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I think it’s time to recalibrate expectations around what AI can do for SaaS companies. As with any emerging technology, I’m seeing two trends: The scared founder : “ I’ve built my entire company around the SaaS model; It feels risky, like too much of a leap to bake AI Agents into the product. It is not my model; it is a distraction.
It seems there is confusion between what I call the “ Zapier Engineer ” and the “ AI Automation Engineer.” I think it is rooted in two false beliefs: AI added an extra intelligent layer that allows us to connect different services using Zapier as glue without writing a single line of code. You don’t need to be a software engineer to build… software (this one makes me laugh every time.
We expect so much from our developers. The unbearable thought that one developer could be idle or have nothing to do is one of the worst nightmares a manager could have. Now, with the AI tools, this has intensified : we are not only expecting our developers to do system design, coding, testing, shipping, and maintaining, but we expect them to do it 10x faster.
I’ve been talking with a few startup friends, and they are telling me the same story: “ We are not hiring anymore, only some specific roles. Thanks to AI, we are now 2-3x more productive. “ They are thinking: “ Instead of hiring a new engineer who could risk my current speed, I’d rather invest in AI to make my team go faster.” After all, why spend $100k a year on a Junior Engineer when I can pay $1k a year to make my Senior Engineer twice as productive?
If you are a senior manager with enough tech cycles under your belt, you might be feeling it. You might not be able to fully explain it because this time is different: it has new elements, and it feels bigger. But it is happening. You know something is wrong with your engineering team, and you need to make changes fast. Otherwise, they are heading for a reputation crash (fueled by overpromise and underdeliver).
If you are like me, one of your biggest nightmares is hiring the wrong engineer. That engineer who won’t play well with the rest of the team, gets into technical fights with the most senior members, and works on side projects he/she believe are more important for the company. I don’t like micromanagement; it is too time-consuming. I also don’t want to rush features that will harm my team’s reputation.
COVID accelerated Remote Work. Remote Work accelerated AI. And AI is not accelerating, it is reshaping the job market. A +20 Years Old Trend Back in 2005, my first client was a media agency from Spain. It was one of my worst clients. It was also my first experience as a remote contractor. Back then, people called it telework. I remember a professor explaining the benefits of teleworking, and all the students looked at her like she was crazy.
Why are Tech Companies Laying Off? Before I get to the answer, let me get something off my chest: when big tech companies (Meta, Microsoft, Amazon) lay off people, it causes a nonsensical ripple effect in small tech startups. Founders think, “ If they are laying off, something is coming, I should do the same.” The irony is that, I believe, big companies are not laying off to cut costs: they are reorganizing their workforce to integrate (you already know) AI and Automation.
AI that can code sounds like a dream come true: “ Ask what you need, and the AI tool will write the code for you. “ Engineers’ first reactions were something like, “ This is exactly what I was looking for! ” and the fear in the back of their heads was, “ This is it. We are out of jobs. “ To me, the first time I tried GitHub Copilot was a bad experience… too many retries/reasking the same questions.
The pandemic didn’t just change where we work it fundamentally altered how we perceive loyalty to the office. As a remote software engineer, I’ve witnessed firsthand the rising tide of remote work resistance, where the allure of flexibility trumps the old-school office grind. Gone are the days of commuting for hours, staring at spreadsheet-induced headaches, and striving for that coveted corner desk.
Ever found yourself staring at your screen at 7 a.m., only to realize its already 9 and youve accomplished nothing? Welcome to the paradox of remote engineering: the freedom is liberating, but without the right self-discipline, it can quickly turn into a productivity black hole. As a remote software engineer, self-discipline for remote engineers isn’t just a handy traitit’s the secret sauce that separates thriving professionals from those stuck in the endless cycle of uncompleted tas
Every remote engineer knows that while coding from a cozy home office has its perks, maintaining seamless collaboration across time zones can feel like herding cats with caffeine. Mastering remote engineering skills is not just a nice to have its the secret sauce that turns solitary code warriors into cohesive, high-performing teams. Identifying and honing the most critical skills for remote work has never been more essential.
Distraction-free coding is every developer’s ultimate goal, isn’t it? Imagine this: it’s 2 AM, your code refuses to comply, and your only companions are a half-drunk coffee and your coffee-fueled determination. The chaos of home life, endless meetings, and the constant temptation of social media can derail even the most dedicated coder.
Have you ever felt like every keystroke you make is being watched, even when you’re miles away from the office? Welcome to the unsettling world ofmicro-management, where constant oversight silently erodes team morale and stifles creativity. In the early days of remote work, leaders thought tighter control would ensure success. However, history has shown that micro-managementdoesn’t foster trustit suffocates it.
Understanding the differences between traditional and remote team management is crucial in the evolving landscape of remote engineering team management. Whether you’re a startup founder, CTO, or HR professional, adeptly managing teams in a remote setting can significantly influence your company’s productivity and culture. This guide delves into the contrasting tactics of traditional and remote team management, highlighting the unique challenges and strategies associated with each.
Introduction Color plays a pivotal role in shaping brand identity, influencing consumer perceptions, and driving marketing success. Understanding the impact of color branding can significantly enhance your brand’s visibility and emotional connection with your audience. In the advertising and marketing industry, where competition is fierce, leveraging the right colors can set your brand apart and foster a deeper connection with your target market.
Introduction In the rapidly evolving world of software development, the integration of artificial intelligence (AI) has become a cornerstone for innovation. However, with this advancement comes the challenge of ensuring fairness and equity in AI-driven systems. The concept of “ Human-in-the-Loop ” for bias mitigation is gaining traction as a vital strategy to address these concerns.
Introduction Implementing federated learning in ad tech presents unique challenges that require innovative solutions. This article explores the key challenges and potential solutions for integrating federated learning into advertising technology platforms. Overview of Federated Learning Challenges Key Points Data Privacy: Ensuring user data remains private and secure.
Graph Neural Networks (GNNs) are revolutionizing Real-Time Bidding (RTB) systems in the ad tech industry. This article explores how GNNs can enhance RTB systems, providing a robust solution for developing AI-powered advertising platforms. Understanding Graph Neural Networks for RTB Systems Key Points Graph Neural Networks (GNNs) can significantly improve the performance of RTB systems.
Understanding the emotional impact of your local advertising campaigns can be a game-changer. By measuring how your audience feels about your ads, you can fine-tune your strategies to create more effective and engaging campaigns. This article explores the importance of emotional impact metrics and how to measure them effectively. Understanding Emotional Impact Metrics Key Points Emotional impact metrics help gauge audience reactions.
Understanding the role of mirror neurons in consumer behavior can provide valuable insights for marketing professionals. This article explores how these specialized brain cells influence purchasing decisions and how marketers can leverage this knowledge to enhance engagement and conversion rates. Understanding Mirror Neurons Key Points Mirror neurons fire both when performing an action and observing the same action.
Understanding the role of color psychology in neuroaesthetics can significantly enhance advertising and marketing strategies. This article delves into how colors influence human emotions and behaviors, providing valuable insights for marketing managers, advertising executives, and media planners. Understanding Color Psychology in Neuroaesthetics Key Points Colors can evoke specific emotional responses.
Building trust and accountability in remote teams is crucial for maintaining productivity and fostering innovation. This article explores strategies to achieve these goals, particularly for individuals in leadership roles within the ad tech sector. Understanding Trust and Accountability in Remote Work Key Points Clear communication is essential for building trust.
Understanding the neuroscience behind emotional engagement in advertising can significantly enhance your marketing strategies. By leveraging insights from brain science, you can create more impactful and memorable ads that resonate with your audience. Introduction to Emotional Engagement in Advertising Key Points Emotional engagement drives consumer behavior Neuroscience helps measure emotional responses AI can analyze and optimize emotional engagement Effective emotional engagement boosts ROI U
In the ever-evolving landscape of cybersecurity, understanding and mitigating multi-vector attacks is crucial. Behavioral clustering offers a powerful approach to identify and counteract these complex threats. This article delves into the intricacies of multi-vector attack clustering, providing insights and practical solutions for cybersecurity professionals.
In the rapidly evolving field of cybersecurity, e xplainable AI (artificial intelligence) techniques are becoming crucial for effective cyber threat detection. These techniques not only enhance detection capabilities but also provide transparency and trust in AI systems, which is essential for decision-makers in medium to large enterprises. Overview of Explainable AI in Cyber Threat Detection Key Points Explainable AI enhances transparency in cyber threat detection.
Trust metrics are essential for managing remote teams effectively. They help leaders gauge trust levels, which is crucial for maintaining productivity and fostering innovation. This article delves into the importance of trust metrics, the challenges faced in the remote developers industry, and practical solutions to overcome these challenges. Understanding Trust Metrics Key Points Trust metrics are vital for remote team management.
AI bias in advertising is a significant concern in the ad-tech industry. This article explores how to mitigate bias in AI-driven advertising, ensuring fair and inclusive marketing practices. Understanding AI Bias in Advertising Key Points AI bias can perpetuate stereotypes and exclusionary practices. Diverse training data is crucial for reducing bias.
Key Points Homomorphic encryption allows computations on encrypted data without decryption. Federated learning trains models across multiple decentralized devices. Combining these technologies enhances privacy in machine learning. Challenges include computational overhead and communication costs. Optimized systems like FedML-HE reduce these overheads significantly.
Integrating RNNs with Graph Neural Networks for Cybersecurity is a cutting-edge approach that combines the strengths of Recurrent Neural Networks ( RNNs ) and Graph Neural Networks ( GNNs ) to enhance cybersecurity measures. This integration aims to provide a robust solution for detecting and mitigating cyber threats by leveraging the sequential data processing capabilities of RNNs and the relational data handling prowess of GNNs.
Privacy-preserving GANs offer a promising solution for protecting user data while enabling effective digital marketing. This article explores how these advanced techniques can safeguard user privacy without compromising the utility of data for marketing purposes. Understanding Privacy-Preserving GANs Key Points Privacy-preserving GANs generate synthetic data to protect user privacy.
Introduction Understanding the connection between mirror neurons and emotional branding can revolutionize how you approach marketing strategies. By tapping into the brain’s natural empathy mechanisms, you can create more effective and resonant campaigns that deeply connect with your audience. Mirror Neurons and Emotional Branding Key Points Mirror neurons play a crucial role in emotional branding by fostering empathy and connection.
In the rapidly evolving world of mobile advertising, ensuring user consent and privacy is paramount. This article delves into the importance of user consent and privacy in mobile ads, the challenges faced by the industry, and practical solutions to address these issues. Understanding User Consent and Privacy Key Points Importance of user consent in mobile advertising Challenges in maintaining user privacy Regulatory frameworks and compliance Best practices for obtaining user consent Future trend
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In the fast-evolving world of ad tech and AI advertising, cross-channel programmatic advertising has emerged as a powerful strategy to optimize ad performance and leverage AI for marketing insights. This article delves into the key aspects of cross-channel programmatic advertising, its challenges, and effective strategies to overcome them. Understanding Cross-Channel Programmatic Advertising Key Points Enhanced Audience Reach: Cross-channel advertising ensures your message reaches a broader audi
Integrating federated learning with generative adversarial networks (GANs) offers a promising approach to enhance privacy in AI-driven applications. This article explores the key points, challenges, and solutions related to this integration, providing insights for technology leaders in the cybersecurity industry. Overview of Federated Learning and GANs Key Points Federated learning allows decentralized data training without sharing raw data.
Emotional contagion plays a significant role in influencer marketing, impacting how audiences perceive and engage with content. Understanding this phenomenon can help marketing managers and advertising executives create more effective campaigns. Understanding Emotional Contagion in Influencer Marketing Key Points Emotional contagion is the process by which emotions are transferred from one person to another.
Understanding mobile ad data privacy is crucial for marketing professionals. This article explores the importance of user consent and data privacy, especially in the context of mobile advertising. It provides insights into the challenges faced by the industry and offers practical solutions to enhance user trust and compliance with data protection laws.
In the fast-paced world of real-time bidding (RTB), advanced feature engineering is crucial for developing predictive models that can optimize ad placements and maximize returns. This article delves into the intricacies of feature engineering in RTB, offering insights and practical steps for industry professionals. Understanding Advanced Feature Engineering in RTB Key Points Importance of feature engineering in RTB.
In the advertising and marketing industry, finding the right balance between personalization and privacy is crucial. This article explores how to achieve this balance, providing insights and practical steps for marketing professionals. Understanding Personalization vs Privacy Key Points Personalization enhances customer experience but requires data collection.
AI-driven predictive analytics is revolutionizing the cybersecurity landscape by enabling organizations to anticipate and mitigate threats before they materialize. This article delves into the key aspects of AI predictive analytics in cybersecurity, the challenges faced by the industry, and practical solutions to enhance security measures. Understanding AI-Driven Predictive Analytics Key Points Proactive Threat Detection: AI predictive analytics helps in identifying potential threats before they
Asynchronous communication in remote teams is essential for maintaining productivity and fostering innovation. This article explores the key points, challenges, and solutions for implementing effective asynchronous communication strategies in remote development teams. Understanding Asynchronous Communication Key Points Flexibility: Allows team members to work at their own pace.
Real-time data processing is crucial for dynamic bidding in the ad tech industry. This article explores the key aspects of real-time data stream processing, its challenges, and solutions, providing insights for CTOs, software development managers, and product managers in ad tech startups and medium-sized companies. Understanding Real-Time Data Stream Processing Key Points Real-time data processing is essential for dynamic bidding in ad tech.
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