Kozminski Techblog

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Introduction to Prompt Engineering in Hiring

Prompt engineering is a technique in artificial intelligence (AI) in which particular instructions or “prompts” are designed to produce exact outputs from generative models. This method has gained popularity across sectors for activities such as automating content production, optimizing procedures, and hiring.

In recruiting, quick engineering may help firms evaluate resumes, create job descriptions, and undertake early applicant assessments. Businesses may use targeted prompts to enhance the accuracy and effectiveness of their recruiting procedures, saving time and resources.

InPost’s approach represents one of the earliest large-scale adoptions of prompt engineering in recruitment within the logistics sector.

InPost’s Practical Application of Prompt Engineering

InPost, led by Rafał Brzoska, has implemented fast engineering to improve recruiting for logistics and technology professions. They’ve used powerful generative AI technologies like Zapier and proprietary GPT-like solutions to automate screening and evaluating candidates’ core abilities by comparing applications to job-specific requirements.

Recruitment Optimization:

InPost optimizes recruitment by using AI to filter resumes and better match individuals to jobs. Using language models like as OpenAI’s GPT, the organization compares applicants’ talents, experiences, and qualifications to established job criteria. The AI creates score measures that allow recruiters to focus on top applicants without the need for human filtering. For example, prompts are intended to collect important facts, check alignment with job tasks, and even indicate potential mismatches, therefore expediting the hiring process.

Enhanced Candidate Communication:

Another innovative application is in candidate interaction. Using tools like GPT-based AI or conversational platforms such as Intercom or Drift (integrated with generative AI), InPost ensures that applicants receive personalized updates at each recruitment stage. This includes AI-generated emails with tailored feedback, which improves transparency and builds trust with candidates.

Training and Development of AI Models:

InPost likely employs fine-tuning methods on models like GPT, using historical hiring data to enhance the accuracy of candidate evaluations. These customizations ensure the AI recognizes industry-specific terminology and evaluates nuanced qualifications critical in logistics roles. By integrating platforms like Make.com or Zapier, InPost further connects its generative AI tools to broader workflow automations, creating a seamless recruitment system.

Insights from Rafał Brzoska

Rafał Brzoska has highlighted how leveraging AI, including prompt engineering, has significantly reduced time-to-hire and improved the overall quality of recruits at InPost – On his LinkedIn, he emphasizes that embracing such technologies is not just a trend but a necessity in staying competitive in the logistics and tech-driven market. The company’s AI initiatives, including those in hiring, reflect their commitment to efficiency and excellence in operations

Broader Implications for Other Companies
Other organizations can take inspiration from InPost’s model by adopting prompt engineering for:

1. Crafting detailed, unbiased job descriptions that attract diverse talent.
2. Pre-screening resumes using AI to filter out mismatches.
3. Using AI-driven chatbots to conduct initial candidate interviews.

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Written with help of Claude.ai

Sources:

https://www.pracuj.pl/praca/prompt-engineer-warszawa-czerniakowska-87a,oferta,1002513338

https://www.ey.com/en_lb/weoy/class-of-2022/poland

https://inpost.pl/kariera/data-ai

https://www.linkedin.com/jobs/view/ai-engineer-at-inpost-4083473735/

InPost oferuje pracę przyszłości? Prompt engineer będzie pracował m.in. z GPT-4

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With breakthroughs in AI, organization now have a unique chance to alter the way they run consumer testing by leveraging sentiment analysis to acquire a richer, more accurate understanding of customer input. This method expands on standard surveys and focus groups by allowing AI to decipher emotional reactions and even assess the legitimacy of customer replies.

Why It’s a Game-Changer for Companies ?

AI-powered sentiment analysis, combined with speech-to-text capabilities, provides a valuable instrument. It catches every detail in a consumer’s voice, from eagerness and hesitancy to confidence and uncertainty, giving businesses insight into the underlying emotions driving consumer behaviors. AI can transform verbal input into useful insights by identifying alterations in tone or word choice that convey deeper sentiment.

One of the most amazing features of AI in consumer tests is its prediction ability to determine the validity of replies. AI can distinguish between real and filtered or exaggerated feedback using data patterns and algorithms that identify consistency, spontaneity, and natural expression. This discovery enables businesses to focus on true insights while eliminating biases that might distort outcomes.

Mariot International Case Study:

Marriott International uses AI-powered sentiment analysis to handle customer reviews and comments from over 7,000 hotels worldwide. By evaluating themes and feelings in guest evaluations, including as room cleanliness, staff friendliness, and amenity quality, Marriott may identify opportunities for improvement at individual properties. For example, if a hotel receives recurrent complaints about service delays, managers may rapidly address the problem by changing staffing or processes.

EA Case Study:

Leading video game publisher Electronic Arts (EA) uses artificial intelligence (AI) sentiment analysis to handle player reviews and comments for their titles. EA determines which aspects users like and which ones could require a little more work by examining sentiment at the game level.

This kind of potentially ignored information can help with problem patches, game upgrades, and the creation of new games. EA can modify a game’s micro-transaction system to make it more player-friendly and enhance reviews from third-party critics if feedback analysis shows that users are dissatisfied with the system, which is a very common problem in the video game industry. It basically means that they analyze your in game chats.  

AI sentiment analysis is also relevant in a variety of industries, including automotive, healthcare, e-commerce, and entertainment. Businesses that regularly monitor and respond to consumers maintain a great online reputation, develop customer loyalty, and gain a competitive advantage in their particular sectors.

Sentiment market in Poland

As more people use AI-driven products, the sentiment analysis market in Poland is expanding. Growing social media usage and the need for real-time analytics in sectors like finance, retail, and telecommunications are driving this expansion. Globally, the market is growing at a compound annual growth rate (CAGR) of more than 17%, with developments in machine learning and natural language processing (NLP) playing important roles. Applications in Poland are mostly found in brand reputation tracking and customer experience management, where businesses use local language natural language processing (NLP) techniques to increase efficiency.

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Resources:

https://www.widewail.com/blog/10-real-world-examples-of-ai-topic-sentiment-analysis

sentire2024karlinska.pdf

Sentiment Analysis Software Market Report 2024 – Sentiment Analysis Software Market Trends And Overview

15 Sentiment Analysis Statistics in 2024 – Marketing Scoop

Consumer Sentiment in Poland Remains Positive

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Text is basing on the output of Chat GPT

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As AI-powered technologies advance, companies can automate a variety of operations that formerly required a specialized sales crew with relatively little knowledge. This article will briefly present a strategic approach of building AI powered sales system with tools that are available for everyone.

AUTOMATED LEAD GENERATION WITH APOLLO.IO

This tool enriches each prospect’s profile with verified contact details, including email addresses, phone numbers and social media links allowing for more effective and informed outreach. Integration of Apollo.ai with platforms like Airtable (covered next) creates a seamless workflow for managing and organizing leads within the pipeline.

ORGANIZING LEADS IN AIRTABLE

Airtable serves as flexible CRM-like (customer relationship managament system) database that is ideal for tracking leads, managing contact information and visualising current marketing efforts. Its automation features simplify many repeating task like reporting, status updates etc.

OUTREACH AUTOMATION WITH INSTANTLY.AI

This tool is a core of whole direct outreach. By automating follow-up sequences based on recipient engagement, Instantly.ai ensures continous outreach without manual effort. Tool offers tailored messaging and timely follow-ups within fully automated marketing campaigns. It serves as a scalable solution that mimics personalized interactions across numerous leads efficiently.

SYSTEM INTEGRATION WITH ZAPIER.COM

Zapier automates workflows by seamlessly connecting various platforms, enabling synchonized data updates and task triggers across tools like those mentioned above. For example. Zapier can initiate email sequences or update lead statuses based on present actions, streamlining operations without manual intervention.

Integrating mentioned tools unlocks many opportunities for scalable growth and seamless automation for smaller to medium businesses, that with this knowledge won’t even need a marketing agency.

P.S This automation serves as a basis for my company to generate 5-6K zł profit every month for 7 consecutive months!

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Reference links:

Apollo.io

Airtable.com

Instantly.ai

Zapier.com

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