to just these two paths
path 1: use AI to amplify what you're already good at
this is for 90% of you reading this

if you're decent at copywriting, sales, paid ads, whatever - don't abandon that to become an "AI expert"

instead, use AI to make you 10x better at what you already do
Read 10 tweets
Aug 27
here's everything you need to build and deploy AI apps in hours (complete beginner's guide):
most people think you need years of coding experience to build apps

but with AI tools doing the heavy lifting, you can go from idea to deployed app in a single day

the key is using the right stack and approach
here's the vibe coding stack I usually recommend for beginners:

> planning with ChatGPT/Claude
> coding with Cursor and Sonnet 4
> storing data with Supabase
> handling user logins with Clerk
> deploying with Vercel or Railway

here's how each piece works
Read 10 tweets
Aug 26
how to build an AI that understands context across an entire business:
here's the problem with most AI systems:

they can read individual documents perfectly but they have no idea how everything connects

your AI can tell you what's in Contract A or Document B

but it can't answer "which clients that have SEO services need contract renewals next month?"
this is because most traditional AI systems each document like it exists in a vacuum

it doesn't understand that

> Client X has 3 different contracts

> Contract Y expires next week

> Service Z is mentioned across 10 different agreements

it reads documents one by one instead of seeing the big picture
Read 18 tweets

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