As AI takes over most code generation, the act of writing code by hand will become obsolete for practical purposes. Like calligraphy, it will transform into a rare and admired art form, appreciated for its craft and the human touch rather than its necessity in software development.
When an AI makes a mistake, avoid angry or emotional prompts. The model is trained to be agreeable and will waste its limited context window (tokens) formulating an apology and de-escalating the situation, rather than dedicating all its resources to fixing the underlying problem.
The historical separation between product management, design, and engineering is dissolving. AI assistants handle the coding, allowing a single person to define the product (PM), ensure high-quality aesthetics and UX (designer), and direct the technical implementation (engineer), thus converging the three roles.
People without a coding background approach AI tools with a "positively delusional" mindset, attempting tasks that technical experts might deem impossible. This unbiased approach often leads to discovering novel capabilities of AI platforms and pushing their boundaries in unexpected ways.
Since AI can generate output rapidly, the differentiator is no longer speed but the quality of your judgment and clarity. AI acts as an amplifier; if your input lacks taste or direction, you'll simply produce "garbage faster." The most valuable skills become decision-making and refinement.
AI agents have limited context windows and "forget" earlier instructions. To solve this, generate PRDs (e.g., master plan, design guidelines) and a task list. Then, instruct the agent to reference these documents before every action, effectively creating a persistent, dynamic source of truth for the project.
To quickly clarify a product idea, create multiple versions in parallel using different inputs for each: a simple brain dump, a structured prompt, a visual design reference, and an existing code snippet. This process rapidly reveals the best direction and saves significant time on later refinement cycles.
Jobs based on deterministic, logical tasks are highly susceptible to AI replacement. Durable careers will be built on skills that rely on nuanced human understanding, like emotional intelligence, taste, and creativity. AI will replace translators but not comedians, because it lacks a true understanding of humor.
After solving a problem with an AI tool, don't just move on. Ask the AI agent how you could have phrased your prompt differently to avoid the issue or solve it faster. This creates a powerful feedback loop that continuously improves your ability to communicate effectively with the AI.
Don't wait for a job title to start working as a professional AI developer. Begin building projects, sharing your process and learnings publicly on platforms like LinkedIn or YouTube, and developing a portfolio. This demonstrates your skills and passion, making you an obvious hire for companies looking for this new role.
AI lacks the implicit context humans share. Like a genie granting a wish for "taller" by making you 13 feet tall, AI will interpret vague prompts literally and produce dysfunctional results. Success requires extreme specificity and clarity in your requests because the AI doesn't know what you "mean."
A four-step method for non-technical users to debug AI code. First, use the tool's auto-fix feature. Second, ask the AI to add console logs to increase its awareness. Third, use an external tool like OpenAI's Codex for a "second opinion." Finally, revert to a working version and re-prompt with more clarity.