We put the Hermes agent to work on cold email outreach to pull in new partnerships and sponsors for BridgeMind. After just eight minutes of processing a to-do list and delegating tasks, it was already executing code. It looks like it is using Python to run search requests entirely in the background. I am letting it do its thing right now. I will share the final results once the automated outreach is finished. Drop a comment if you want to see the final results of this automated outreach. #vibecoding #agenticcoding #aicoding #python #coldemail #aiagents #shipfast

ClimateCare Bot! 💻 I’m excited to share a look at a mini-project I built to practice Conditional Statements (if-elif-else) in Python! In this project, I focused on: Logic Building: Creating specific instructions based on different temperature ranges. User Input: Making the program interactive and responsive. Practical Application: Solving a real-world scenario with clean code. Understanding how to control the flow of a program through conditions is a major milestone in my coding journey. Each small script is a step closer to mastering AI and Data Science! #PythonProgramming #CodingJourney #WomenInTech #LogicBuilding #VSCode #ClimateCareBot"

GitVizz combines Tree-sitter AST parsing, interactive dependency graphs, auto-generated documentation, and multi-LLM repo chat (Claude, GPT, Gemini, Groq) in one deployable stack. Its LLM context builder assembles structured prompts from repo topology … your model gets navigable context instead of dumped files. Also ships as a standalone Python library, so the analysis layer embeds into your own tooling. 360 stars, MIT, Docker-ready. #GitVizz #codeVisualization #contextEngineering #LLM

🚀 Day 28 of Problem Solving Journey Today, I worked on an interesting problem: Group Anagrams 🔍 Problem Statement: Given an array of strings, group the anagrams together. Anagrams are words that have the same characters but arranged differently. 💡 Approaches I explored: ✅ Approach 1: Character Frequency Count (Optimized) Used a fixed-size array (26 letters) to count character occurrences Converted the count into a tuple to use as a dictionary key Achieved an efficient time complexity of O(n * k) ✅ Approach 2: Sorting Strings Sorted each string and used it as a key Simple and intuitive approach Time complexity: O(n * k log k) 📌 Key Learning: Understanding how hashing works with different representations (frequency vs sorted string) helps in optimizing solutions. ⚡ Takeaway: There are always multiple ways to solve a problem, but choosing the most efficient one makes a difference in real-world applications and interviews. 💻 Tech Used: Python | HashMap | Arrays #Day28 #ProblemSolving #Python #DataStructures #Algorithms #CodingJourney #100DaysOfCode

🚀 Day 5 – Expanding Problem-Solving Perspective What looks simple… often has deeper layers. Showing up daily is compounding 🔥 📌 Today’s Problem: Swap Two Numbers Initially, I thought swapping is just about using a temporary variable. But diving deeper changed that mindset. 🔹 Approaches Explored 1️⃣ Naive Approach → Using a third variable (temp) 2️⃣ Expected Approach → Swapping without using a third variable 3️⃣ Alternate Approach → Using built-in swapping 💡 Key Takeaway One simple problem. Three different approaches. ✔️ Learned that problems can have multiple optimized solutions ✔️ Realized that thinking beyond the obvious is important 📈 Progress Update: From basic understanding → to exploring multiple solution paths Consistency is the real growth engine 🔑 #Python #ProblemSolving #100DaysOfCode #Consistency #LearningJourney #DeveloperMindset

I was cleaning a dataset — filtering rows, transforming values, the usual. My 5-line for loop worked fine. But I wanted to be "Pythonic." So I compressed it into a one-liner. Then I added another layer. The next morning I stared at it for two full minutes trying to decode my own logic. If I couldn't read it, my future teammates had no chance. This carousel breaks down: → The mental model that makes list comprehensions click instantly → The reading order most beginners get backwards → The exact rule for when to stop using them and write a real loop What's the longest you've stared at your own code before realizing you had no idea what it does? #Python #DataAnalytics #DataAnalyst #PythonTips #LearnInPublic #AHAMoments #DataAnalystJourney

🚀 Cracked “Top K Frequent Elements” with an Optimal Approach! Today I solved one of the most important interview problems on LeetCode using an efficient Bucket Sort approach (O(n)) — and got it accepted ✅ 🔍 Problem Insight: Instead of sorting (which takes O(n log n)), I used frequency as an index to directly access elements with higher occurrence. 💡 Key Learnings: How to reduce time complexity from O(n log n) → O(n) Using hashmaps (Counter) for frequency counting Applying bucket sort for optimization Writing clean and interview-ready code ⚡ Complexity Analysis: Time Complexity: O(n) (Frequency count + bucket fill + traversal) Space Complexity: O(n) (Hashmap + bucket storage) ⚡ Performance: Runtime: 10 ms 🧠 Approach Summary: Count frequency of elements Store elements in buckets based on frequency Traverse from highest frequency to get top K elements 📌 Consistency > Perfection Every problem solved is one step closer to mastering DSA. #DataStructures #Algorithms #Python #LeetCode #CodingJourney #ProblemSolving #TechGrowth #Consistency #Learning #DSA

How an EXCAVO indicator goes from idea to TradingView: Hypothesis — "Does this concept have an edge?" Research — study the mechanics, find the data Build — write the code, test on charts Backtest — Python, historical data, multiple markets Kill or ship — most ideas die here The 27 indicators on our TradingView survived this process. The strategies we run privately survived even more. We don't publish things we wouldn't use ourselves. #Trading #SystematicTrading #Process

🚀 Day 3 – Building a Problem-Solving Mindset Still on the grind. Still showing up. Because consistency > motivation. 📌 Today’s Problem: Sum of N Natural Numbers Looks simple. But again… the goal is not just solving — it’s how efficiently you think. 🔹 Approaches Explored 1️⃣ Naive Approach → Basic step-by-step addition 2️⃣ Using Recursion → Function calling itself to solve smaller parts 3️⃣ Formula-Based Approach → Direct mathematical solution for maximum efficiency 💡 Key Takeaway Same problem. Three different approaches. Different levels of thinking. ✔️ Learned how multiple solutions exist for one problem ✔️ Understood that efficiency improves with better thinking 📈 Progress Update: From solving problems → to choosing the best approach Consistency is the real unlock 🔑 #Python #ProblemSolving #100DaysOfCode #Consistency #LearningJourney #DeveloperMindset

Just solved “First Matching Character From Both Ends” 🚀 💡 My approach (simple & efficient): Instead of overcomplicating it, I used a two-pointer mindset without explicitly creating two pointers. Loop through the string from the start For each index i, compare: s[i] (from the front) s[n - i - 1] (from the back) The moment both match → return the index If no match → return -1 ✨ This works because we're checking symmetry from both ends in a single pass (O(n)) with O(1) space. Sometimes the best solutions aren’t fancy — they’re just clean and intuitive. 🔥 Consistency > Complexity. Small wins like this build strong problem-solving instincts. #LeetCode #DSA #Python #CodingJourney #ProblemSolving #TechGrowth #CodeDaily #WomenInTech #FutureEngineer #100DaysOfCode #KeepBuilding