Your AI Pilot Was Cheap. The Bill Won't Be

In this episode, Ricardo warns that artificial intelligence is often approved as a project cost, but after implementation, it becomes an ongoing operational expense. Unlike traditional licenses, its cost varies according to consumption: the greater the adoption, the higher the bill. He also highlights frequently ignored expenses such as data preparation, systems integration, human review, price changes, model replacement, and new testing. Ricardo recommends presenting recurring costs per unit, projecting growth scenarios, identifying who will assume the expense after the project ends, and proactively assessing exit costs. For him, advancing with AI is essential, but it requires financial discipline. Without knowing the cost, the responsible party, and the value generated, there is no complete and sustainable business case. Listen to the podcast to learn more!

In this episode, Ricardo warns about the risk of resuming January’s projects at midyear. According to him, the context has changed: budgets, suppliers, technology, markets, regulations, and priorities may now be different. Before following the original plan, he recommends three actions: recalculate the project using current information, assess external changes, and reevaluate the portfolio, prioritizing what truly matters. Ricardo emphasizes that replanning does not represent failure; instead, it shows awareness of the transformations that have occurred. He suggests setting aside two hours, gathering people who understand the project’s reality, and asking whether it would still be approved today with the same structure, scope, team, and cost. This reflection reveals whether the project will meet the organization’s needs in December. Listen to the podcast to learn more!

In this episode, Ricardo explains that modern projects depend heavily on external suppliers, contractors, partners, and AI vendors whose teams do not report directly to the project manager. He argues that leading these people has become a core project management skill. He emphasizes that contracts and service-level agreements define obligations and penalties but do not create trust, commitment, or guarantee success. Ricardo also warns that supplier risk should be treated as a major project risk. He recommends involving partners in planning, explaining the project’s purpose, addressing problems early, and speaking directly with leaders who can reallocate resources. Finally, he encourages managers to identify their three most critical external organizations and build genuine relationships with their senior decision-makers. Listen to the podcast to learn more!

In this episode, Ricardo discusses the common rush to start acting before fully understanding a project’s problem. Action creates a sense of progress, while thinking may seem like wasted time. However, teams can work intensely and still move quickly in the wrong direction. Ricardo emphasizes that speed should not be confused with impulsiveness. Asking simple questions about the problem, missing information, potential consequences, urgency, and reversibility can prevent weeks of unnecessary rework. Even during crises or emergencies, acting quickly does not mean abandoning reflection. Planning often appears expensive because it happens before execution, while the cost of correcting poor decisions remains hidden. Before saying there is no time to think, teams should ask whether they have time to do the work twice. Want to know more? Tune in to the podcast!

In this episode, Ricardo discusses rework, one of the most damaging yet invisible costs in projects. Rework occurs when presentations, software, proposals, plans, or decisions must be redone because expectations, requirements, or responsibilities were unclear. Although teams appear busy, they may simply be returning to a point they believed they had already reached—paying multiple times for a result. The later an error is discovered, the greater its impact, which shows that speed does not always mean efficiency. Ricardo highlights avoidable rework caused by haste, poor communication, ambiguous decisions, weak planning, and unvalidated requirements. He suggests measuring not only completed work, but also how much had to be repeated. True efficiency means transforming effort into results with minimal waste. Want to know more? Tune in to the podcast!

In this episode, Ricardo explains that projects are promises about a future often experienced by people other than those who originally approved or delivered them. He argues that organizations tend to exaggerate benefits, minimize long-term costs, and focus on schedules, budgets, scope, and acceptance instead of verifying whether promised outcomes materialize. Ricardo highlights the imbalance between those who gain visibility by making promises, those pressured to execute them, and those left to operate solutions and face their consequences. He offers three recommendations: involve the people who will inherit the project from the beginning, document promised benefits as carefully as deliverables, and extend accountability beyond project closure. Ultimately, he says projects must create the future used to justify their existence. Listen to the podcast to learn more!

In this episode, Ricardo reflects on reactions to his newsletter about project management in the age of AI. He stresses that he is not predicting the future but encouraging professionals to question assumptions and prepare for rapid change. Although some readers considered his views alarmist, he argues that learning AI carries little downside: even if its impact is smaller than expected, new skills remain valuable. However, ignoring AI could be risky if organizations continue redesigning structures, PMOs, governance, roles, and teams. Ricardo believes project management will not disappear, but it will evolve significantly. His central concern is helping younger professionals remain relevant, adaptable, and responsible for their choices in a world changing faster than ever before through continuous learning and reflection. Listen to the podcast to learn more!

In this episode, Ricardo reflects on how many project managers have shifted from managing projects to merely reacting to urgent matters. Their daily routines are consumed by meetings, messages, emails, and immediate issues, creating a sense of heavy workload but little actual progress. According to him, managing projects means reducing uncertainty, whereas managing anxiety amounts to nothing more than reacting to chaos. Artificial intelligence has accelerated operational tasks but also raised expectations for instant responses, thereby intensifying anxiety within organizations. In this context, the project manager's role becomes even more critical: establishing priorities, shielding the team from false urgencies, creating predictability, making decisions, and instilling confidence. Listen to the podcast to learn more about!

In this episode, Ricardo discusses the new PMP certification exam. He explains that updating the exam is a natural progression, as project management has evolved with artificial intelligence, agile methods, distributed teams, and new challenges. He highlights that the PMP exam has always prioritized the ability to analyze situations, make decisions, lead teams, and deliver value, rather than simply memorizing concepts. Ricardo also emphasizes that previous versions of the PMBOK® remain relevant because project management fundamentals stay the same, while only the context and tools evolve. His recommendation is to stay up to date without believing that all prior knowledge has lost its value. Listen to the podcast to learn more about!

In this podcast, Ricardo argues that many projects are not actually late; instead, their schedules were unrealistic from the beginning. He explains that organizations often approve aggressive timelines to satisfy executives, budgets, or customer expectations, only to blame the project team when those plans fail. Ricardo emphasizes that early estimates are always surrounded by uncertainty, making unrealistic forecasts a planning problem rather than an execution issue. While artificial intelligence can quickly generate detailed schedules, its results are only as reliable as the assumptions behind them. Therefore, project managers must challenge deadlines and question key assumptions before approval. Effective planning requires honesty about risks, constraints, capacity, and uncertainty, because expectations alone do not deliver projects—people executing realistic plans do.