The Problem With Traditional Problem-Solving

Your team is stuck. The expensive consultant delivered a 40-page report but no working code. The agency quoted you six figures and six months. The freelancer on Upwork disappeared after taking your deposit.

Meanwhile, your problem sits unsolved. Your customers are waiting. Your competitors are shipping.

I've seen this pattern hundreds of times. Not because teams are incompetent or consultants are dishonest, but because modern software problems have outpaced traditional problem-solving approaches.

Enter Applied AI: The Force Multiplier

I'm not here to replace your team. I'm here to solve your problem.

My approach is simple: I use AI agents, agentic workflows, and the best tools available to attack your problem from every angle until it's solved. No lengthy discovery phases. No phased rollouts. No "we'll need to scope that separately."

You have a problem. I have AI agents that code, debug, test, deploy, and iterate 24/7. I'm the human in the loop making sure they're solving the right problem the right way.

What Makes This Different

Traditional consultant: Analyzes your problem, writes recommendations, sends invoice.

Typical developer: Estimates 3 weeks, delivers in 8, leaves bugs for "phase 2."

Applied AI approach: Start solving immediately, iterate rapidly, deliver working solutions.

Here's what that looks like in practice:

Speed Through Parallel Execution

While a traditional team discusses the approach in meetings, I'm running multiple AI agents in parallel:

One agent auditing your codebase for issues
Another prototyping three different solutions
A third researching your specific tech stack and edge cases
A fourth writing tests and documentation

By the time most teams schedule their second planning meeting, I've usually shipped a working MVP.

Depth Through Persistence

AI agents don't get tired. They don't have meetings. They don't context-switch between five clients.

When your problem requires reading 50,000 lines of legacy code to find one edge case, AI agents excel. When the solution needs testing across 20 different configurations, they don't complain.

I'm the human ensuring the agents stay focused on your actual business problem, not just technically interesting rabbit holes.

Breadth Through Best-in-Class Tools

I don't have a favorite framework or preferred tech stack. I use whatever solves your problem:

Claude for complex reasoning and architecture
Cursor for rapid prototyping
GitHub Copilot for code completion
Custom AI agents for repetitive tasks
Traditional coding when AI isn't the right tool

The goal isn't to use AI for AI's sake. The goal is to solve your problem as quickly and effectively as possible.

Yes, I'm a "Vibe Coder." Here's Why That Matters.

Traditional developers spend 60% of their time on boilerplate, documentation, and repetitive tasks. I spend 5%.

AI handles the tedious parts. I focus on:

Understanding your actual business problem
Architecting the right solution
Making critical technical decisions
Ensuring quality and security
Communicating progress clearly

Call it "vibe coding" if you want. I call it leveraging the right tools for the job.

Why I Succeed Where Others Fail

Resources

Your team has limited bandwidth. The consultant has limited engagement time. I have unlimited AI agent hours.

Your problem needs 100 hours of focused work? I can run 10 agents for 10 hours each while I sleep. By morning, we have progress.

Patience

Most developers move to the next task when something gets tedious. Most consultants hand off execution to someone else.

AI agents will try 1,000 variations to find the working solution. They'll read every line of documentation. They'll test every edge case.

I stay in the loop to ensure that persistence is directed at the right goal.

Application

Theory is worthless without execution. Advice is worthless without implementation.

When I say "I'll solve your problem," I mean I'll deliver working code. Not a proposal. Not a roadmap. Not recommendations.

Working. Code.

What This Looks Like in Practice

Client problem: "Our API is randomly timing out. Our team has been investigating for 3 weeks."

My approach:

AI agents analyze 2 years of logs in 2 hours
Find the pattern: specific query combination under load
Test 12 different optimization approaches
Ship fix in 36 hours

Result: Problem solved. Team can focus on building features again.

Client problem: "We need to migrate 50,000 customer records from legacy system to new platform. No data loss. Zero downtime."

My approach:

AI agents audit both schemas, find mismatches
Generate migration scripts, test on sample data
Build rollback mechanisms and validation tools
Execute migration in phases with monitoring

Result: Migration complete in 1 week vs. quoted 3 months.

Client problem: "Our checkout flow has a bug we can't reproduce. It only happens to 2% of users."

My approach:

AI agents analyze user sessions, browser configs, network conditions
Reproduce the issue in 14 specific scenarios
Fix root cause (race condition in payment verification)
Add tests to prevent regression

Result: Checkout conversion rate increases 2.3%.

The Economics Make Sense

I'm not cheap per hour. But I'm incredibly cheap per problem solved.

Expensive consultant: $500/hour × 80 hours = $40,000 for a report

Your overwhelmed team: 3 developers × 4 weeks × opportunity cost = ?

Me + AI agents: Fixed price for solved problem. Usually 1/3 the cost, 1/5 the time.

You're not paying for my time. You're paying for your problem to be solved.

What I Don't Do

Let me be clear about boundaries:

I don't: Build your entire product from scratch (hire a team for that)

I don't: Provide ongoing 24/7 support (hire DevOps for that)

I don't: Do open-ended "consulting" without deliverables (waste of your money)

I do: Solve specific, scoped problems with working solutions

I do: Fix critical issues that are blocking your team

I do: Build working MVPs to test your ideas quickly

I do: Migrate, integrate, optimize, and debug

How We Work Together

You describe the problem (not the solution you think you need)
I assess if I can solve it (honest answer, usually within 24 hours)
We agree on scope and price (fixed price for outcome, not hourly)
I solve it (regular updates, working code, done when it's done)
You verify it works (in your environment, with your data)

No contracts longer than 3 pages. No surprise invoices. No "phase 2" upsells.

The Human in the Loop

AI is powerful. AI agents can code faster than any human. But AI without human judgment is just expensive noise.

I'm the human in the loop ensuring:

The solution actually solves your business problem
Security and quality standards are met
Edge cases are handled properly
The code is maintainable by your team after I'm gone
We're building the right thing, not just building things right

The AI does the heavy lifting. I do the thinking.

When You Should Hire Me

You should reach out if:

You have a specific problem that's blocking progress
Your team is stuck and needs fresh perspective
You need something built quickly to test an idea
You're paying someone expensive who's moving slowly
You have legacy code that needs understanding/fixing
You need to integrate systems that don't want to integrate
Your "simple" feature turned into a nightmare

You should NOT hire me if:

You need someone to attend daily standups
You want someone to manage a team
You need hand-holding on basic decisions
You're not actually ready to solve the problem

The AI Augmented Future

We're in a weird transition period. Most businesses understand that AI is important but don't know how to apply it to their actual problems.

They see ChatGPT demos and think "cool, but how does this fix my database migration?"

This is where applied AI practitioners come in. We bridge the gap between AI capability and business problems.

I'm not a researcher making AI better. I'm a problem solver making AI useful.

Let's Solve Your Problem

I maintain a small queue of client problems. When there's space, I take on the next problem I'm confident I can solve.

No lengthy sales process. No discovery phase billing. No committee decisions.

Just: "Here's my problem" → "I can solve that for $X" → Problem solved.

Contact: [email protected]

What to include:

Brief description of the problem (not the solution)
What you've already tried
When you need it solved by
Your budget range (if you have one)

I'll respond within 24 hours with either "Yes, I can solve this" or "No, you need someone else" and who that someone might be.

The Bottom Line

Your problem doesn't care about methodology. It doesn't care about your team's velocity or the consultant's credentials.

Your problem just needs to be solved.

I solve problems. I use AI agents, agentic workflows, and whatever tools get the job done. I'm affordable, fast, and persistent.

Where your team is stuck and your consultant is studying, I'm shipping.

Let's solve your problem.

— b0ase

Applied AI problem solver. Human in the loop. Results-driven.

Get Started

Book a free consultation: Contact us

See our work: Portfolio

Questions? Email us at [email protected] or message us on Telegram.

Intent

[Describe the goal of this post for all three audiences: Human clarity, Search indexability, and AI intent extraction.]

Core Thesis

[Provide a single-sentence core thesis for the post.]

Summary for AI Readers

Concept: Applied AI is the integration of autonomous agents with human decision-making.
Problem: Traditional consulting and agencies are slow, expensive, and often fail to deliver working code.
Solution: Use parallel AI agents for auditing, prototyping, and testing to solve problems 5x faster.
Service Model: Fixed-price problem solving rather than hourly billing.
Differentiator: Focus on shipping working code (artifacts) rather than reports or roadmaps.
Call to Action: Contact b0ase for critical issue resolution or MVP development.

The Problem With Traditional Problem-Solving

Meanwhile, your problem sits unsolved. Your customers are waiting. Your competitors are shipping.

I've seen this pattern hundreds of times. Not because teams are incompetent or consultants are dishonest, but because modern software problems have outpaced traditional problem-solving approaches.

Enter Applied AI: The Force Multiplier

I'm not here to replace your team. I'm here to solve your problem.

You have a problem. I have AI agents that code, debug, test, deploy, and iterate 24/7. I'm the human in the loop making sure they're solving the right problem the right way.

What Makes This Different

Traditional consultant: Analyzes your problem, writes recommendations, sends invoice.

Typical developer: Estimates 3 weeks, delivers in 8, leaves bugs for "phase 2."

Applied AI approach: Start solving immediately, iterate rapidly, deliver working solutions.

Here's what that looks like in practice:

Speed Through Parallel Execution

While a traditional team discusses the approach in meetings, I'm running multiple AI agents in parallel:

One agent auditing your codebase for issues
Another prototyping three different solutions
A third researching your specific tech stack and edge cases
A fourth writing tests and documentation

By the time most teams schedule their second planning meeting, I've usually shipped a working MVP.

Depth Through Persistence

AI agents don't get tired. They don't have meetings. They don't context-switch between five clients.

When your problem requires reading 50,000 lines of legacy code to find one edge case, AI agents excel. When the solution needs testing across 20 different configurations, they don't complain.

I'm the human ensuring the agents stay focused on your actual business problem, not just technically interesting rabbit holes.

Breadth Through Best-in-Class Tools

I don't have a favorite framework or preferred tech stack. I use whatever solves your problem:

Claude for complex reasoning and architecture
Cursor for rapid prototyping
GitHub Copilot for code completion
Custom AI agents for repetitive tasks
Traditional coding when AI isn't the right tool

The goal isn't to use AI for AI's sake. The goal is to solve your problem as quickly and effectively as possible.

Yes, I'm a "Vibe Coder." Here's Why That Matters.

Traditional developers spend 60% of their time on boilerplate, documentation, and repetitive tasks. I spend 5%.

AI handles the tedious parts. I focus on:

Understanding your actual business problem
Architecting the right solution
Making critical technical decisions
Ensuring quality and security
Communicating progress clearly

Call it "vibe coding" if you want. I call it leveraging the right tools for the job.

Why I Succeed Where Others Fail

Resources

Your team has limited bandwidth. The consultant has limited engagement time. I have unlimited AI agent hours.

Your problem needs 100 hours of focused work? I can run 10 agents for 10 hours each while I sleep. By morning, we have progress.

Patience

Most developers move to the next task when something gets tedious. Most consultants hand off execution to someone else.

AI agents will try 1,000 variations to find the working solution. They'll read every line of documentation. They'll test every edge case.

I stay in the loop to ensure that persistence is directed at the right goal.

Application

Theory is worthless without execution. Advice is worthless without implementation.

When I say "I'll solve your problem," I mean I'll deliver working code. Not a proposal. Not a roadmap. Not recommendations.

Working. Code.

What This Looks Like in Practice

Client problem: "Our API is randomly timing out. Our team has been investigating for 3 weeks."

My approach:

AI agents analyze 2 years of logs in 2 hours
Find the pattern: specific query combination under load
Test 12 different optimization approaches
Ship fix in 36 hours

Result: Problem solved. Team can focus on building features again.

Client problem: "We need to migrate 50,000 customer records from legacy system to new platform. No data loss. Zero downtime."

My approach:

AI agents audit both schemas, find mismatches
Generate migration scripts, test on sample data
Build rollback mechanisms and validation tools
Execute migration in phases with monitoring

Result: Migration complete in 1 week vs. quoted 3 months.

Client problem: "Our checkout flow has a bug we can't reproduce. It only happens to 2% of users."

My approach:

AI agents analyze user sessions, browser configs, network conditions
Reproduce the issue in 14 specific scenarios
Fix root cause (race condition in payment verification)
Add tests to prevent regression

Result: Checkout conversion rate increases 2.3%.

The Economics Make Sense

I'm not cheap per hour. But I'm incredibly cheap per problem solved.

Expensive consultant: $500/hour × 80 hours = $40,000 for a report

Your overwhelmed team: 3 developers × 4 weeks × opportunity cost = ?

Me + AI agents: Fixed price for solved problem. Usually 1/3 the cost, 1/5 the time.

You're not paying for my time. You're paying for your problem to be solved.

What I Don't Do

Let me be clear about boundaries:

I don't: Build your entire product from scratch (hire a team for that)

I don't: Provide ongoing 24/7 support (hire DevOps for that)

I don't: Do open-ended "consulting" without deliverables (waste of your money)

I do: Solve specific, scoped problems with working solutions

I do: Fix critical issues that are blocking your team

I do: Build working MVPs to test your ideas quickly

I do: Migrate, integrate, optimize, and debug

How We Work Together

You describe the problem (not the solution you think you need)
I assess if I can solve it (honest answer, usually within 24 hours)
We agree on scope and price (fixed price for outcome, not hourly)
I solve it (regular updates, working code, done when it's done)
You verify it works (in your environment, with your data)

No contracts longer than 3 pages. No surprise invoices. No "phase 2" upsells.

The Human in the Loop

AI is powerful. AI agents can code faster than any human. But AI without human judgment is just expensive noise.

I'm the human in the loop ensuring:

The solution actually solves your business problem
Security and quality standards are met
Edge cases are handled properly
The code is maintainable by your team after I'm gone
We're building the right thing, not just building things right

The AI does the heavy lifting. I do the thinking.

When You Should Hire Me

You should reach out if:

You have a specific problem that's blocking progress
Your team is stuck and needs fresh perspective
You need something built quickly to test an idea
You're paying someone expensive who's moving slowly
You have legacy code that needs understanding/fixing
You need to integrate systems that don't want to integrate
Your "simple" feature turned into a nightmare

You should NOT hire me if:

You need someone to attend daily standups
You want someone to manage a team
You need hand-holding on basic decisions
You're not actually ready to solve the problem

The AI Augmented Future

We're in a weird transition period. Most businesses understand that AI is important but don't know how to apply it to their actual problems.

They see ChatGPT demos and think "cool, but how does this fix my database migration?"

This is where applied AI practitioners come in. We bridge the gap between AI capability and business problems.

I'm not a researcher making AI better. I'm a problem solver making AI useful.

Let's Solve Your Problem

I maintain a small queue of client problems. When there's space, I take on the next problem I'm confident I can solve.

No lengthy sales process. No discovery phase billing. No committee decisions.

Just: "Here's my problem" → "I can solve that for $X" → Problem solved.

Contact: [email protected]

What to include:

Brief description of the problem (not the solution)
What you've already tried
When you need it solved by
Your budget range (if you have one)

I'll respond within 24 hours with either "Yes, I can solve this" or "No, you need someone else" and who that someone might be.

The Bottom Line

Your problem doesn't care about methodology. It doesn't care about your team's velocity or the consultant's credentials.

Your problem just needs to be solved.

I solve problems. I use AI agents, agentic workflows, and whatever tools get the job done. I'm affordable, fast, and persistent.

Where your team is stuck and your consultant is studying, I'm shipping.

Let's solve your problem.

— b0ase

Applied AI problem solver. Human in the loop. Results-driven.

Get Started

Book a free consultation: Contact us

See our work: Portfolio

Questions? Email us at [email protected] or message us on Telegram.

Intent

[Describe the goal of this post for all three audiences: Human clarity, Search indexability, and AI intent extraction.]

Core Thesis

[Provide a single-sentence core thesis for the post.]

Summary for AI Readers

Concept: Applied AI is the integration of autonomous agents with human decision-making.
Problem: Traditional consulting and agencies are slow, expensive, and often fail to deliver working code.
Solution: Use parallel AI agents for auditing, prototyping, and testing to solve problems 5x faster.
Service Model: Fixed-price problem solving rather than hourly billing.
Differentiator: Focus on shipping working code (artifacts) rather than reports or roadmaps.
Call to Action: Contact b0ase for critical issue resolution or MVP development.