Under the Radar

Under the Radar | October 10, 2025: AI Agents In, Prompt Engineering Out; Weekly Top 5

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Career opportunities before the crowd discovers them

Under the Radar
Top 5 AI jobs and gig paths this week

This article was written using extensive AI assistance and research. See the full methodology at the end.

Every week, I ask AI to dig into the web’s online job sites for the 5 most in-demand jobs and gigs. From that, we will bring you the Top 5 most in-demand opportunities. We will present one deep dive, replace old titles with fresh new ones if the data changes, and include at least one entry level path. Careers and jobs can change faster than people are accustomed to. This week’s golden opportunity could be next week’s lead balloon. The data is current as of October 9, 2025 and subject to change.

DISCLAIMER: The information in this article is for educational and informational purposes only. Results may vary significantly based on individual circumstances, skills, location, and market conditions. This guide does not guarantee employment, income, or success in any field. Job markets change rapidly, and salary ranges are estimates that may not reflect current or future conditions. Always conduct your own research, consult with career professionals, and verify all information before making career decisions. The author and publisher assume no liability for actions taken based on this information.

Legend: 🏛️ Government/Institutional | 🎯 Unbiased/Centrist | 💼 Business/Industry Analysis | 🔵 Progressive-Leaning | 🔴 Conservative-Leaning

Table of Contents

Top 5 Status Update

Deep Dive: Local Business AI Implementation

FAQ

Sources & Methodologies

Top 5 Status Update

Welcome to Week 2 of our series tracking emerging opportunities. The AI job market moves fast, and this week we’re already seeing major shifts.

What Dropped: Prompt Engineering

Prompt Engineering has fallen off our Top 5. Job postings are now minimal according to Indeed’s VP of AI Hannah Calhoon, and a Microsoft survey ranked it second-to-last among roles companies are considering adding in the next 12-18 months.

Why it’s declining:

  • AI models have matured to the point where precise prompt engineering is less necessary – as Jared Spataro, Microsoft’s Chief Marketing Officer of AI at Work, noted: “Two years ago, everybody said, ‘Oh, I think Prompt Engineer is going to be the hot job… [but] you don’t have to have the perfect prompt anymore”
  • The skill is being democratized and absorbed into broader roles
  • While salaries still average around $123,274 annually for existing positions, new hiring has essentially stopped

What this means: If you were considering prompt engineering, you may consider a pivot to AI Agent Builders (see below) or broader AI/ML engineering roles.

NEW #5: AI Agent Builders (Brief)

What replaced Prompt Engineering: AI Agent Builders – the professionals who design, build, and deploy autonomous AI systems that can take actions, use tools, and complete complex workflows.

Why it’s taking over:

  • 88% of executives plan to increase AI-related budgets due to agentic AI, with the market projected to grow from $7.38B in 2025 to $103.6B by 2032 at 45.3% CAGR
  • 99% of 1,000 developers surveyed are exploring or developing AI agents for enterprise
  • This is foundational infrastructure – agents are powering everything from customer service to development workflows

Quick stats:

  • Entry salary range: $34,000-$99,500 (wide range based on skills)
  • Time to first paid work: 2-4 months with focused learning
  • Location flexibility: 100% remote possible
  • Skill level: Intermediate (but entry-level with no-code platforms)

See the full deep dive on AI Agent Builders below after the Local Business AI section.

Holding Steady

The other four from Week 1 are maintaining strong positions:

#1: Micro-Community Management – Hundreds of active openings across Discord, Slack, and niche platforms. Entry-level friendly.

#2: Local Business AI Implementation – Growing demand as small businesses realize they need AI help. See full deep dive below.

#3: Digital Estate Management – Still niche but steady, embedded within estate planning practices.

#4: Synthetic Data Creation – Solid technical role, primarily W-2 positions at tech companies.

No major changes to report on these four this week.

Free Resource Guide

📚 Access the Complete Resource Library

Visit theopenrecord.org/resources for the full collection: 30-day action plans for all 5 career paths, assessment tools, and portfolio-building templates.

All completely free, no signup required.

One To Watch: Voice AI Implementation

While not yet in our Top 5, Voice AI Implementation is heating up fast and deserves your attention:

The opportunity: The conversational AI market is growing from $11.58B in 2024 to $41.39B by 2030 at 23.7% CAGR, with voice AI agents specifically growing from $2.4B to $47.5B by 2034 at 34.8% CAGR.

Why it matters: Voice is one of the most powerful unlocks for AI – it’s the most frequent and information-dense form of human communication, now made “programmable” for the first time. For enterprises, AI directly replaces human labor with technology that’s cheaper, faster, and more reliable.

Early movers advantage: 90 voice agent companies have emerged from Y Combinator since 2020, with acceleration in recent cohorts. The most common use cases are B2B customer support, healthcare (patient-facing and back office), and high-salary job coaching/training.

Skills needed: Understanding of conversational design, familiarity with voice AI platforms (like Vapi, ElevenLabs, or enterprise solutions), and industry-specific workflow knowledge.

We’ll likely feature Voice AI in our Top 5 within the next 2-3 weeks as adoption accelerates.

Deep Dive: Local Business AI Implementation

Skill Level: INTERMEDIATE | Est. Time to First Paid Work: 2-4 months

At-a-Glance Indicators

🕐 TIME COMMITMENT:     🌡️🌡️🌡️⚪⚪ (25-35 hrs/week, flexible scheduling)
📍 LOCATION:                      ◐ (Hybrid - can be remote but local presence helps)
🌍 INTERNATIONAL:           🌍 (Works globally - every market has local businesses)
🚦 MARKET ENTRY:             🟢 (Wide open, massive underserved market)
⚡ SATURATION SPEED:    ⚡⚡ (18-24 months in major metros, longer in secondary markets)
💰 STARTUP COSTS:            $$ ($500-$1,000 for tools, training, initial marketing)
🎓 CREDENTIALS:               🚫🎓 (No degree required - business acumen matters more)
📈 INCOME TIMELINE:        First $ in 2-4 months | Sustainable in 4-8 months
💵 INCOME POTENTIAL:    $50,000-$120,000/year (consulting rates: $50-$200/hour)
🎯 HIRING ODDS*:             60% (with proper positioning and 2-3 case studies)

*Hiring Odds: Estimated likelihood of securing paid work within stated timeframe, assuming baseline qualifications are met. See Methodologies for calculation details.

What It Actually Is

Local Business AI Implementation is helping small and medium-sized businesses (typically under 100 employees) integrate practical AI tools into their daily operations. You’re not building custom AI models – you’re the translator between what AI can do and what local businesses actually need.

You become the bridge between:

  • Overwhelmed business owners who know they “should” use AI
  • Powerful AI tools (ChatGPT, Claude, specialized business software)
  • Real operational problems (scheduling chaos, customer follow-up, data entry)

Typical projects include:

  • Automating appointment scheduling and confirmations
  • Setting up AI-powered customer service (chatbots, email responses)
  • Creating systems for review monitoring and response
  • Building internal knowledge bases for staff training
  • Streamlining invoice processing and basic bookkeeping
  • Generating marketing content (social posts, email campaigns)

The Reality Check

This isn’t glamorous work. You won’t be at the cutting edge of AI research. You’ll be helping a dental office respond to patient emails faster or showing a contractor how to use AI to write estimates.

What makes this work valuable:

  • These businesses are drowning in administrative tasks
  • They can’t afford a full-time tech person or big consulting firms
  • They need someone who speaks their language, not tech jargon
  • The ROI is immediate and measurable (hours saved = money saved)
  • Once they trust you, referrals flow naturally

What makes it challenging:

  • You need to understand business problems, not just AI tools
  • Clients may be skeptical or resistant to technology
  • Each industry has unique workflows you need to learn
  • You’re often working with outdated systems that don’t integrate well
  • Payment collection can be slow (Net 30-60 is common)

How To Actually Do The Work

The Business Model: Most successful local AI consultants operate as independent contractors charging either:

  • Hourly: $50-$200/hour depending on market and experience
  • Project-based: $2,000-$8,000 for initial implementation
  • Retainer: $500-$1,500/month for ongoing optimization and support

Your service stack typically includes:

  1. Discovery & Assessment (Week 1)
    • Interview business owner about pain points
    • Shadow their daily operations
    • Identify 2-3 high-impact automation opportunities
    • Create simple ROI projection
  2. Implementation (Weeks 2-4)
    • Set up AI tools (usually no-code/low-code platforms)
    • Create standard operating procedures
    • Train staff on new systems
    • Establish feedback loops
  3. Optimization & Support (Ongoing)
    • Monthly check-ins
    • Adjust automations based on usage
    • Add new capabilities as business evolves
    • Handle troubleshooting

Technical approach:

  • Start with off-the-shelf tools: ChatGPT Plus, Zapier, Make, Claude, specialized industry software
  • Use no-code automation platforms to connect systems
  • Leverage AI for content generation, but always require human review
  • Focus on workflows that save 5+ hours per week
  • Document everything so staff can maintain it

Compensation Overview

Consulting/Freelance Rates (Most Common):

  • Beginner: $50-$75/hour (first 5 clients, building portfolio)
  • Experienced: $100-$150/hour (established track record, 10+ implementations)
  • Specialized: $150-$200/hour (niche expertise in high-value industries like legal, medical)
  • Project-based: $2,000-$8,000 for full implementation (typically 20-40 hours of work)
  • Retainer arrangements: $500-$1,500/month for ongoing support (5-10 hours/month)

Agency Model (If You Scale):

  • Junior consultant: $60,000-$80,000/year salary
  • Senior consultant: $80,000-$110,000/year salary
  • Agency owner: $100,000-$200,000/year (after expenses, 2-3 years in)

Geographic Variations:

  • Major metros (SF, NYC, LA): Add 30-50% to rates
  • Mid-sized cities: Baseline rates as listed above
  • Rural/small towns: Subtract 20-30% but lower cost of living
  • International remote: Highly variable, often 30-50% lower than US rates but still competitive locally

Reality Check on Income:

  • Months 1-3: $0-$3,000 (building pipeline)
  • Months 4-6: $3,000-$8,000/month (first paying clients)
  • Months 7-12: $6,000-$15,000/month (established pipeline)
  • Year 2+: $8,000-$20,000/month (referral engine + optimization income)

The key is that one satisfied client in a business network (like a Rotary Club or Chamber of Commerce) can generate 3-5 referrals within 6 months.

See:

Resources: Learning & Tools

Foundation (Free):

Intermediate (Paid But High Value):

Tools You’ll Use:

Industry-Specific Learning:

  • Medical/Dental: 🔗 HHS HIPAA Compliance, practice management software integration
  • Legal: Client intake automation, document management systems
  • Contractors: Estimate generation, project tracking, invoice automation
  • Retail: Inventory alerts, customer loyalty automation
  • Restaurants: Reservation management, review response systems

Stay Current:

  • 🔗 Ben’s Bites Newsletter – Daily AI news for business
  • 🔗 The Rundown AI – Weekly practical AI updates
  • LinkedIn groups: “AI for Small Business”, “Business Automation Professionals”

See:

Apply Now: Where To Find The Work

Direct Outreach (Highest Success Rate):

  1. Local Business Associations:
    • Join your local Chamber of Commerce ($200-500/year)
    • Attend Rotary Club meetings (guest passes available)
    • BNI (Business Network International) chapters
    • Industry-specific associations (medical, legal, contractors)
  2. Offer Free Value First:
  3. Partnership Strategy:
    • Connect with web designers, marketing agencies, IT support companies
    • They have clients who need AI but don’t offer it
    • Offer 10-20% referral fees
    • Co-host workshops at their offices

Online Platforms:

Job Boards (For Agency Positions):

Industry-Specific Platforms:

  • Medical: Partner with practice management consultants, join MGMA (Medical Group Management Association)
  • Legal: Connect through Legal Marketing Association, law firm tech consultants
  • Construction: Procore user groups, contractor associations
  • Restaurants: Partner with POS system providers, restaurant consultants

The Strategy:

  • Start with 1-2 industries you understand (previous work experience is gold)
  • Get ONE paying client and document everything – Free Tool: Project Documentation Template (fill it in or download / print. Save locally, we do not store these. No catch.)
  • Turn that into a case study with metrics (“Saved 12 hours/week, reduced missed appointments by 40%”) – Free Tool: Case Study Builder (fill it in or download / print. Save locally, we do not store these. No catch.)
  • Use that case study to get 3-5 more clients
  • Specialize in one industry where you can become known
  • Referrals become your main source after 6-12 months

See:

Common Mistakes & What You Need To Know

Biggest Mistakes Beginners Make:

  1. Being too technical with clients
    • They probably don’t care about GPT-4 vs Claude – they care about saving time and money
    • Lead with business outcomes, not features
    • Use their language: “This will handle appointment confirmations automatically” not “This uses natural language processing to parse and respond to SMS”
  2. Over-promising AI capabilities
    • AI makes mistakes and needs human oversight
    • Always build in review steps for critical communications
    • Be honest about limitations upfront
  3. Not understanding the business first
    • You can’t solve problems you don’t understand
    • Shadow their operations for at least a full day before proposing anything
    • Ask “stupid” questions about their workflow
  4. Starting with complex implementations
    • Your first project with a client should be simple and high-impact
    • Choose something that saves them time THIS WEEK
    • Build trust before tackling major overhauls
  5. Not documenting properly
    • Create simple SOPs (Standard Operating Procedures) for everything
    • Record video walkthroughs for staff training
    • Make yourself replaceable (counterintuitively, this builds trust)

Success Factors:

  • Focus on industries where time = money (professional services, healthcare)
  • Start local – in-person credibility accelerates everything
  • Learn one business type deeply before expanding
  • Collect testimonials and metrics obsessively
  • Build ongoing relationships, not one-off projects

Red Flags – When to Walk Away:

  • Client expects AI to fully replace employees immediately
  • Business has severe operational dysfunction (fix that first)
  • Owner isn’t willing to invest time in training staff
  • Payment terms exceed Net 60

See:

  • 💼 Small Business AI Consultant Survey (2025)
  • 🎯 Implementation Best Practices Guide
  • 🔗 Free resource library for troubleshooting common issues –  Local Business AI 30-Day Action Plan

Your First 30 Days: Action Plan

Week 1: Foundation

  • Choose 2-3 industries you’ll target (ideally where you have connections)
  • Complete Google AI Essentials Certificate (8 hours)
  • Set up your tech stack: ChatGPT Plus + Zapier + project management tool
  • Create a simple website or LinkedIn profile highlighting your service

Week 2: Market Research

  • Interview 5 local business owners (offer free coffee chats)
  • Ask about their biggest time-wasters and repetitive tasks
  • Document common pain points by industry
  • Join 2-3 relevant business groups (Chamber, online communities)

Week 3: Skill Building

  • Pick ONE common problem from your interviews
  • Build a working automation that solves it (use your own “business” as practice)
  • Create a 3-5 minute video demo
  • Document the process step-by-step

Week 4: First Client Acquisition

  • Offer 3 businesses a free “AI Readiness Assessment” (30 minutes) – 🔗Free: Use our free assessment tool
  • Present one specific automation you can implement for them
  • Quote: $500-1,000 for first implementation (below market but builds portfolio)
  • Ask for testimonial and referrals in exchange for discounted rate
  • DOCUMENT EVERYTHING for your portfolio – 🔗 Free: Documentation checklist

Ongoing After Day 30:

  • Deliver on first client project with obsessive attention to quality
  • Film testimonial video with client
  • Create written case study with metrics – 🔗 Free: Case study template
  • Post results on LinkedIn
  • Ask satisfied client for 2-3 introductions
  • Increase rates slightly with each new client

See:

Deep Dive: AI Agent Builders

Skill Level: INTERMEDIATE | Est. Time to First Paid Work: 2-4 months

At-a-Glance Indicators

🕐 TIME COMMITMENT:     🌡️🌡️🌡️🌡️⚪ (35-45 hrs/week for full-time, flexible for freelance)
📍 LOCATION:                     ⭕ (100% remote possible, global opportunities)
🌍 INTERNATIONAL:           🌍 (Highly international-friendly)
🚦 MARKET ENTRY:             🟢 (Wide open, massive demand)
⚡ SATURATION SPEED:     ⚡ (3+ years - foundational technology)
💰 STARTUP COSTS:             $ ($0-$500 - most tools have free tiers)
🎓 CREDENTIALS:               🚫🎓 (No degree required, portfolio is everything)
📈 INCOME TIMELINE:        First $ in 2-4 months | Sustainable in 4-6 months
💵 INCOME POTENTIAL:     $34,000-$250,000/year (huge range based on approach)
🎯 HIRING ODDS*:              65% (with solid portfolio and no-code start)

What It Actually Is

AI Agent Builders create autonomous systems that can take actions, use tools, and complete multi-step workflows without constant human intervention. Unlike prompt engineers who craft better questions, agent builders construct systems that can do things.

Think of it this way:

  • Chatbot: Answers questions (“What’s the weather?”)
  • AI Assistant: Helps with tasks (“Draft this email for me”)
  • AI Agent: Completes workflows autonomously (“Monitor my inbox, categorize emails by urgency, draft responses to common questions, schedule meetings when someone requests one, and alert me only about high-priority items”)

What Agent Builders Actually Build:

  • Customer service agents that handle full conversations and take actions (refunds, scheduling, ticket creation)
  • Sales agents that qualify leads, schedule demos, and update CRM systems
  • Development agents that write code, run tests, and create pull requests
  • Research agents that gather information, synthesize findings, and generate reports
  • Internal automation agents that handle recurring workflows across multiple tools

The Role Breakdown:

  • No-Code Agent Builders: Use platforms like Lindy, Relevance AI, Microsoft Copilot Studio to build agents through visual interfaces (Entry-level friendly)
  • Low-Code Agent Builders: Leverage frameworks like CrewAI, LangChain with minimal coding to customize agents (Intermediate)
  • Full-Stack Agent Engineers: Build custom agentic systems from scratch using Python, LangGraph, and advanced frameworks (Advanced)

The Reality Check

This field is exploding right now, but it requires a specific mindset and skill mix.

Why it’s valuable:

  • PwC’s AI Jobs Barometer found industries exposed to AI have nearly 3x higher revenue per employee growth than less-exposed industries
  • Companies are desperate for people who can turn AI capabilities into actual working systems
  • The market is so new that you can establish expertise quickly
  • Both startups and enterprises need this skillset
  • You can start with no-code tools and level up to advanced frameworks

What makes it challenging:

  • The field evolves constantly – tools from 6 months ago may be obsolete
  • You need to understand both technical concepts AND business workflows
  • Debugging AI agents is harder than debugging regular code (non-deterministic behavior)
  • Clients often have unrealistic expectations about what agents can do
  • You’re frequently the first person in an organization doing this work (lonely but opportunity-rich)

The Skill Progression: Most people follow this path:

  1. Start with no-code platforms (Lindy, Relevance AI) to understand agent concepts
  2. Learn to connect multiple agents together for complex workflows
  3. Move to low-code frameworks (CrewAI, LangGraph) for customization
  4. Eventually dive into full coding if needed for specialized use cases

You do NOT need to be a senior engineer to start. Many successful agent builders come from product, operations, or sales backgrounds and never touch hardcore coding.

How To Actually Do The Work

The Business Models:

Option 1: Freelance Agent Builder

  • Build custom agents for businesses on project basis
  • Charge $3,000-$15,000 per agent project
  • Ongoing optimization retainers: $1,000-$3,000/month
  • Best for: People who want flexibility and diverse projects

Option 2: Agency Position

  • Join an AI consulting firm as agent specialist
  • W-2 position: $60,000-$120,000/year depending on experience
  • Benefits and stable income
  • Best for: People wanting structure and mentorship

Option 3: In-House Agent Developer

  • Work for a tech company building their agent platform
  • W-2 position: $90,000-$200,000/year (wide range by company and seniority)
  • Equity potential at startups
  • Best for: Deep technical work on one platform

Option 4: Create and Sell Agents

  • Build pre-configured agents for specific use cases
  • Sell on marketplaces or via subscription
  • Income varies wildly: $0-$10,000+/month
  • Best for: Entrepreneurs who want recurring revenue

Your Typical Project Flow:

  1. Discovery (1-2 days)
    • Understand the workflow that needs automation
    • Map out decision points and actions
    • Identify required integrations and data sources
    • Set success metrics
  2. Design (2-3 days)
    • Choose platform based on complexity and budget
    • Map agent architecture (single agent vs multi-agent)
    • Define triggers, logic, and outputs
    • Create testing scenarios
  3. Build (1-2 weeks)
    • Implement using chosen platform
    • Connect to necessary tools (CRM, email, Slack, etc.)
    • Build in error handling and edge cases
    • Create human oversight checkpoints
  4. Test & Iterate (3-5 days)
    • Run through multiple scenarios
    • Adjust based on unexpected behavior
    • Get stakeholder feedback
    • Refine prompts and logic
  5. Deploy & Monitor (Ongoing)
    • Launch to production with limited scope
    • Monitor performance daily initially
    • Expand gradually as confidence builds
    • Monthly optimization sessions

Compensation Overview

The salary range for AI Agent Builders is extremely wide because the role encompasses everything from no-code citizen developers to senior ML engineers.

Freelance/Contract Rates:

  • Beginner (No-Code Focus): $40-$75/hour (first 10 projects)
  • Experienced (Low-Code + Integrations): $100-$150/hour
  • Expert (Custom Frameworks): $150-$250/hour
  • Project-based: $3,000-$15,000 per agent implementation (typically 20-60 hours)
  • Retainer arrangements: $1,000-$3,000/month for monitoring and optimization (5-15 hours/month)

W-2 Positions:

Entry-Level (No-Code/Low-Code Focus):

  • Junior Agent Builder: $60,000-$90,000/year
  • Associate Agent Developer: $70,000-$100,000/year

Mid-Level (Framework Experience):

  • Agent Developer: $90,000-$140,000/year
  • Senior Agent Engineer: $120,000-$180,000/year

Senior-Level (Custom Systems):

  • Lead Agent Architect: $150,000-$220,000/year
  • Principal Agent Engineer: $180,000-$250,000/year

Geographic Variations:

  • San Francisco/Seattle: Top of ranges listed above
  • NYC/Boston: 80-100% of SF rates
  • Austin/Denver/Remote-first startups: 70-90% of SF rates
  • Remote positions at national companies: Often pay coastal rates regardless of location
  • International remote: Competitive locally but often 30-60% lower than US rates

Reality Check on Income Trajectory:

  • Months 1-2: $0 (learning, building portfolio)
  • Months 3-4: $2,000-$5,000 (first small projects at lower rates)
  • Months 5-8: $5,000-$12,000/month (established capability)
  • Months 9-12: $8,000-$20,000/month (specialty niche + referrals)
  • Year 2: $100,000-$150,000/year (sustainable business or mid-level W-2)

The key is to start with simpler projects and build public evidence of capability. Your third agent project should pay 2-3x what your first one did.

See:

Resources: Learning & Tools

Foundation (Free):

No-Code/Low-Code Platforms (Start Here):

  • 🔗 Lindy.ai – No-code business automation agents (Free tier available, $50/month typical)
  • 🔗 Relevance AI – Low-code multi-agent platform (Free tier, $99/month for production)
  • 🔗 Microsoft Copilot Studio – Enterprise agent builder (Pricing varies)
  • 🔗 Voiceflow – Conversation design and agent building (Free tier available)
  • 🔗 n8n – Workflow automation with AI integrations (Self-hosted free, cloud $20/month)

Intermediate Frameworks (Python Required):

  • 🔗 CrewAI – Multi-agent coordination framework ($99/month after trial)
  • 🔗 LangGraph – Build stateful multi-actor applications (Open source)
  • 🔗 AutoGen – Microsoft’s multi-agent framework (Open source)
  • 🔗 LangChain – Comprehensive LLM application framework (Open source core, paid services)

Paid Courses (High Value):

Essential Tools:

  • LLM Providers: OpenAI API ($0.02-$10/request depending on model), Anthropic Claude API (similar pricing)
  • Agent Platforms: See no-code/low-code list above
  • Development: VS Code, Python 3.10+, Git/GitHub
  • Testing: LangSmith (debugging), Helicone (monitoring), Weights & Biases (experiment tracking)
  • Deployment: Vercel, Railway, or cloud providers (AWS, GCP, Azure)

Community & Stay Current:

Practice Projects:

  1. Personal email triage agent (sorts, categorizes, drafts responses)
  2. Content research agent (gathers info on topic, synthesizes report)
  3. Code review agent (analyzes PRs, suggests improvements)
  4. Customer support agent (handles FAQs, escalates complex issues)
  5. Multi-agent system (research agent → writer agent → editor agent pipeline)

See:

Apply Now: Where To Find The Work

Freelance Platforms:

Job Boards (W-2 Positions):

Direct Application – Fast-Growing Platforms: These companies are actively hiring agent builders:

Agencies & Consultancies:

  • 🔗 Accenture AI – Search “AI Agent”
  • 🔗 Deloitte AI Practice – Enterprise implementations
  • Smaller AI consultancies: Apply directly via LinkedIn, often more flexible

Build in Public Strategy (Highly Effective):

  1. Pick a specific use case (e.g., “AI agents for e-commerce customer service”)
  2. Build 3-5 demo agents and document the process
  3. Post weekly updates on LinkedIn/Twitter with:
    • Screenshots of the agent working
    • Code snippets (if using frameworks)
    • Results/metrics (“Reduced response time from 4 hours to 15 minutes”)
    • Lessons learned
  4. Create a simple portfolio site with:
    • Live demos people can try
    • Video walkthroughs
    • GitHub repos (if open source)
  5. Clients will come to you within 2-3 months

Partnership Opportunities:

  • Marketing agencies need agents for client campaigns
  • Software development shops are adding AI capabilities
  • Business consultants need technical partners
  • Industry-specific SaaS companies want agent integrations

The Fastest Path to First Client:

  1. Join 3-5 no-code agent platforms (free tiers)
  2. Build 2-3 working agents for common business problems
  3. Document with video walkthroughs
  4. Post on LinkedIn: “I just built an AI agent that does [specific thing]. Who needs this?”
  5. Offer first 2 clients discounted rates in exchange for testimonials
  6. Use those testimonials to raise rates 50-100% for next clients

See:

Common Mistakes & What You Need To Know

Biggest Mistakes Beginners Make:

  1. Over-engineering from the start
    • Don’t build a multi-agent system when a single agent will do
    • Start with the simplest solution that works
    • You can always add complexity later
  2. Not testing edge cases
    • AI agents can fail in creative ways you didn’t anticipate
    • Test with intentionally bad/weird inputs
    • Always include error handling and fallback logic
    • Never assume the agent will work perfectly
  3. Building without clear success metrics
    • “It works” isn’t enough – how do you know?
    • Define measurable outcomes: time saved, accuracy rate, user satisfaction
    • Track these metrics from day one
    • Use data to justify ongoing optimization work
  4. Ignoring the human-in-the-loop
    • Agents shouldn’t be fully autonomous for high-stakes decisions
    • Build in approval steps for critical actions
    • Create notification systems for unusual situations
    • Give users override capabilities
  5. Not documenting the agent’s behavior
    • Future you (or your client) needs to understand what the agent does
    • Document the decision tree, prompts used, and expected behavior
    • Create troubleshooting guides
    • Make agents maintainable by others
  6. Chasing the latest framework without mastering basics
    • Frameworks change weekly, concepts are more stable
    • Master one approach before jumping to the next shiny thing
    • Deep knowledge of one tool > surface knowledge of ten tools

Success Factors:

  • Start with no-code platforms to understand agent patterns
  • Build a portfolio of diverse use cases
  • Focus on one industry/use case until you’re known for it
  • Share your work publicly (blog, videos, social media)
  • Join agent builder communities for support and opportunities
  • Keep learning – this field evolves monthly

Red Flags – Projects to Avoid:

  • Clients expecting 100% autonomous systems with no oversight
  • Projects requiring deep domain expertise you don’t have (medical diagnosis, legal advice, etc.)
  • Contracts that make you liable for agent errors
  • Unclear or constantly changing requirements
  • Payment only on “successful” completion with vague success criteria

See:

  • 💼 AI Agent Development Best Practices Guide (2025)
  • 🎯 Community Survey on Common Pitfalls
  • 🔗 Free resource: Agent debugging checklist

Your First 30 Days: Action Plan

Week 1: Foundation & First Build

  • Complete DeepLearning.AI LangGraph course (4-6 hours)
  • Sign up for 3 no-code platforms: Lindy, Relevance AI, and one other
  • Build your first agent: Simple email triage system for yourself
  • Document what works and what doesn’t

Week 2: Concept Mastery

  • Build 2 more agents using different platforms:
    • A research agent that gathers information on a topic
    • A content generation agent that creates social media posts
  • Compare the platforms – which is easiest? Most powerful?
  • Write a blog post or LinkedIn article about what you learned

Week 3: Portfolio Development

  • Choose your best agent and create a professional demo
  • Record a 3-5 minute video walkthrough
  • Build a simple portfolio website (use Carrd, Notion, or similar)
  • List your 3 agents with descriptions and videos
  • Add your tech stack and availability

Week 4: Market Entry

  • Post your portfolio on LinkedIn with the message: “I build AI agents that [solve specific problem]. Check out what I’ve built.”
  • Join 3 agent builder communities (Discord, Reddit, LinkedIn groups)
  • Reach out to 5 businesses in your network offering a free agent assessment
  • Apply to 5-10 freelance listings at competitive rates ($40-60/hour)
  • Set up profiles on Upwork and Fiverr with your portfolio

Days 31-60: First Paid Work

  • Take your first project even if rate is lower than desired
  • Over-deliver: Add extra features, provide great documentation
  • Ask for testimonial and permission to use as case study
  • Post case study on LinkedIn and portfolio
  • Raise rates 20-30% for next project
  • Keep building public projects to maintain visibility

Days 61-90: Specialization

  • By now you should have 2-3 paid projects completed
  • Identify which industry/use case is most lucrative for you
  • Build 2-3 more demo agents in that specialty
  • Position yourself as “AI Agent Builder for [Industry]”
  • Start commanding higher rates ($75-125/hour)

See:

FAQ

Q: How do I choose between these opportunities? A: Start with your current skill level and industry connections. If you have business relationships but limited tech skills, start with Micro-Community Management or Local Business AI. If you’re more technical, AI Agent Builders or Synthetic Data are better fits. Digital Estate requires legal partnerships.

Q: Can I do more than one of these at the same time? A: Yes, but focus on one initially. Local Business AI and AI Agent Builders actually complement each other – you can build agents for local businesses. Community Management and Digital Estate don’t overlap much. Get traction in one before spreading yourself thin.

Q: What if I don’t have a technical background? A: Three of the five are accessible without coding: Micro-Community Management (entry-level), Local Business AI (business acumen more important than tech), and Digital Estate Management (needs estate planning knowledge). AI Agent Builders has a no-code entry path. Only Synthetic Data requires strong technical skills.

Q: How long before I can make this my full-time income? A: Realistic timeline:

  • Months 1-3: Side hustle, inconsistent income
  • Months 4-6: Part-time replacement income ($2,000-4,000/month)
  • Months 7-12: Full-time potential ($4,000-8,000/month)
  • Year 2+: Sustainable business ($6,000-15,000/month)

Don’t quit your day job until you have 3-6 months of expenses saved AND consistent client pipeline.

Q: Do I need an LLC or business structure? A: Not immediately. You can start as a sole proprietor. Consider forming an LLC after you:

  • Hit $50,000/year in revenue
  • Want liability protection
  • Plan to hire contractors
  • Need business credibility with larger clients

See the Business Basics section in Sources & Methodologies for details.

Q: What about health insurance and benefits as a freelancer? A: Options: (1) Keep day job part-time while building, (2) Spouse’s insurance if available, (3) ACA marketplace (healthcare.gov), (4) Freelancer unions (Freelancers Union offers group plans), (5) Once profitable, budget 15-20% of revenue for insurance. This is a real cost of self-employment.

Q: How do I know if a position is oversaturated in my area? A: Check:

  • How many providers show up in Google search for “[service] near me”
  • Ask in local business groups if they’re overwhelmed with pitches
  • Test the market: If you can’t get meetings within 2 weeks of outreach, it may be saturated
  • Look at freelance platforms: If bids exceed 50 per posting, that’s high competition

If oversaturated locally, either specialize deeper or consider adjacent markets.

Q: Can I do this internationally/remotely? A: Absolutely. All five have international potential:

  • Micro-Community Management: Fully remote, time zone considerations
  • Local Business AI: Remote possible but local presence helps initially
  • Digital Estate: Remote-friendly, need local legal partnerships
  • AI Agent Builders: Highly international, language skills are asset
  • Synthetic Data: Usually W-2 but remote positions exist

Expect international freelance rates to be 30-60% of US rates but still competitive locally.

Q: What if I fail at my first choice? A: Most people try 2-3 opportunities before finding the right fit. The skills transfer:

  • Community management → Local Business AI (understanding user needs)
  • Local Business AI → AI Agent Builders (practical automation)
  • AI Agent Builders → Synthetic Data (technical foundation)

Give each opportunity 90 days of focused effort before pivoting. Document what you learned – that becomes your next portfolio.

Q: Are these opportunities recession-resistant? A: Mixed:

  • Most resilient: AI Agent Builders (companies need efficiency), Local Business AI (cost-saving focus)
  • Moderate: Micro-Community Management (depends on industry)
  • Less resilient: Digital Estate (discretionary), Synthetic Data (depends on AI investment levels)

In recessions, focus on ROI and cost-saving applications.

Q: How do I compete against people with CS degrees? A: For most of these positions, degrees matter less than:

  • Demonstrated results (portfolio, case studies)
  • Industry knowledge (understanding the business problem)
  • Communication skills (explaining value clearly)
  • Speed to market (starting before you feel “ready”)

The exception is Synthetic Data, which is more technically demanding. For the others, business results beat credentials.

The Window Is Closing (For Some)

The opportunities we’re tracking evolve at different speeds:

Moving Fast (12-18 months):

  • AI Agent Builders – Tools are rapidly improving, making it easier for non-experts
  • Local Business AI – Awareness is spreading, more consultants entering
  • Prompt Engineering (already fallen off) – Absorbed into broader roles

Still Wide Open (24-36 months):

  • Micro-Community Management – Brands still discovering the value
  • Voice AI Implementation (One To Watch) – Early adopters phase
  • Digital Estate Management – Most estate planners haven’t adapted yet
  • Synthetic Data – Technical barriers keep competition manageable

The Pattern: When mainstream business press (Forbes, WSJ, Fast Company) covers these opportunities extensively, the window is closing. Right now, we’re in the “early adopter” phase for most of these.

Your advantage is time. Starting today puts you 6-12 months ahead of the people who wait for more “proof” these work.

Sources and Methodologies

Data Sources

Top 5 Status Update:

AI Agent Builders Market Data:

Voice AI Market Data:

Local Business AI Implementation:

Platform and Tool Data:

Methodology Notes

Hiring Odds Calculation: The “Hiring Odds” percentages represent estimated likelihood of securing paid work within the stated timeframe (typically 2-4 months), assuming:

  • Baseline qualifications are met (completed relevant training)
  • Active job search (10-15 applications/outreach per week)
  • Portfolio with 2-3 demonstrated projects
  • Professional online presence (LinkedIn, portfolio site)

Calculation factors include:

  • Current job posting volume (sourced from Indeed, LinkedIn, Upwork as of October 2025)
  • Application-to-interview ratios (when available from platforms)
  • Market demand signals (growth rates, executive surveys)
  • Barrier to entry (lower barriers = higher hiring odds despite more competition)
  • Geographic factors (assumes major metro or remote-friendly role)

Limitations:

  • These are estimates based on market conditions as of October 2025
  • Individual results vary based on skills, networking, location, and effort
  • Sample sizes for newer roles (AI Agents) are smaller than established roles
  • Salary data combines W-2 and 1099 figures; we separate them where possible
  • International data is limited; US-centric bias in salary figures

Saturation Speed Projections: Based on historical analysis of similar gig cycles:

  • Social media management (2010-2012): Mainstream saturation in ~18 months
  • TikTok strategy consulting (2020-2022): Compressed to ~12 months due to faster information spread
  • NFT community management (2021-2022): Boom-bust in ~8 months (speculative bubble)

Current projections assume:

  • Normal economic conditions (no major recession)
  • Continued AI investment at current or growing levels
  • Linear rather than exponential awareness growth
  • Geographical variation (major metros saturate faster)

Business Basics: Tax & Legal Considerations

Tax Implications for Freelancers:

  • 1099 Status: Most freelance work results in 1099-NEC forms (non-employee compensation)
  • Quarterly Estimated Taxes: Required if you expect to owe $1,000+ in taxes. Pay by April 15, June 15, September 15, and January 15
  • Self-Employment Tax: Additional 15.3% (covers Social Security and Medicare) on top of income tax
  • Deductible Expenses: Home office, equipment, software subscriptions, training courses, marketing costs
  • Mileage: $0.67/mile for business travel (2025 rate)
  • Health Insurance: Deductible if self-employed and not eligible for employer coverage

LLC Formation: When to consider forming an LLC:

  • Revenue exceeds $50,000/year
  • Working with larger corporate clients who prefer LLCs
  • Want liability protection (separates personal and business assets)
  • Plan to hire contractors or employees
  • Need business credibility

Costs:

  • Formation: $50-$500 depending on state
  • Annual fees: $0-$800 depending on state
  • Registered agent: $50-300/year (or do it yourself in most states)
  • Business insurance: $300-800/year for general liability

Contract Essentials: Every freelance engagement should include:

  • Scope of work (specific deliverables)
  • Timeline and milestones
  • Payment terms (50% upfront, 50% on completion is common)
  • Revision policy (typically 2-3 rounds included)
  • Intellectual property ownership
  • Termination clause
  • Liability limitations

Recommended Resources:

Disclaimer: This is general information, not legal or tax advice. Consult with a CPA or tax attorney for your specific situation.

Additional Context

About This Series: This is a recurring series published weekly tracking emerging economy opportunities before they become oversaturated. Each week includes:

  • Status update on our tracked Top 5 opportunities
  • One detailed deep dive on a specific option
  • Research-backed salary data and market analysis
  • Actionable resources and job board links

Methodology for “Under-the-Radar” Selection: Opportunities are selected based on:

  • Growing job market demand (20%+ YoY growth in postings)
  • Currently low competition relative to demand
  • Accessible entry points (no advanced degree required for at least one pathway)
  • Demonstrated earning potential ($50,000+ annually)
  • Not yet extensively covered by mainstream business media
  • Realistic 12-36 month window before market saturation

Data Collection:

  • Job posting data collected from Indeed, LinkedIn, ZipRecruiter, Upwork, and specialized platforms
  • Salary figures from Glassdoor, ZipRecruiter, Upwork, and direct survey data when available
  • Market projections from reputable research firms (McKinsey, PwC, Gartner, Grand View Research, MarketsandMarkets)
  • Platform data from company websites, documentation, and developer communities

Update Frequency:

  • Top 5 list reviewed weekly
  • Deep dives rotate through opportunities
  • Salary data refreshed monthly
  • Dropped opportunities archived with explanation

About This Article

This article was created using AI assistance (Claude 3.5 Sonnet) for research aggregation, market analysis, and content structuring. All sources were verified, data cross-referenced across multiple providers, and conclusions drawn from established market research.

The author acknowledges the use of AI tools in creating this content and believes in transparency about AI collaboration in research and writing.

Feedback and Suggestions

Have experience in one of these? Spotted an emerging opportunity we should track? See data that needs correction?

Contact: angela@theopenrecord.org

Next Week: Deep dive on AI Agent Builders with full implementation guide + Top 5 status check.

Last Updated: October 9, 2025 Next Update: October 16, 2025

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