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AI illustrationAI or humans: what's the real problem?
Insights: Summary and key points · Glossary statistics
AI illustrationDistilling models to save tokens — Prima o Poi #63 clip
AI illustrationWill AI kill us all?
Insights: Summary and key points · Glossary statisticsSOUND FAMILIAR?
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AI illustrationAI or humans: what's the real problem?
Insights: Summary and key points · Glossary statisticsIn the debate about AI risks, Montemagno focuses on the incentives shaping people and companies. He links the development race to listings, financial rewards and investor exits, citing social media as a precedent for distorted incentives. His argument is that restricting one technology cannot remove the underlying problem while those motivations remain unchanged.
AI illustrationDistilling models to save tokens — Prima o Poi #63 clip
A clip from Prima o Poi #63. The official description discusses using cheaper models for repetitive tasks and more powerful models for reasoning as a possible way to manage costs.
AI illustrationWill AI kill us all?
Insights: Summary and key points · Glossary statisticsMontemagno separates AI tools’ present capabilities from possible future risks. He contrasts limited adoption of advanced uses and errors in his own automation tasks with rapid technical progress. He does not treat current limitations as a future guarantee, leaving open the possibility that researchers and more advanced systems reveal substantially greater risks.
AI illustrationCommand line or desktop app? — Prima o Poi #63 clip
A clip from Prima o Poi #63. The official description contrasts command-line speed and parallel agents with the visibility offered by a desktop app that brings the tools together.
AI illustrationWill AI kill us all?
Insights: Summary and key points · Glossary statisticsTitle and date from the official feed. Open the source for the full content.
AI illustrationWill AI kill us all?
Insights: Summary and key points · Glossary statisticsMontemagno approaches the debate over extreme AI risk by separating observable capabilities, future scenarios and the interests of those raising alarms. He expresses suspicions about corporate communication while recognizing that both risks and benefits deserve attention. His central concern is political and economic: incentives to race, geopolitical competition and conflicting interests complicate safety. He calls for oversight, discussion and a stronger user voice in development’s collective consequences.
AI illustrationPrima o Poi #63 — Not all that glitters is AGI
Monty, Paolo Barberis and Max Ciociola discuss AI announcements and working with agents. Shortened title; original video link verified against the official channel.
AI illustrationDo views still matter?
Insights: Summary and key points · Glossary statisticsViews do not have one consistent meaning, Montemagno argues: they depend on platforms, formats and counting rules. A large number can include fleeting exposure, paid promotion or inauthentic traffic. He encourages creators and audiences to ask how the metric is constructed and what attention it represents before treating it as a measure of value.
AI illustrationYou can buy ubiquity: the social media trick
Insights: Summary and key points · Glossary statisticsMontemagno describes paid clipping as a way to make a person or podcast appear to be everywhere. Clips distributed by many accounts can look spontaneous while being supported by payments and affiliate incentives. His criticism focuses on promotional transparency and platforms’ responsibility to distinguish perceived popularity from purchased attention.
AI illustrationThe dark side of social media
Title and date from the official feed. Open the source for the full content.
AI illustrationEverything They Don’t Tell You About Social Media
Insights: Context and key pointsTitle and date from the official feed. Open the source for the full content.
AI illustrationThe dark side of social media
Insights: Summary and key points · Glossary statisticsDrawing on his experience as a creator, Montemagno questions views as a uniform measure of success and describes how paid clipping, algorithms and editorial choices shape perceptions of social media. He connects these mechanisms to comparisons with idealized lives and incentives for extreme content. While recognizing platforms’ value for learning and visibility, he encourages protecting attention, assessing personal effects and building relationships with genuinely interested people.
AI illustrationPrima o Poi #62 — A surprise GPT-6 release
A conversation on AI and technology news. These topics reflect the hosts’ claims, not independent verification by AskMonty.
AI illustrationArtificial intelligence: what Monty really thinks
Title and date from the official feed. Open the source for the full content.
AI illustrationEverything I think about AI (unfiltered...)
Insights: Summary and key points · Glossary statisticsMontemagno gathers reflections on everyday AI use, emphasising responsibility, meaningful checks and clear objectives. He distinguishes chatbots from agents that can act and amplify mistakes as well as productivity. He challenges miraculous tools and confident forecasts, favouring practical benefits for ordinary work. In content and education, he prioritises reputation, critical thinking and using AI to challenge rather than merely confirm one's beliefs.
AI illustrationIt's simple, but it isn't easy
Insights: Summary and key points · Glossary statisticsMontemagno distinguishes a simple principle from the difficulty of putting it into practice. Fitness and selling a product illustrate why knowing the instructions does not mean carrying them out. He criticises shortcuts that promise more information when the decisive task is consistently doing what is already understood.
AI illustrationForget motivation
Insights: Summary and key points · Glossary statisticsMotivation is presented as an intermittent aid rather than a prerequisite for action. Montemagno says he has often worked without initial enthusiasm and observes that motivation can follow getting started. He therefore advocates schedules and working systems that make action possible even when inspiration is absent.
AI illustrationHow to schedule tasks for your AI agent
Insights: Summary and key points · Glossary statisticsMontemagno demonstrates assigning an AI agent recurring research for LinkedIn ideas and draft preparation. He extends the example to calendar reviews and researching a potential client before a meeting. Delegation remains adjustable: the assistant can prepare material while the user retains control over subjects, revisions and editorial decisions.
AI illustrationHow to turn your ideas into LinkedIn posts with an AI agent
Insights: Summary and key points · Glossary statisticsCreating a LinkedIn post becomes an example of collaboration between an author and AI. Montemagno supplies three ideas about self-employment, then corrects grammar, invented wording and the draft’s tone. Even adding humour produces unsatisfactory results: the example highlights the thinking and revision still required when the execution of writing changes.
AI illustrationTrying to please everyone is a sign of mediocrity
Insights: Summary and key points · Glossary statisticsMontemagno criticises trying to satisfy every possible customer, arguing that it can dilute a product and make it forgettable. Examples from services and restaurants contrast a clear proposition with an offer that accommodates every request. He encourages focusing on the right audience and accepting disagreement rather than pursuing unanimous approval.
AI illustrationYour AI assistant for LinkedIn: how to build it from scratch
Insights: Summary and key points · Glossary statisticsA LinkedIn assistant illustrates an interface that hides many technical choices behind a conversation. Montemagno contrasts quick and advanced options and describes the credit system of the service being demonstrated. The aim is to start with a concrete activity, such as preparing content, without manually selecting every model or technical connection.
AI illustrationBuild a life you don't need to escape from
Insights: Summary and key points · Glossary statisticsDrawing on his experience of self-employment, Montemagno asks what makes everyday life something to escape. Holidays, he argues, cannot repair work experienced as a prison. Working for oneself can reproduce the same problems: the question is what is missing from ordinary days, rather than simply how many remain until the next break.
AI illustrationIt's easier to improve tenfold than by 10%
Insights: Summary and key points · Glossary statisticsMontemagno uses the idea of a tenfold improvement to discuss changing methods. He draws on ambitious projects and his table-tennis training, where finding a different environment mattered more than adding hours. Comparing this with incremental improvement prompts him to question the scale of projects deserving his energy and the need to reinvent his approach.
AI illustrationHow to create your AI agent (without knowing how to code)
Insights: Summary and key points · Glossary statisticsThe demonstration presents Hostinger agents’ preset skills, from value propositions to writing a post. Montemagno shows an interface that asks about the subject, audience, tone and length, reducing the work involved in formulating a request. His example suggests letting the assistant ask questions, while the quality of the result still depends on the information supplied.