Tools: Fail Fast, Fail Forward

For a long time, I thought failing meant I had done something wrong.
Over time, I realized it usually meant I waited too long to test an idea, ask a question, or try a different approach. Fail fast, fail forward is not about celebrating failure.
It is about 𝐫𝐞𝐝𝐮𝐜𝐢𝐧𝐠 𝐭𝐡𝐞 𝐜𝐨𝐬𝐭 𝐨𝐟 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠. What fail fast actually means Fail fast means 𝐠𝐞𝐭𝐭𝐢𝐧𝐠 𝐟𝐞𝐞𝐝𝐛𝐚𝐜𝐤 𝐞𝐚𝐫𝐥𝐲. Instead of spending weeks polishing something in isolation, you put it in front of reality as soon as possible. Reality can be code running, a question asked in a meeting, or trying a new approach even if you are not fully confident yet. The goal is not speed for the sake of speed.
The goal is 𝐜𝐥𝐚𝐫𝐢𝐭𝐲. A technical example from data structures This idea shows up very clearly in data structures. In Java, HashMap is a good example of a 𝐟𝐚𝐢𝐥 𝐟𝐚𝐬𝐭 data structure. When you iterate over a HashMap and modify it at the same time, Java throws an exception immediately. It does not try to recover or continue quietly. It stops execution so the problem is visible right away. This behavior is intentional. The goal is not to make the program crash randomly.
The goal is to 𝐬𝐮𝐫𝐟𝐚𝐜𝐞 𝐛𝐮𝐠𝐬 𝐞𝐚𝐫𝐥𝐲, while they are still easy to understand and fix. Other data structures are designed to be 𝐟𝐚𝐢𝐥 𝐬𝐚𝐟𝐞. For example, collections like CopyOnWriteArrayList work on a copy of the data. Modifications do not affect the current iteration, so the program continues running without throwing an error. This feels safer, but it also means issues can go unnoticed longer. Neither approach is wrong.
They solve different problems. Fail fast structures prioritize 𝐞𝐚𝐫𝐥𝐲 𝐟𝐞𝐞𝐝𝐛𝐚𝐜𝐤 𝐚𝐧𝐝 𝐜𝐨𝐫𝐫𝐞𝐜𝐭𝐧𝐞𝐬𝐬.
Fail safe structures prioritize 𝐬𝐭𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐜𝐨𝐧𝐭𝐢𝐧𝐮𝐢𝐭𝐲. Seeing this in code helped me understand the idea beyond theory. A simple example from backend development When I started building backend APIs, I would often overthink structure before even running the application. I wanted everything to be clean before seeing if it actually worked. That usually backfired. Now I run the application early, even if the code is incomplete. Errors show up quickly. Misunderstandings become obvious. I learn what the framework expects instead of guessing. Failing fast here means I spend less time being stuck and more time 𝐚𝐝𝐣𝐮𝐬𝐭𝐢𝐧𝐠 𝐢𝐧 𝐭𝐡𝐞 𝐫𝐢𝐠𝐡𝐭 𝐝𝐢𝐫𝐞𝐜𝐭𝐢𝐨𝐧. Applying this idea to public speaking Public speaking did not become easier because I suddenly felt confident.
It became easier because I stopped waiting until I felt ready. Early speeches were imperfect. Timing was off. Feedback was direct. None of that meant I was bad at speaking. It showed me what needed attention next. Failing forward meant taking that feedback and applying 𝐨𝐧𝐞 𝐬𝐦𝐚𝐥𝐥 𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭 𝐚𝐭 𝐚 𝐭𝐢𝐦𝐞, instead of trying to fix everything at once. Why failing forward matters more than failing fast Failing fast gives you information.
Failing forward means 𝐲𝐨𝐮 𝐮𝐬𝐞 𝐢𝐭. Failing forward looks like: Making 𝐨𝐧𝐞 𝐚𝐝𝐣𝐮𝐬𝐭𝐦𝐞𝐧𝐭 based on feedback Asking a 𝐜𝐥𝐞𝐚𝐫𝐞𝐫 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 next time Trying again with 𝐬𝐥𝐢𝐠𝐡𝐭𝐥𝐲 𝐛𝐞𝐭𝐭𝐞𝐫 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 It is not dramatic. Most progress is 𝐢𝐧𝐜𝐫𝐞𝐦𝐞𝐧𝐭𝐚𝐥 𝐚𝐧𝐝 𝐪𝐮𝐢𝐞𝐭. The model I follow is simple: Observe what does not work There is 𝐧𝐨 𝐩𝐞𝐫𝐟𝐞𝐜𝐭 𝐭𝐢𝐦𝐞 𝐭𝐨 𝐬𝐭𝐚𝐫𝐭.
There is 𝐧𝐨 𝐛𝐞𝐧𝐞𝐟𝐢𝐭 𝐢𝐧 𝐰𝐚𝐢𝐭𝐢𝐧𝐠 This is the same approach I use in tech, learning, and preparing workshops. What I'm working on next I am excited to share that I will be giving a workshop titled: 𝐀 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫-𝐅𝐫𝐢𝐞𝐧𝐝𝐥𝐲 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩: 𝐇𝐨𝐰 𝐭𝐨 𝐒𝐩𝐞𝐚𝐤 𝐂𝐨𝐦𝐟𝐨𝐫𝐭𝐚𝐛𝐥𝐲 𝐢𝐧 𝐏𝐮𝐛𝐥𝐢𝐜 The ideas around failing fast and failing forward are a core part of how I approach public speaking, especially for beginners who feel pressure to be confident before they start. I will write more about the process, lessons, and practical exercises from this workshop in future blog posts. Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to ? It will become hidden in your post, but will still be visible via the comment's permalink. as well , this person and/or - Observe what does not work
- Adjust one thing