Jaspreet Singh - Ai

Building 10x With AI.
AI Automation | AI Agents

[Jaspreet Singh - Ai @jaspreet2727]

That voice in my brain, which is always negotiating with me.
Is the temptation.

Allowing it to always distract me. Is how I loose control over my mind.

And develop an habit of taking a step back and analysing before I act, gives me control over it.

And clarity over time.

[Jaspreet Singh - Ai @jaspreet2727]

Be specific of what you want.

This world rewards clarity.

[Jaspreet Singh - Ai @jaspreet2727]

Your attention is a container, if u cannot keep it empty.
There will be no space for the right things to put in whenever u want to.

And also the fact you didn’t tried to make it clean, it will always automatically get filled by the random things.

And you loose control over it.

[Jaspreet Singh - Ai @jaspreet2727]

Being one with who you are is the game.
The moment you show two personalities to yourself you loose.

You cannot lie to yourself even if you want to, the truth that you’re always know the reality of you inside.

[Jaspreet Singh - Ai @jaspreet2727]

Mediation is just observing clear mind, allowing thoughts to pass by without any interference or judgement.
And getting back to your natural state - present state if it is dragging.

Absolute presence is your native state.
This practice gives u a switch, you can turn on or off.

[Akshay 🚀 @akshay_pachaar]

the four types of agent loops.

loop engineering keeps getting talked about as one thing. it's actually a choice between four structures, and each one fits a different kind of task.

it means designing the system that steers the agent, instead of steering it yourself move by move.

that system always answers two questions. what starts a run, and what decides the work is done.

in a hand-run session you answer both yourself, every single time. each loop type moves more of that into the system.

here's each type, what triggers it, and when to reach for it.

1) turn-based.

triggered by a user prompt. the agent gathers context, acts, and checks its work inside a single turn, then a human reviews the output and writes the next prompt.

use this when requirements are still forming and every output changes what you'd ask for next.

2) goal-based.

triggered by a /goal command carrying success criteria and a budget, like "get the homepage Lighthouse score to 90, stop after 5 tries." when the agent tries to stop, an evaluator model checks whether the goal is met, and a no sends it back to work.

use this when the outcome is measurable but the path there isn't worth your attention.

3) time-based.

triggered by a clock. an interval fires, the agent runs a fixed prompt like "check the PR, fix CI," then waits for the next tick. /loop runs on your machine, /schedule moves it to the cloud so it survives a closed laptop.

use this for recurring work where the task is known in advance and only the timing repeats.

4) proactive.

triggered by an event or schedule with no human present. a routine watches a channel, and when something needs handling it spawns a workflow with a triage agent, a fix agent, and a reviewer that adversarially judges the work before the task closes.

use this for standing responsibilities where you can't predict what will come in, only that something will.

each type hands off one more job than the last. turn-based keeps both with the human, goal-based automates the checking, time-based automates the trigger, and proactive automates both while deciding the workflow shape at runtime.

so the mapping question isn't which loop is most advanced. it's whether your task is exploratory, measurable, recurring, or standing.

the more you hand off, the less you babysit.

I wrote the full breakdown on loop engineering. the article is quoted below.

[Jaspreet Singh - Ai @jaspreet2727]

I made a "7-Day AI Build Challenge" checklist.

Day-by-day micro-actions. From zero to your first AI build shipped.

Reply "CHALLENGE" and I'll DM it.

This is Week 1. Follow for weekly build recaps.

What would YOU build with AI in 7 days?

[Jaspreet Singh - Ai @jaspreet2727]

I built something with AI every day this week.

7 days. 7 builds. ~5 hours total.

The same thinking framework worked for ALL of them.

Full breakdown: 🧵

[Jaspreet Singh - Ai @jaspreet2727]

The pattern:

Every single build used Claude Code:
1. DIRECTIVE
2. ORCHESTRATION
3. EXECUTION

Not a single build required:
❌ Prompt engineering
❌ A CS degree
❌ A special tool

All required: THINKING differently.

[Jaspreet Singh - Ai @jaspreet2727]

RT @AlexHormozi: We desperately want to learn someone’s true intentions (their desired outcome) because it helps us predict their behavior.…

[Jaspreet Singh - Ai @jaspreet2727]

Reply "SKILLS" and I'll DM you a PDF breaking down each skill in more detail.

Including: what to charge, where to find clients, and real examples.

Follow for daily AI breakdowns.

Tomorrow: The AI job replacement fear — and why it's both real AND an opportunity.

[Jaspreet Singh - Ai @jaspreet2727]

5 AI skills that are paying real people real money right now.

Not "someday."
Not "in theory."
Actually paying. This month. In 2026.

Here's what they are and how to start: 🧵

[Jaspreet Singh - Ai @jaspreet2727]

My prediction for end of 2026:

People who learned to THINK with AI → earning $2K-$20K/month
People who learned AI TOOLS → still watching tutorials

The difference isn't talent.
It's whether you build or just learn.