Tech Talent Acquisition

This is the most underrated way to use Claude: (and it has nothing to do with writing or coding) It's competitive intelligence. Using data that's free, public, and updated every single week. Here's my extract step by step guide: Step 1. Go to claude .ai. Step 2. Select the new Claude "Opus 4.6." Step 3. Turn on "Extended Thinking." Step 4. Pick a competitor. Go to their careers page. Step 5. Copy every open job listing into one doc. (Title. Team name. Location. Full description) Step 6. Save it as one .txt or .docx file. Step 7. Search the company at EDGAR (sec .gov) Step 8. Download its recent 10-K or 10-Q filing. (Official strategy, risks, and financials - all public.) Step 9. Upload both files to Claude Opus 4.6. Step 10. Paste this exact prompt: "You are a competitive intelligence analyst at a rival company. I've uploaded [Company]'s complete current job listings and their most recent SEC filing. Perform a strategic intelligence analysis: → Cluster these roles by what they suggest is being built. Don't use the team names they've listed. Infer the actual product initiatives from the skills, tools, and responsibilities described. → Identify capabilities or teams that appear entirely new — not mentioned anywhere in the SEC filing. These are unreleased bets. → Find roles where seniority is disproportionately high for a new team. This signals executive-level priority. → Cross-reference the SEC filing's Risk Factors and Strategy sections with hiring patterns. Where are they investing against a stated risk? Where did they flag a risk but have zero hiring to address it? → Predict 3 product launches or strategic moves this company will make in the next 6-12 months. State your confidence level and cite specific job titles and filing sections as evidence. Format this as a 1-page competitive intelligence briefing for a CMO." What you'll find: → Products that don't exist yet but will in 6 months. → Priorities that contradict what the CEO said. → Risks they told the SEC but aren't addressing. This is what consulting firms charge $200K for. It took me 10 minutes. I used the new Claude 'Opus 4.6' for a reason: ✦ It read 60 job listing & a 200-page filing together.  ✦ And connects dots across both. ✦ It is superior in thinking and context retrieval. That's why I didn't use ChatGPT for this.

When I was recruiting at a startup, I didn’t have LinkedIn Recruiter or fancy sourcing tools. So I got creative and turned to Google. There’s a trick called X-ray search that recruiters use to find talent. But job seekers can flip it to find roles that aren’t showing up on LinkedIn or job boards. It works because you’re searching company job boards directly specifically sites hosted by Greenhouse, Lever and Ashby which are the three most common platforms used by startups, tech companies and design forward teams to post jobs. Here’s how it works: Say you’re a Product Designer looking for remote roles. Pop this into Google: site:jobs.lever.co OR site:jobs.greenhouse.io OR site:ashbyhq.com "product designer" AND "remote" You’ll get real-time openings, straight from company career pages. Looking for something location-based and you’re a Social Media Manager in LA, use this: site:jobs.greenhouse.io OR site:jobs.lever.co "social media manager" AND "Los Angeles" You can plug in any title, industry or location that matters to you like “brand designer,” “UX internship,” or “marketing. coordinator” This is how I found amazing candidates when I had zero tools. Now I’m sharing it with you because the best jobs aren’t always on the front page. Try it and let me know what you find!

Most HR leaders would hate me for saying this, but 90% of hiring metrics are useless. You don't need a dashboard with 47 KPIs. Here’s 7 numbers that actually predict whether your hiring is working: 1. Quality Applications Track how many candidates meet minimum qualifications versus total applicants. If you're getting 200 applications but only 10 are qualified, your job postings or employer brand need work. Quality beats quantity every time. 2. Time to Fill Days from requisition to accepted offer. Every day a role stays open costs productivity and team morale. Track by role type to identify bottlenecks…is sourcing slow? Interview scheduling? Decision-making? 3. Interview-to-Offer Ratio What percentage of interviewed candidates receive offers? If you're interviewing 20 people to make one offer, your screening process is broken. This reveals whether your pre-interview assessments actually work. 4. Offer Acceptance Rate What percentage of your offers get accepted? Low acceptance rates signal problems with compensation, candidate experience, or employer brand. Track by seniority level to see where you're losing top talent. 5. 90-Day Retention What percentage of new hires are still engaged and performing after 90 days? Early turnover is expensive and usually preventable. This metric reveals misalignment between expectations and reality. 6. Hiring Manager Satisfaction How do managers rate the candidates you deliver and the hiring process? Your internal customers' satisfaction predicts whether hiring best practices will stick. Low scores mean misaligned expectations. 7. Cost Per Hire All-in recruiting costs divided by hires made. Include recruiter time, tools, assessments, and external fees. Understanding true cost-per-hire enables better resource allocation and ROI discussions. TAKEAWAY: Most hiring teams measure activity instead of outcomes. These 7 metrics focus on quality, efficiency, and long-term success. Track what matters, improve what you measure.

The reality of hiring right now looks a bit contradictory. Many roles get hundreds, sometimes thousands, of applications. Then, at the same time, there are still pockets of talent that feel almost impossible to reach. Everyone we speak to complains that the vast majority of these applications aren’t relevant, and that they can't reach talent groups like skilled tech talent, senior leadership, and often diverse talent. But it varies from company to company. So you end up with two contradictory things happening at once. This is a distribution issue. We aren’t approaching hiring in a way that will solve this problem. Most platforms are still built to maximise volume and applications, and people measure success on applications because that’s what worked in a less complicated hiring context. But if anything, that makes the problem worse. We can't solve too many applications with more applications. We need fewer, better ones. And we need to reach people who aren’t actively searching or considering us in the first place. Because relying on job adverts means relying on timing: right place, right moment, right wording, right information. Miss it, and the right people never see you. Hit it, and you’re filtering through hundreds of people who were never going to be a fit anyway because they don’t know enough about you and you don’t know enough about them. The companies that are getting closer to solving this are doing something slightly different. They’re getting much clearer on who they’re actually trying to attract, what those people care about, and how that talent makes decisions about their next employer. When you start working with demand data instead of just reacting to it, the funnel changes surprisingly quickly. Lower volumes, more relevance, and overall a much nicer experience for candidates and companies. The talent isn’t missing - we’re just in a blind game of musical chairs - and we can solve both problems by looking more at putting the wrong people off and attracting the right people rather than focusing purely on applications. I'd love to talk more about this, so if this resonates, drop me a comment or a DM and I can share some more data on what we're seeing. Or tag someone you think might find this interesting!

The best candidate experience I’ve ever had when applying for opportunities didn’t make me feel like just another number It made me feel like a human being with potential, value, and a story. I’ve been through hiring processes that felt transactional, rushed, or impersonal. But I’ve also experienced ones where I felt seen, respected, supported, and genuinely excited about the possibility of joining. And that experience changed everything. Here’s what made the best one stand out: - The team clearly reviewed my background and asked meaningful, personalized questions - Expectations, timelines, and next steps were transparent, no guessing or chasing updates - From tone to timing, every interaction showed empathy, respect, and appreciation for my time - They weren’t just testing skills; they wanted to understand my ideas, career goals, and long-term interests - They didn’t just pitch the role, they shared what the mission meant to them and why the work mattered As a reminder, as much as you’re being evaluated, you’re evaluating, too. Pay close attention to every step of the process and leverage that to make an informed decision. Here’s to better, more human candidate experiences in the future, ones that leave people feeling respected, hopeful, and inspired, regardless of the outcome. #StephSynergy

Most hiring advice focuses on résumés and technical skills — and completely miss the point. The real way to identify top talent? Pay attention to how they think, communicate, and challenge ideas. When I was building proprietary tools for my business, I interviewed three candidates. First candidate: From the start, something felt off. His camera was blurry, his responses were vague, and he struggled to articulate his ideas. When I asked how he would approach a specific problem, he paused, mumbled a few disconnected thoughts, and quickly pivoted to something unrelated. It felt like he was grasping for the right answer instead of actually thinking through the question. Second candidate: He was polished and professional. He had a structured way of gathering information and asked all the expected questions—“What features do you need?” “What’s your timeline?” “What are the specifications?” It was a solid conversation, but something was missing. His focus was on execution, not impact. He never asked why I needed these features or how they fit into the bigger picture. Third Candidate: From the start, the conversation felt different. He listened carefully, then asked, “What’s the real problem you’re trying to solve?” Instead of diving straight into execution, he wanted to understand the users—who they were, what challenges they faced, and how the tool would address those challenges. When I explained one of my ideas, he paused and said, “That could work, but have you thought about doing it this way instead? It might be more efficient.” That’s when it clicked. The first candidate was lost. The second candidate could execute. But the third? He thought like an owner. He didn’t just follow instructions—he improved them. Some candidates focus on getting the job done. Others push for clarity, challenge inefficiencies, and think ahead. Those are the ones who truly make a difference. If you want to spot top talent, don’t just look for skills. Look for the ones who ask the right questions.

If your job application process has a higher drop-off rate than your website funnel… it’s time for a shift! I’ve reviewed hundreds of job posts lately, and most don’t need a rewrite, They need a mindset shift! We’ve nailed digital marketing funnels everywhere.... clear CTAs, A/B testing landing pages, removing unnecessary steps in e-commerce orders.... But when it comes to recruitment, many companies still expect top talent to: ⚠️ Rewrite their experience manually! ⚠️Answer 20 “motivational” and "technical" questions! ⚠️Spend 45 minutes applying, just to get ghosted?! Let’s be honest, the best candidates aren’t lazy They’re tired! Tired of repetitive, outdated hiring journeys that ignore everything we’ve learned in UX and marketing. And the irony is that companies say they “can’t find the right people” But they haven’t even talked to them!!! because the ATS filtered them out first. We’ve optimized for automation, not human connection. The truth is If you really want great applicants, treat them like valuable users: ✔️A/B test your job descriptions, are they clear or just corporate soup? ✔️Track drop-offs, where do people give up? ✔️Cut the noise, move non-critical questions to interviews ✔️Fix your autofills, and don’t make them fill out their resume after uploading it!! 🚨And most importantly: put real humans back in the hiring loop. You didn’t fail to attract great talent, You just buried them under 12 dropdown menus and 9 mandatory fields. ❓️What’s the most frustrating part of job applications today? #RecruitmentMarketing #DigitalMarketing #ATS #ABTesting #hiring

Candidates should be genuinely concerned about how companies use AI-powered Applicant Tracking Systems (ATS) and sourcing tools. TA Tech companies also have a real opportunity to continue to improve and differentiate. Here's why ↴ 1. Fairness and Bias → Concern: AI systems may perpetuate or even amplify biases if the training data is not diverse or if the algorithms are not rigorously tested. → Candidate Worry: Will the AI unfairly disqualify me based on factors like my name, background, or employment history? 2. Transparency → Concern: Candidates often don’t know how AI evaluates their resumes or application responses. → Candidate Worry: How are decisions being made, and what criteria are used? If I’m rejected, will I even know why? 3. Loss of Human Touch → Concern: Over-reliance on AI may result in less personal interaction during the hiring process, which requires empathy and context. → Candidate Worry: Am I being overlooked because a machine doesn’t see my unique skills or context that a human recruiter might appreciate? 4. Accuracy of Matching → Concern: AI might prioritize keyword matching over context or nuance in a candidate’s experience. → Candidate Worry: Will the system recognize my transferable skills, or is it just searching for buzzwords? 5. Data Privacy → Concern: AI tools often process large amounts of candidate data, raising privacy and security issues. → Candidate Worry: How is my personal information being stored, shared, or used? 6. Over-automation → Concern: If AI is used too heavily in sourcing and screening, good candidates may slip through the cracks. → Candidate Worry: Am I being filtered out by rigid algorithms before anyone even looks at my application? 7. Algorithmic Accountability → Concern: Candidates want assurance that AI errors can be identified and corrected. → Candidate Worry: If the AI makes a mistake about my application, who’s accountable, and can it be reversed? How would I even know? How Companies and Vendors Can Address These Concerns ↴ →Self-audit their AI tools regularly for bias and fairness. → Provide transparency by clearly communicating how AI impacts the hiring process. → Use AI to assist, not replace, human decision-making. → Ensure data privacy through compliance with laws like GDPR or CCPA. 👆 These efforts can help build trust with candidates while ensuring that AI remains a tool to enhance, not diminish, the recruitment process. ✅ Candidates: Did I miss anything? ✅Companies: There is a massive opportunity to listen to job seekers and internal TA teams in the trenches as you develop the next phase of AI-powered TA tools. Exciting times, people! And I am here for all of it!

First Impressions Matter... Especially for Candidates! The employee experience begins the moment a candidate interacts with your business. The first interview isn’t just an interview, it’s the start of their onboarding journey. If that first interaction isn’t great, it sets the tone for everything that follows. I’m challenging businesses & hiring managers to rethink how we treat candidates. Why make them jump through hoops when they haven’t even had enough info to decide if they want to join? 💡 A shift we’ve made: We’ve agreed globally & for all level roles, to hold the hiring manager interview before the case study/task. This ensures candidates have enough information to make an informed decision before investing time in a task that might not even be relevant if they aren’t aligned with the role or team. 💭 Why does this matter? I get it, hiring managers might think, “But what if they fail the test?” The truth, candidates who meet with the hiring manager first are MORE engaged, motivated & informed allowing this to shine through in their task. There will also be less drop off from candidates who haven't had a chance to meet the most important person in the process - their future manager! Talent - Here’s how to start: 1️⃣ Audit your funnel: Where are candidates dropping off, and why? 2️⃣ Map the candidate journey: How is their experience at each stage? Are they feeling informed and valued? 3️⃣ Educate hiring managers: Candidate experience isn’t just about filling a role - it’s setting up a future employee for success. Their experience impacts engagement and retention long after they're hired. 💪 Now’s the time for action. Let’s not just hire great talent, let’s treat them right from the start. Prioritise their experience and see how it impacts conversion, engagement, and retention. 💬 I’d love to hear from you — Hiring managers, how are YOU ensuring a great candidate experience? Candidates, what’s your experience been like? Talent, what have you built in to ensure engaging interview process? Drop a comment, share your thoughts and let’s start a conversation! 👇 #CandidateExperience #EmployeeExperience #Hiring #InfluencingVoices