fix: update references and smooth first paragraph

essay.md

@@ -4,15 +4,15 @@
 
 By: Peter M. Palles
 
-Software engineering is standing on the edge of a structural shift unlike anything the industry has seen since the rise of the internet. For decades, progress relied on adding more people, more processes, and more layers of coordination. But the next generation of engineering will belong not to the largest teams, but to the _smallest, most skilled_ engineers—those who learn to command hives and swarms of intelligent agents (Ghahramani, 2024; Reflection AI, 2024).
+Software engineering is standing on the edge of a structural shift unlike anything the industry has seen since the rise of the internet. For decades, progress relied on adding more people, more processes, and more layers of coordination. But the next generation of engineering will belong not to the largest teams, but to small, elite teams—those who learn to command hives and swarms of intelligent agents (Russell & Norvig, 2020; Wooldridge, 2009; Beni & Wang, 1989).
 
 In this emerging model, a single engineer equipped with a well-orchestrated swarm can achieve what once required an entire department. Architect agents establish the blueprint. Planner agents transform broad goals into precise task graphs. Coders and reviewers operate in parallel, generating clean, test-driven patches under strict safety, provenance, and audit constraints. A hive becomes an extension of the engineer’s mind: a tool for reasoning, building, validating, and iterating at scale (Cognition AI, 2024; Google, 2024).
 
 This changes the profession in three profound ways.
 
-**First**, software engineering becomes more cognitive than mechanical. The value of a human engineer shifts toward problem framing, systems thinking, domain expertise, and quality control. Everything downstream—the code, tests, documentation, and structure—can be delegated to a swarm that works deterministically and verifiably, with the engineer guiding the intent and reviewing the results.
+**First**, software engineering becomes more cognitive than mechanical. The value of a human engineer shifts toward problem framing, systems thinking, domain expertise, and quality control. Everything downstream—the code, tests, documentation, and structure—can be delegated to a swarm that works deterministically and verifiably, with the engineer guiding the intent and reviewing the results (Amershi et al., 2019).
 
-**Second**, the productivity delta between a top-tier engineer and an average one grows exponentially. Swarm systems are not a universal equalizer; they are force multipliers. The more precise, methodical, and senior the engineer, the more leverage they generate from a hive. Just as a master carpenter extracts more capability from tools than an apprentice, an expert engineer can extract far greater capability from intelligent, parallel, tireless digital tools.
+**Second**, the productivity delta between a top-tier engineer and an average one grows exponentially. Swarm systems are not a universal equalizer; they are force multipliers. The more precise, methodical, and senior the engineer, the more leverage they generate from a hive. Just as a master carpenter extracts more capability from tools than an apprentice, an expert engineer can extract far greater capability from intelligent, parallel, tireless digital tools (Daugherty & Wilson, 2018).
 
 **Third**, the nature of teams transforms. Instead of 20 engineers coordinating tasks and merging pull requests, a future team may consist of 3–5 senior engineers, each wielding their own hive. Coordination scales down; execution scales up. The team becomes more resilient, more consistent, and more capable of solving problems previously out of reach.
 
@@ -22,14 +22,22 @@ We are entering an era where a single engineer can build a platform, ship a prod
 
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-# **References (APA 7th Edition)**
+# **References**
 
-Cognition AI. (2024). _Devin: The AI software engineer_. [https://devin.ai/](https://devin.ai/)
+Amershi, S., Weld, D. S., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., … & Horvitz, E. (2019). _Guidelines for human-AI interaction._ CHI Conference on Human Factors in Computing Systems.
 
-Ghahramani, Z. (2024). _The future of AI-assisted engineering_. Google DeepMind. (Conceptual reference; no direct quotation)
+Beni, G., & Wang, J. (1989). _Swarm intelligence in cellular robotic systems._ Proceedings of the NATO Advanced Workshop on Robots and Biological Systems.
 
-Google. (2024). _Antigravity: Agentic development environment_. [https://antigravity.google/](https://antigravity.google/)
+Cognition AI. (2024). Devin: _The AI software engineer._ https://devin.ai/
 
-Reflection AI. (2024). _Agentic systems and multi-agent collaboration_. Anthropic Research Notes. (Conceptual reference; no direct quotation)
+Daugherty, P. R., & Wilson, H. J. (2018). _Human + machine: Reimagining work in the age of AI._ Harvard Business Review Press.
 
-Wooldridge, M. (2021). _A concise introduction to multiagent systems and distributed AI_. MIT Press. (Background theory on multi-agent systems)
+Google. (2024). _Antigravity: Agentic development environment._ https://antigravity.google/
+
+Lee, K.-F. (2018). _AI superpowers: China, Silicon Valley, and the new world order._ Houghton Mifflin Harcourt.
+
+Russell, S. J., & Norvig, P. (2020). _Artificial intelligence: A modern approach_ (4th ed.). Pearson.
+
+Suleyman, M., with Bhaskar, M. (2023). _The coming wave: AI, power, and the twenty-first century's greatest dilemma._ Crown.
+
+Wooldridge, M. (2009). _An introduction to multiagent systems_ (2nd ed.). Wiley.