PromptBlocks for Recruiters
The Challenge
Recruiters juggle multiple clients, dozens of open roles, and hundreds of candidates simultaneously. Context is everything—but it's scattered across emails, spreadsheets, ATS systems, and your own notes. Every AI conversation starts from scratch, forcing you to re-explain client requirements, role specifics, and candidate histories over and over.
The result: wasted time, mixed-up details, and missed connections between the perfect candidate and the right opportunity.
How PromptBlocks Helps
1. Projects: Your Client Command Center
Create a dedicated project for each client or search engagement. This is your single source of truth for everything related to that relationship:
- Client context: Company culture, team dynamics, hiring manager preferences, compensation philosophy
- Role requirements: Must-haves, nice-to-haves, deal-breakers, growth trajectory
- Pipeline notes: Where candidates stand, interview feedback, decision history
When you open a client's project, the AI instantly has full context. No more "let me explain the background..." at the start of every conversation. Ask "should I present this candidate?" and the AI evaluates against everything it knows about that client's needs.
2. Mid-Chat Project Switching: Cross-Pollinate Your Pipeline
This is where PromptBlocks becomes a recruiting superpower.
You're deep in a conversation about a candidate for Client A when it hits you—this person might actually be perfect for Client B's role. With one click, switch to Client B's project mid-chat. Now the AI has Client B's full context: their requirements, culture, what they've said yes and no to before.
Real scenario:
- You're reviewing a product manager candidate for a Series B startup
- Their enterprise background is a concern for that client
- Switch to your Fortune 500 client's project mid-chat
- Instantly evaluate the same candidate against enterprise requirements
- The AI pulls in the F500 client's stated preferences and past feedback
- You realize this is actually a better fit, and you haven't lost any context
Switch back to the startup project and continue where you left off. Your insights travel with you, but the context stays client-specific.
3. File Knowledge: Your Documents Answer Questions
Attach job descriptions, org charts, interview guides, and compensation bands directly to each project. The AI doesn't just store these—it searches them when you ask questions.
How it works:
- Upload the detailed JD, hiring manager's wish list, and team structure doc
- Ask "What are the must-have technical requirements for this role?"
- The AI searches your attached files, finds the relevant sections, and cites them
- Ask "What's the reporting structure for this position?" and it pulls from the org chart
No more flipping between tabs to double-check requirements. No more accidentally pitching the wrong salary range. The AI finds and cites exactly what's in your documents.
4. Chat History Search: Find Past Conversations Instantly
Three weeks ago, the hiring manager gave specific feedback on why they passed on a candidate. Where is that conversation? With PromptBlocks, you don't have to remember or dig through chat logs.
Search across your conversation history:
- "What feedback did Sarah give on backend candidates last month?"
- "What concerns came up about remote work for this client?"
- "What did we decide about the salary flexibility?"
The AI searches your past conversations and surfaces the relevant context. That offhand comment from the hiring manager? Found. The decision you made about a candidate two weeks ago? Retrieved with full context.
5. Memory: The AI That Learns Your Clients
As you work, PromptBlocks builds persistent memory for each project. Say "remember that this client strongly prefers candidates with startup experience" and it's captured. The AI also suggests memories based on your conversations—accept the ones that matter.
What gets remembered:
- Client preferences ("They value culture fit over technical perfection")
- Candidate notes ("John withdrew—taking a counteroffer, but open to future roles")
- Decisions and reasoning ("Passed on candidate due to relocation concerns")
- Hiring manager quirks ("Sarah responds better to bullet points than paragraphs")
This memory persists across every conversation for that client. A month from now, when you're working a new role for the same client, all that accumulated knowledge is there. You're not starting from scratch—you're building on everything you've learned.
Sample Prompts
Candidate-Role Fit Analysis
I'm considering presenting this candidate to the client:
Background: 8 years in enterprise SaaS, last 3 as Director of Product at a Fortune 500. Strong technical background, led teams of 12+. Looking for a smaller company with more ownership.
Based on everything you know about this client and role:
1. What are the strongest alignment points?
2. What concerns might the hiring manager raise?
3. How should I position this candidate in my presentation?
Cross-Client Candidate Placement
I just interviewed a candidate who's strong but not right for this role. Their strengths: deep ML/AI experience, prefers IC roles, values work-life balance, comp expectations around $180K.
Which of my other active searches might be a fit? Consider the requirements and culture of each client.
Interview Prep From History
I'm prepping for tomorrow's debrief with the hiring manager. Search our past conversations and remind me:
- What feedback have they given on previous candidates?
- What patterns have emerged in who they like vs. pass on?
- Any specific concerns they've raised about this role?
Getting Started
- Create your first client project — Add the company overview, role requirements, and any context about the hiring manager and team
- Upload key documents — Attach the job description, interview guides, and compensation details so the AI can search them
- Start working and building memory — As you chat, accept memory suggestions or explicitly tell the AI what to remember about this client
- Use project switching — When you spot a potential cross-client fit, switch projects mid-chat to evaluate with full context
Your recruiting intelligence compounds with every conversation.