The latest wave of tech layoffs doesn’t have to be a step backwards—it can be a launchpad.
If you’ve spent years shipping products, debugging systems, and partnering with go-to-market teams, you already have what many founders don’t: domain insight and a network.
Pair that with AI “employees” (role-specific software agents trained on your company’s data that can perform defined tasks like drafting on-brand content, qualifying leads, and updating CRMs) and your severance becomes seed capital for a lean, scalable company.
What’s different now is that the traditional barriers to starting a business have collapsed.
The math is transformative: What once required $500,000 in annual salaries can now be achieved for less than $500 a month.
Beyond cost, there’s leverage—those complex migrations you managed, the customer insights you unearthed, the systems you architected—that’s IP AI can now operationalise at scale.
The most successful builders aren’t just venture-backed startups—they’re experienced operators who realised AI employees can handle everything from customer research to financial analysis, all trained on their specific expertise and methods.
Former Google engineers, Meta product managers, and Amazon developers are spinning up businesses with the capacity of a 10-person startup, run solo. Take Todd Krise, who launched Mercenary Marketing after two decades in agencies and now teaches others to run lean, AI-powered businesses without traditional overhead. Or Jenna Ahern of Guardian Owl Digital, who is transforming a decade-old agency into an AI-first marketing firm.
Tech professionals have a unique edge here: You understand system architecture, data flows, and automation logic, and you know what “good” looks like from UX to code quality—knowledge that becomes exponentially more valuable when deployed through AI agents working 24/7.
While I didn’t lose my job, I did choose to leave my job at TikTok when changing in‑office requirements and a fading work‑life balance told me it was time to rethink my path. I realised companies were being asked to deliver more with leaner teams, and AI was finally capable of helping. I started Parallel AI soon after with a simple goal to turn anxiety about headcount into AI tools that could help teams automate content, sales workflows, and operations without burning out.
Building is messy and setbacks happen, even now. The steps below aim to reduce risk and improve your odds.
Start with a real problem
- Write one sentence that states the outcome a buyer wants.
- Test it with 10 buyer conversations before you build. Ask: What have you tried? What did it cost? What would make this a “yes” in 30 days?
- A former marketing agency leader, Todd Krise, mapped out how artificial intelligence could replace the bloated, outdated agency model he worked in before launching Mercenary Marketing. He pressure-tested the plan with real clients and deadlines at the start of 2025 to prove that the systems, prices, and deliverables worked before he scaled.
- If you cannot find 10 people who would pay, change the outcome and try again.
What to prioritise in the first 30 to 90 days
- Aim to land two or three paid pilots and validate one repeatable way to get customers.
- Divide your runway into two or three time blocks (for example, 30, 60, and 90 days) with clear milestones.
- Sell clear outcomes you can deliver in two to six weeks. Use them to confirm the right customers, the right price, and the value you create.
- Create a simple brand: Think a clear one‑line promise, a basic landing page, and two or three proof pieces (short case example, short demonstration, testimonial). Building trust matters more than polish.
- Measurement: Pick one main goal (revenue or active pilots) to focus on, and three early signs (qualified talks each week, proposals sent, share of proposals that become sales).
- Careful spending: Cap monthly spending, and pay yourself a modest paycheck.
- Platform choice: Prefer a measurable, custom AI agent platform over many single‑purpose tools. Fewer vendors means lower cost, less setup, and a clearer view of what works.
How to land and execute your first paid pilot
Define a tight offer
- Who: one target customer with a clear problem (for example, software companies that sell to businesses but have a weak sales outreach, or agencies that need brand‑safe content in larger amounts).
- What: a named pilot (for example, “30‑Day Artificial Intelligence Sales Outreach Boost” or “Content in Context Sprint”) with three to five deliverables and success measures.
- Why now: a clear trigger (new product launch, missed sales target, hiring freeze, a backlog of content).
Use your own relationships to find your first pilot clients
- Use a short, specific outreach
- Subject or opener: “Quick pilot to achieve [outcome] in 30 days” Body (three lines): We help [customer type] achieve [outcome] without [main headache].Proposed four‑week pilot: [deliverables] → success = [measure]. Price: [$X], 50% upfront, applied to ongoing work if it delivers.Worth a 20‑minute fit call next week? If not you, who is best?
- Include one proof point, a short case example, a short demonstration clip, or a measured personal example.
- Reduce friction
- Apply the pilot fee to a monthly agreement or offer a partial refund if success measures are not met.
- Keep paperwork simple with a one‑page work plan with clear data rules and weekly cadence.
- Make onboarding quick with a startup checklist, access you will need, and a day‑one plan.
- Execute to convert
- Measure everything! Record starting levels, send weekly updates with a simple measures checklist, and deliver early quick wins.
- At your mid‑point review show progress, confirm success measures, and discuss the follow‑on now.
- During the final week, present a short results deck and a one‑page decision plan with a yes or no choice and a start date for the monthly agreement.
This is the moment to turn your experience into a scalable business with artificial intelligence on your terms.
ABOUT THE AUTHOR
David Richards is the founder of Parallel AI, a platform that builds custom, context-aware AI employees that can automate content, sales, and workflows—helping teams scale securely and efficiently. He writes about practical AI adoption and the future of work.
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